Warning: Permanently added '13.221.82.233' (ED25519) to the list of known hosts. You can reproduce this build on your computer by running: sudo dnf install copr-rpmbuild /usr/bin/copr-rpmbuild --verbose --drop-resultdir --task-url https://copr.fedorainfracloud.org/backend/get-build-task/10028966-fedora-43-aarch64 --chroot fedora-43-aarch64 Version: 1.6 PID: 19313 Logging PID: 19315 Task: {'allow_user_ssh': False, 'appstream': False, 'background': True, 'build_id': 10028966, 'buildroot_pkgs': [], 'chroot': 'fedora-43-aarch64', 'enable_net': False, 'fedora_review': False, 'git_hash': '687368ccfb7e67e53490d9eb793b5baa2d3d64bd', 'git_repo': 'https://copr-dist-git.fedorainfracloud.org/git/psimovec/scipy-1.8.3/python-pyscf', 'isolation': 'default', 'memory_reqs': 2048, 'package_name': 'python-pyscf', 'package_version': '2.11.0-2', 'project_dirname': 'scipy-1.8.3', 'project_name': 'scipy-1.8.3', 'project_owner': 'psimovec', 'repo_priority': None, 'repos': [{'baseurl': 'https://download.copr.fedorainfracloud.org/results/psimovec/scipy-1.8.3/fedora-43-aarch64/', 'id': 'copr_base', 'name': 'Copr repository', 'priority': None}, {'baseurl': 'http://kojipkgs.fedoraproject.org/repos/rawhide/latest/$basearch/', 'id': 'http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch', 'name': 'Additional repo http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch'}], 'sandbox': 'psimovec/scipy-1.8.3--https://src.fedoraproject.org/user/releng', 'source_json': {}, 'source_type': None, 'ssh_public_keys': None, 'storage': 0, 'submitter': 'https://src.fedoraproject.org/user/releng', 'tags': [], 'task_id': '10028966-fedora-43-aarch64', 'timeout': 18000, 'uses_devel_repo': False, 'with_opts': [], 'without_opts': []} Running: git clone https://copr-dist-git.fedorainfracloud.org/git/psimovec/scipy-1.8.3/python-pyscf /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf --depth 500 --no-single-branch --recursive cmd: ['git', 'clone', 'https://copr-dist-git.fedorainfracloud.org/git/psimovec/scipy-1.8.3/python-pyscf', '/var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf', '--depth', '500', '--no-single-branch', '--recursive'] cwd: . rc: 0 stdout: stderr: Cloning into '/var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf'... Running: git checkout 687368ccfb7e67e53490d9eb793b5baa2d3d64bd -- cmd: ['git', 'checkout', '687368ccfb7e67e53490d9eb793b5baa2d3d64bd', '--'] cwd: /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf rc: 0 stdout: stderr: Note: switching to '687368ccfb7e67e53490d9eb793b5baa2d3d64bd'. You are in 'detached HEAD' state. You can look around, make experimental changes and commit them, and you can discard any commits you make in this state without impacting any branches by switching back to a branch. If you want to create a new branch to retain commits you create, you may do so (now or later) by using -c with the switch command. Example: git switch -c Or undo this operation with: git switch - Turn off this advice by setting config variable advice.detachedHead to false HEAD is now at 687368c automatic import of python-pyscf Running: dist-git-client sources cmd: ['dist-git-client', 'sources'] cwd: /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf rc: 0 stdout: stderr: INFO: Reading stdout from command: git rev-parse --abbrev-ref HEAD INFO: Reading stdout from command: git rev-parse HEAD INFO: Reading sources specification file: sources INFO: Downloading pyscf-2.11.0.tar.gz INFO: Reading stdout from command: curl --help all INFO: Calling: curl -H Pragma: -o pyscf-2.11.0.tar.gz --location --connect-timeout 60 --retry 3 --retry-delay 10 --remote-time --show-error --fail --retry-all-errors https://copr-dist-git.fedorainfracloud.org/repo/pkgs/psimovec/scipy-1.8.3/python-pyscf/pyscf-2.11.0.tar.gz/md5/168792ff957ce24df1141e5ae2147149/pyscf-2.11.0.tar.gz % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 11.1M 100 11.1M 0 0 255M 0 --:--:-- --:--:-- --:--:-- 259M INFO: Reading stdout from command: md5sum pyscf-2.11.0.tar.gz tail: /var/lib/copr-rpmbuild/main.log: file truncated Running (timeout=18000): unbuffer mock --spec /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf/python-pyscf.spec --sources /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf --resultdir /var/lib/copr-rpmbuild/results --uniqueext 1768641411.012166 -r /var/lib/copr-rpmbuild/results/configs/child.cfg INFO: mock.py version 6.6 starting (python version = 3.13.7, NVR = mock-6.6-1.fc42), args: /usr/libexec/mock/mock --spec /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf/python-pyscf.spec --sources /var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf --resultdir /var/lib/copr-rpmbuild/results --uniqueext 1768641411.012166 -r /var/lib/copr-rpmbuild/results/configs/child.cfg Start(bootstrap): init plugins INFO: tmpfs initialized INFO: selinux enabled INFO: chroot_scan: initialized INFO: compress_logs: initialized Finish(bootstrap): init plugins Start: init plugins INFO: tmpfs initialized INFO: selinux enabled INFO: chroot_scan: initialized INFO: compress_logs: initialized Finish: init plugins INFO: Signal handler active Start: run INFO: Start(/var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf/python-pyscf.spec) Config(fedora-43-aarch64) Start: clean chroot Finish: clean chroot Mock Version: 6.6 INFO: Mock Version: 6.6 Start(bootstrap): chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-43-aarch64-bootstrap-1768641411.012166/root. INFO: calling preinit hooks INFO: enabled root cache INFO: enabled package manager cache Start(bootstrap): cleaning package manager metadata Finish(bootstrap): cleaning package manager metadata INFO: Guessed host environment type: unknown INFO: Using container image: registry.fedoraproject.org/fedora:43 INFO: Pulling image: registry.fedoraproject.org/fedora:43 INFO: Tagging container image as mock-bootstrap-1e83ff44-853f-4be3-92bb-dd8c952a3b26 INFO: Checking that ed1f61cf9b299ccd28f27c38efda5671270554bc02239dd101b224e43936684a image matches host's architecture INFO: Copy content of container ed1f61cf9b299ccd28f27c38efda5671270554bc02239dd101b224e43936684a to /var/lib/mock/fedora-43-aarch64-bootstrap-1768641411.012166/root INFO: mounting ed1f61cf9b299ccd28f27c38efda5671270554bc02239dd101b224e43936684a with podman image mount INFO: image ed1f61cf9b299ccd28f27c38efda5671270554bc02239dd101b224e43936684a as /var/lib/containers/storage/overlay/4fb5d1b72552f9b8e8bc0c32de43a490df75a5045b899fd73d84c1d46b25c1a6/merged INFO: umounting image ed1f61cf9b299ccd28f27c38efda5671270554bc02239dd101b224e43936684a (/var/lib/containers/storage/overlay/4fb5d1b72552f9b8e8bc0c32de43a490df75a5045b899fd73d84c1d46b25c1a6/merged) with podman image umount INFO: Removing image mock-bootstrap-1e83ff44-853f-4be3-92bb-dd8c952a3b26 INFO: Package manager dnf5 detected and used (fallback) INFO: Not updating bootstrap chroot, bootstrap_image_ready=True Start(bootstrap): creating root cache Finish(bootstrap): creating root cache Finish(bootstrap): chroot init Start: chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-43-aarch64-1768641411.012166/root. INFO: calling preinit hooks INFO: enabled root cache INFO: enabled package manager cache Start: cleaning package manager metadata Finish: cleaning package manager metadata INFO: enabled HW Info plugin INFO: Package manager dnf5 detected and used (direct choice) INFO: Buildroot is handled by package management downloaded with a bootstrap image: rpm-6.0.1-1.fc43.aarch64 rpm-sequoia-1.10.0-1.fc43.aarch64 dnf5-5.2.17.0-2.fc43.aarch64 dnf5-plugins-5.2.17.0-2.fc43.aarch64 Start: installing minimal buildroot with dnf5 Updating and loading repositories: Copr repository 100% | 1.2 MiB/s | 370.9 KiB | 00m00s fedora 100% | 24.9 MiB/s | 37.8 MiB | 00m02s updates 100% | 12.5 MiB/s | 18.8 MiB | 00m02s Additional repo http_kojipkgs_fedorapr 100% | 4.8 MiB/s | 14.2 MiB | 00m03s Repositories loaded. 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http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 500.0 B qt6-srpm-macros noarch 6.10.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 464.0 B readline aarch64 8.3-3.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 563.5 KiB rpm aarch64 6.0.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 3.3 MiB rpm-build-libs aarch64 6.0.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 264.1 KiB rpm-libs aarch64 6.0.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 995.5 KiB rpm-plugin-selinux aarch64 6.0.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 68.0 KiB rpm-sequoia aarch64 1.10.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 2.3 MiB rpm-sign-libs aarch64 6.0.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 67.8 KiB rust-srpm-macros noarch 28.4-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 5.5 KiB selinux-policy noarch 42.21-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 32.0 KiB selinux-policy-targeted noarch 42.21-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 18.4 MiB setup noarch 2.15.0-27.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 724.9 KiB sqlite-libs aarch64 3.51.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.5 MiB systemd-libs aarch64 259-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 2.5 MiB systemd-standalone-sysusers aarch64 259-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 329.6 KiB tpm2-tss aarch64 4.1.3-8.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 2.1 MiB tree-sitter-srpm-macros noarch 0.4.2-1.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 8.3 KiB util-linux-core aarch64 2.41.3-11.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 2.4 MiB xxhash-libs aarch64 0.8.3-3.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 86.0 KiB xz-libs aarch64 1:5.8.2-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 201.4 KiB zig-srpm-macros noarch 1-7.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.3 KiB zip aarch64 3.0-44.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 762.5 KiB zlib-ng-compat aarch64 2.3.2-2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 133.3 KiB zstd aarch64 1.5.7-3.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 574.0 KiB Installing groups: Buildsystem building group Transaction Summary: Installing: 182 packages Total size of inbound packages is 65 MiB. Need to download 65 MiB. After this operation, 248 MiB extra will be used (install 248 MiB, remove 0 B). [ 1/182] bzip2-0:1.0.8-21.fc43.aarch64 100% | 122.2 KiB/s | 51.6 KiB | 00m00s [ 2/182] cpio-0:2.15-6.fc43.aarch64 100% | 1.1 MiB/s | 283.0 KiB | 00m00s [ 3/182] coreutils-0:9.9-2.fc44.aarch6 100% | 1.2 MiB/s | 1.1 MiB | 00m01s [ 4/182] diffutils-0:3.12-3.fc43.aarch 100% | 1.3 MiB/s | 381.5 KiB | 00m00s [ 5/182] fedora-release-common-0:44-0. 100% | 177.5 KiB/s | 24.7 KiB | 00m00s [ 6/182] bash-0:5.3.9-1.fc44.aarch64 100% | 1.6 MiB/s | 1.8 MiB | 00m01s [ 7/182] findutils-1:4.10.0-6.fc43.aar 100% | 2.1 MiB/s | 544.0 KiB | 00m00s [ 8/182] glibc-minimal-langpack-0:2.42 100% | 618.4 KiB/s | 74.8 KiB | 00m00s [ 9/182] gawk-0:5.3.2-2.fc43.aarch64 100% | 3.3 MiB/s | 1.1 MiB | 00m00s [ 10/182] gzip-0:1.14-1.fc44.aarch64 100% | 1.0 MiB/s | 166.5 KiB | 00m00s [ 11/182] grep-0:3.12-2.fc43.aarch64 100% | 1.3 MiB/s | 286.2 KiB | 00m00s [ 12/182] info-0:7.2-7.fc44.aarch64 100% | 1.1 MiB/s | 179.5 KiB | 00m00s [ 13/182] patch-0:2.8-3.fc44.aarch64 100% | 703.6 KiB/s | 111.9 KiB | 00m00s [ 14/182] redhat-rpm-config-0:343-19.fc 100% | 451.7 KiB/s | 73.2 KiB | 00m00s [ 15/182] rpm-build-0:6.0.1-1.fc44.aarc 100% | 788.4 KiB/s | 124.6 KiB | 00m00s [ 16/182] sed-0:4.9-6.fc44.aarch64 100% | 1.2 MiB/s | 306.2 KiB | 00m00s [ 17/182] unzip-0:6.0-68.fc44.aarch64 100% | 1.1 MiB/s | 186.4 KiB | 00m00s [ 18/182] shadow-utils-2:4.18.0-7.fc44. 100% | 2.4 MiB/s | 1.2 MiB | 00m01s [ 19/182] tar-2:1.35-6.fc43.aarch64 100% | 1.9 MiB/s | 842.2 KiB | 00m00s [ 20/182] which-0:2.23-3.fc43.aarch64 100% | 289.2 KiB/s | 41.4 KiB | 00m00s [ 21/182] xz-1:5.8.2-1.fc44.aarch64 100% | 2.0 MiB/s | 589.6 KiB | 00m00s [ 22/182] util-linux-0:2.41.3-11.fc44.a 100% | 2.6 MiB/s | 1.1 MiB | 00m00s [ 23/182] fedora-repos-0:44-0.1.noarch 100% | 67.2 KiB/s | 9.1 KiB | 00m00s [ 24/182] glibc-common-0:2.42.9000-22.f 100% | 1.6 MiB/s | 344.3 KiB | 00m00s [ 25/182] coreutils-common-0:9.9-2.fc44 100% | 3.8 MiB/s | 2.1 MiB | 00m01s [ 26/182] glibc-0:2.42.9000-22.fc44.aar 100% | 4.0 MiB/s | 1.9 MiB | 00m00s [ 27/182] libblkid-0:2.41.3-11.fc44.aar 100% | 914.8 KiB/s | 121.7 KiB | 00m00s [ 28/182] rpm-0:6.0.1-1.fc44.aarch64 100% | 2.7 MiB/s | 545.5 KiB | 00m00s [ 29/182] libfdisk-0:2.41.3-11.fc44.aar 100% | 1.2 MiB/s | 154.1 KiB | 00m00s [ 30/182] liblastlog2-0:2.41.3-11.fc44. 100% | 173.4 KiB/s | 23.2 KiB | 00m00s [ 31/182] libmount-0:2.41.3-11.fc44.aar 100% | 1.1 MiB/s | 157.7 KiB | 00m00s [ 32/182] libsmartcols-0:2.41.3-11.fc44 100% | 597.9 KiB/s | 82.5 KiB | 00m00s [ 33/182] libuuid-0:2.41.3-11.fc44.aarc 100% | 178.2 KiB/s | 25.7 KiB | 00m00s [ 34/182] util-linux-core-0:2.41.3-11.f 100% | 2.3 MiB/s | 523.6 KiB | 00m00s [ 35/182] xz-libs-1:5.8.2-1.fc44.aarch6 100% | 726.2 KiB/s | 111.1 KiB | 00m00s [ 36/182] fedora-gpg-keys-0:44-0.1.noar 100% | 808.3 KiB/s | 127.7 KiB | 00m00s [ 37/182] fedora-repos-rawhide-0:44-0.1 100% | 54.7 KiB/s | 8.6 KiB | 00m00s [ 38/182] rpm-libs-0:6.0.1-1.fc44.aarch 100% | 2.3 MiB/s | 379.8 KiB | 00m00s [ 39/182] rpm-build-libs-0:6.0.1-1.fc44 100% | 758.2 KiB/s | 117.5 KiB | 00m00s [ 40/182] rpm-sign-libs-0:6.0.1-1.fc44. 100% | 185.6 KiB/s | 27.3 KiB | 00m00s [ 41/182] glibc-gconv-extra-0:2.42.9000 100% | 3.6 MiB/s | 1.7 MiB | 00m00s [ 42/182] libgcc-0:16.0.1-0.2.fc44.aarc 100% | 651.9 KiB/s | 95.8 KiB | 00m00s [ 43/182] filesystem-0:3.18-50.fc43.aar 100% | 4.7 MiB/s | 1.3 MiB | 00m00s [ 44/182] libselinux-0:3.9-6.fc44.aarch 100% | 738.3 KiB/s | 96.7 KiB | 00m00s [ 45/182] libxcrypt-0:4.5.2-2.fc44.aarc 100% | 956.8 KiB/s | 125.3 KiB | 00m00s [ 46/182] ncurses-libs-0:6.5-8.20250614 100% | 2.4 MiB/s | 324.8 KiB | 00m00s [ 47/182] ncurses-base-0:6.5-8.20250614 100% | 444.4 KiB/s | 63.5 KiB | 00m00s [ 48/182] audit-libs-0:4.1.2-2.fc44.aar 100% | 920.5 KiB/s | 139.9 KiB | 00m00s [ 49/182] systemd-libs-0:259-1.fc44.aar 100% | 3.3 MiB/s | 784.8 KiB | 00m00s [ 50/182] libcap-ng-0:0.9-2.fc44.aarch6 100% | 194.2 KiB/s | 32.4 KiB | 00m00s [ 51/182] pam-libs-0:1.7.1-4.fc44.aarch 100% | 348.0 KiB/s | 56.7 KiB | 00m00s [ 52/182] readline-0:8.3-3.fc44.aarch64 100% | 1.3 MiB/s | 221.8 KiB | 00m00s [ 53/182] zlib-ng-compat-0:2.3.2-2.fc44 100% | 433.0 KiB/s | 72.3 KiB | 00m00s [ 54/182] bzip2-libs-0:1.0.8-21.fc43.aa 100% | 258.8 KiB/s | 40.9 KiB | 00m00s [ 55/182] libacl-0:2.3.2-4.fc43.aarch64 100% | 149.2 KiB/s | 24.2 KiB | 00m00s [ 56/182] libeconf-0:0.7.9-2.fc43.aarch 100% | 218.4 KiB/s | 35.2 KiB | 00m00s [ 57/182] libsemanage-0:3.9-4.fc44.aarc 100% | 790.7 KiB/s | 119.4 KiB | 00m00s [ 58/182] setup-0:2.15.0-27.fc44.noarch 100% | 1.0 MiB/s | 151.3 KiB | 00m00s [ 59/182] gnupg2-dirmngr-0:2.4.9-1.fc44 100% | 1.8 MiB/s | 266.0 KiB | 00m00s [ 60/182] gnupg2-gpg-agent-0:2.4.9-1.fc 100% | 1.7 MiB/s | 266.0 KiB | 00m00s [ 61/182] gnupg2-0:2.4.9-1.fc44.aarch64 100% | 4.3 MiB/s | 1.6 MiB | 00m00s [ 62/182] gnupg2-gpgconf-0:2.4.9-1.fc44 100% | 774.3 KiB/s | 113.8 KiB | 00m00s [ 63/182] gnupg2-keyboxd-0:2.4.9-1.fc44 100% | 607.8 KiB/s | 91.2 KiB | 00m00s [ 64/182] gnupg2-verify-0:2.4.9-1.fc44. 100% | 1.1 MiB/s | 164.1 KiB | 00m00s [ 65/182] ima-evm-utils-libs-0:1.6.2-7. 100% | 204.4 KiB/s | 29.4 KiB | 00m00s [ 66/182] libfsverity-0:1.6-3.fc43.aarc 100% | 130.8 KiB/s | 18.6 KiB | 00m00s [ 67/182] popt-0:1.19-9.fc43.aarch64 100% | 407.8 KiB/s | 58.7 KiB | 00m00s [ 68/182] libcap-0:2.77-1.fc44.aarch64 100% | 600.2 KiB/s | 88.2 KiB | 00m00s [ 69/182] libstdc++-0:16.0.1-0.2.fc44.a 100% | 3.7 MiB/s | 840.0 KiB | 00m00s [ 70/182] libzstd-0:1.5.7-3.fc44.aarch6 100% | 2.1 MiB/s | 332.1 KiB | 00m00s [ 71/182] lua-libs-0:5.4.8-4.fc44.aarch 100% | 849.8 KiB/s | 129.2 KiB | 00m00s [ 72/182] rpm-sequoia-0:1.10.0-1.fc44.a 100% | 3.9 MiB/s | 885.3 KiB | 00m00s [ 73/182] elfutils-libelf-0:0.194-2.fc4 100% | 1.3 MiB/s | 201.7 KiB | 00m00s [ 74/182] sqlite-libs-0:3.51.0-1.fc44.a 100% | 3.4 MiB/s | 748.4 KiB | 00m00s [ 75/182] elfutils-libs-0:0.194-2.fc44. 100% | 1.7 MiB/s | 265.3 KiB | 00m00s [ 76/182] elfutils-0:0.194-2.fc44.aarch 100% | 3.5 MiB/s | 530.5 KiB | 00m00s [ 77/182] elfutils-debuginfod-client-0: 100% | 308.4 KiB/s | 45.6 KiB | 00m00s [ 78/182] file-0:5.46-8.fc44.aarch64 100% | 340.9 KiB/s | 49.1 KiB | 00m00s [ 79/182] file-libs-0:5.46-8.fc44.aarch 100% | 3.6 MiB/s | 848.0 KiB | 00m00s [ 80/182] libgomp-0:16.0.1-0.2.fc44.aar 100% | 1.5 MiB/s | 355.6 KiB | 00m00s [ 81/182] debugedit-0:5.2-4.fc44.aarch6 100% | 491.2 KiB/s | 84.5 KiB | 00m00s [ 82/182] pkgconf-pkg-config-0:2.3.0-3. 100% | 55.4 KiB/s | 9.6 KiB | 00m00s [ 83/182] libarchive-0:3.8.4-1.fc44.aar 100% | 1.6 MiB/s | 413.7 KiB | 00m00s [ 84/182] zstd-0:1.5.7-3.fc44.aarch64 100% | 1.3 MiB/s | 182.6 KiB | 00m00s [ 85/182] curl-0:8.18.0-1.fc44.aarch64 100% | 1.6 MiB/s | 235.2 KiB | 00m00s [ 86/182] gpgverify-0:2.2-3.fc43.noarch 100% | 84.1 KiB/s | 11.1 KiB | 00m00s [ 87/182] ansible-srpm-macros-0:1-18.1. 100% | 153.1 KiB/s | 19.9 KiB | 00m00s [ 88/182] binutils-0:2.45.50-16.fc44.aa 100% | 8.6 MiB/s | 6.3 MiB | 00m01s [ 89/182] build-reproducibility-srpm-ma 100% | 107.1 KiB/s | 12.9 KiB | 00m00s [ 90/182] linkdupes-0:0.7.2-2.fc44.aarc 100% | 2.6 MiB/s | 337.5 KiB | 00m00s [ 91/182] add-determinism-0:0.7.2-2.fc4 100% | 4.2 MiB/s | 825.0 KiB | 00m00s [ 92/182] dwz-0:0.16-2.fc43.aarch64 100% | 1.0 MiB/s | 132.2 KiB | 00m00s [ 93/182] efi-srpm-macros-0:6-5.fc44.no 100% | 187.7 KiB/s | 22.5 KiB | 00m00s [ 94/182] filesystem-srpm-macros-0:3.18 100% | 211.3 KiB/s | 26.4 KiB | 00m00s [ 95/182] fonts-srpm-macros-1:5.0.0-1.f 100% | 223.7 KiB/s | 27.3 KiB | 00m00s [ 96/182] forge-srpm-macros-0:0.4.0-3.f 100% | 149.9 KiB/s | 20.1 KiB | 00m00s [ 97/182] fpc-srpm-macros-0:1.3-15.fc43 100% | 56.4 KiB/s | 7.9 KiB | 00m00s [ 98/182] gap-srpm-macros-0:2-1.fc44.no 100% | 65.1 KiB/s | 9.1 KiB | 00m00s [ 99/182] ghc-srpm-macros-0:1.9.2-3.fc4 100% | 66.3 KiB/s | 8.7 KiB | 00m00s [100/182] gnat-srpm-macros-0:7-1.fc44.n 100% | 68.4 KiB/s | 8.6 KiB | 00m00s [101/182] go-srpm-macros-0:3.8.0-1.fc44 100% | 195.2 KiB/s | 28.3 KiB | 00m00s [102/182] java-srpm-macros-0:1-7.fc43.n 100% | 70.3 KiB/s | 7.9 KiB | 00m00s [103/182] kernel-srpm-macros-0:1.0-27.f 100% | 79.7 KiB/s | 8.9 KiB | 00m00s [104/182] lua-srpm-macros-0:1-16.fc43.n 100% | 81.1 KiB/s | 8.8 KiB | 00m00s [105/182] ocaml-srpm-macros-0:11-2.fc43 100% | 87.4 KiB/s | 9.3 KiB | 00m00s [106/182] openblas-srpm-macros-0:2-20.f 100% | 69.7 KiB/s | 7.6 KiB | 00m00s [107/182] package-notes-srpm-macros-0:0 100% | 82.4 KiB/s | 9.0 KiB | 00m00s [108/182] perl-srpm-macros-0:1-60.fc43. 100% | 72.1 KiB/s | 8.3 KiB | 00m00s [109/182] pyproject-srpm-macros-0:1.18. 100% | 111.9 KiB/s | 13.3 KiB | 00m00s [110/182] python-srpm-macros-0:3.14-9.f 100% | 200.1 KiB/s | 23.8 KiB | 00m00s [111/182] qt5-srpm-macros-0:5.15.18-1.f 100% | 71.7 KiB/s | 8.6 KiB | 00m00s [112/182] qt6-srpm-macros-0:6.10.1-1.fc 100% | 76.1 KiB/s | 9.4 KiB | 00m00s [113/182] rust-srpm-macros-0:28.4-1.fc4 100% | 92.3 KiB/s | 10.9 KiB | 00m00s [114/182] tree-sitter-srpm-macros-0:0.4 100% | 112.2 KiB/s | 13.4 KiB | 00m00s [115/182] zig-srpm-macros-0:1-7.fc44.no 100% | 71.6 KiB/s | 8.6 KiB | 00m00s [116/182] zip-0:3.0-44.fc43.aarch64 100% | 2.2 MiB/s | 262.6 KiB | 00m00s [117/182] R-srpm-macros-0:1.3.4-1.fc44. 100% | 84.7 KiB/s | 10.5 KiB | 00m00s [118/182] cmake-srpm-macros-0:3.31.10-3 100% | 83.5 KiB/s | 10.4 KiB | 00m00s [119/182] pkgconf-0:2.3.0-3.fc43.aarch6 100% | 352.4 KiB/s | 44.4 KiB | 00m00s [120/182] pkgconf-m4-0:2.3.0-3.fc43.noa 100% | 103.0 KiB/s | 13.9 KiB | 00m00s [121/182] libpkgconf-0:2.3.0-3.fc43.aar 100% | 280.6 KiB/s | 37.9 KiB | 00m00s [122/182] ed-0:1.22.4-1.fc44.aarch64 100% | 584.7 KiB/s | 83.6 KiB | 00m00s [123/182] libattr-0:2.5.2-6.fc43.aarch6 100% | 130.3 KiB/s | 17.7 KiB | 00m00s [124/182] libsepol-0:3.9-2.fc43.aarch64 100% | 2.3 MiB/s | 323.6 KiB | 00m00s [125/182] pcre2-0:10.47-1.fc44.aarch64 100% | 1.8 MiB/s | 246.2 KiB | 00m00s [126/182] pcre2-syntax-0:10.47-1.fc44.n 100% | 1.2 MiB/s | 164.7 KiB | 00m00s [127/182] lz4-libs-0:1.10.0-3.fc43.aarc 100% | 640.9 KiB/s | 79.5 KiB | 00m00s [128/182] openssl-libs-1:3.5.4-1.fc44.a 100% | 9.8 MiB/s | 2.4 MiB | 00m00s [129/182] libxml2-0:2.12.10-5.fc44.aarc 100% | 3.5 MiB/s | 678.7 KiB | 00m00s [130/182] tpm2-tss-0:4.1.3-8.fc43.aarch 100% | 2.9 MiB/s | 395.9 KiB | 00m00s [131/182] libassuan-0:2.5.7-4.fc43.aarc 100% | 527.9 KiB/s | 66.5 KiB | 00m00s [132/182] libgpg-error-0:1.58-1.fc44.aa 100% | 2.0 MiB/s | 243.3 KiB | 00m00s [133/182] libgcrypt-0:1.11.2-1.fc44.aar 100% | 2.1 MiB/s | 519.6 KiB | 00m00s [134/182] npth-0:1.8-3.fc43.aarch64 100% | 208.4 KiB/s | 25.0 KiB | 00m00s [135/182] libksba-0:1.6.7-4.fc43.aarch6 100% | 1.4 MiB/s | 157.5 KiB | 00m00s [136/182] openldap-0:2.6.10-6.fc44.aarc 100% | 2.0 MiB/s | 251.3 KiB | 00m00s [137/182] gmp-1:6.3.0-4.fc44.aarch64 100% | 2.3 MiB/s | 271.3 KiB | 00m00s [138/182] gnutls-0:3.8.11-6.fc44.aarch6 100% | 5.5 MiB/s | 1.3 MiB | 00m00s [139/182] mpfr-0:4.2.2-2.fc43.aarch64 100% | 2.5 MiB/s | 322.0 KiB | 00m00s [140/182] elfutils-default-yama-scope-0 100% | 101.4 KiB/s | 11.8 KiB | 00m00s [141/182] json-c-0:0.18-7.fc43.aarch64 100% | 366.9 KiB/s | 45.1 KiB | 00m00s [142/182] gnulib-l10n-0:20241231-1.fc44 100% | 1.2 MiB/s | 143.0 KiB | 00m00s [143/182] alternatives-0:1.33-3.fc44.aa 100% | 325.1 KiB/s | 40.3 KiB | 00m00s [144/182] jansson-0:2.14-3.fc43.aarch64 100% | 364.8 KiB/s | 46.7 KiB | 00m00s [145/182] libusb1-0:1.0.29-4.fc44.aarch 100% | 591.8 KiB/s | 77.5 KiB | 00m00s [146/182] ca-certificates-0:2025.2.80_v 100% | 7.2 MiB/s | 973.8 KiB | 00m00s [147/182] crypto-policies-0:20251128-1. 100% | 574.3 KiB/s | 74.7 KiB | 00m00s [148/182] cyrus-sasl-lib-0:2.1.28-33.fc 100% | 4.1 MiB/s | 773.3 KiB | 00m00s [149/182] libevent-0:2.1.12-16.fc43.aar 100% | 2.3 MiB/s | 253.4 KiB | 00m00s [150/182] libtool-ltdl-0:2.5.4-9.fc44.a 100% | 355.3 KiB/s | 35.5 KiB | 00m00s [151/182] libidn2-0:2.3.8-2.fc43.aarch6 100% | 1.7 MiB/s | 168.7 KiB | 00m00s [152/182] libtasn1-0:4.20.0-2.fc43.aarc 100% | 753.2 KiB/s | 73.8 KiB | 00m00s [153/182] libunistring-0:1.1-10.fc43.aa 100% | 3.6 MiB/s | 539.2 KiB | 00m00s [154/182] nettle-0:3.10.1-2.fc43.aarch6 100% | 3.9 MiB/s | 425.7 KiB | 00m00s [155/182] p11-kit-0:0.25.8-1.fc44.aarch 100% | 4.1 MiB/s | 478.5 KiB | 00m00s [156/182] p11-kit-trust-0:0.25.8-1.fc44 100% | 1.2 MiB/s | 138.6 KiB | 00m00s [157/182] gdbm-libs-1:1.23-10.fc43.aarc 100% | 500.1 KiB/s | 56.0 KiB | 00m00s [158/182] libffi-0:3.5.2-1.fc44.aarch64 100% | 364.6 KiB/s | 39.4 KiB | 00m00s [159/182] fedora-release-0:44-0.10.noar 100% | 135.0 KiB/s | 13.5 KiB | 00m00s [160/182] systemd-standalone-sysusers-0 100% | 1.4 MiB/s | 138.8 KiB | 00m00s [161/182] xxhash-libs-0:0.8.3-3.fc43.aa 100% | 374.6 KiB/s | 34.5 KiB | 00m00s [162/182] fedora-release-identity-basic 100% | 156.9 KiB/s | 14.3 KiB | 00m00s [163/182] libcurl-0:8.18.0-1.fc44.aarch 100% | 4.6 MiB/s | 423.5 KiB | 00m00s [164/182] libnghttp2-0:1.68.0-2.fc44.aa 100% | 760.8 KiB/s | 72.3 KiB | 00m00s [165/182] selinux-policy-0:42.21-1.fc44 100% | 713.4 KiB/s | 67.1 KiB | 00m00s [166/182] gdb-minimal-0:17.1-1.fc44.aar 100% | 10.6 MiB/s | 4.4 MiB | 00m00s [167/182] rpm-plugin-selinux-0:6.0.1-1. 100% | 220.0 KiB/s | 19.4 KiB | 00m00s [168/182] policycoreutils-0:3.9-5.fc44. 100% | 2.2 MiB/s | 191.9 KiB | 00m00s [169/182] libselinux-utils-0:3.9-6.fc44 100% | 1.4 MiB/s | 112.7 KiB | 00m00s [170/182] selinux-policy-targeted-0:42. 100% | 21.8 MiB/s | 6.6 MiB | 00m00s [171/182] krb5-libs-0:1.21.3-11.fc44.aa 100% | 9.3 MiB/s | 749.2 KiB | 00m00s [172/182] libbrotli-0:1.2.0-1.fc44.aarc 100% | 4.3 MiB/s | 350.2 KiB | 00m00s [173/182] libpsl-0:0.21.5-6.fc43.aarch6 100% | 794.2 KiB/s | 65.1 KiB | 00m00s [174/182] libssh-0:0.11.3-1.fc44.aarch6 100% | 2.9 MiB/s | 230.6 KiB | 00m00s [175/182] libssh-config-0:0.11.3-1.fc44 100% | 123.1 KiB/s | 9.1 KiB | 00m00s [176/182] ngtcp2-0:1.19.0-1.fc44.aarch6 100% | 1.9 MiB/s | 144.9 KiB | 00m00s [177/182] ngtcp2-crypto-ossl-0:1.19.0-1 100% | 373.7 KiB/s | 25.4 KiB | 00m00s [178/182] libnghttp3-0:1.14.0-1.fc44.aa 100% | 945.9 KiB/s | 69.1 KiB | 00m00s [179/182] keyutils-libs-0:1.6.3-6.fc43. 100% | 420.2 KiB/s | 31.5 KiB | 00m00s [180/182] libcom_err-0:1.47.3-3.fc44.aa 100% | 335.9 KiB/s | 26.9 KiB | 00m00s [181/182] libverto-0:0.3.2-11.fc43.aarc 100% | 229.5 KiB/s | 20.4 KiB | 00m00s [182/182] publicsuffix-list-dafsa-0:202 100% | 664.6 KiB/s | 59.2 KiB | 00m00s -------------------------------------------------------------------------------- [182/182] Total 100% | 6.2 MiB/s | 65.1 MiB | 00m10s Running transaction [ 1/184] Verify package files 100% | 784.0 B/s | 182.0 B | 00m00s [ 2/184] Prepare transaction 100% | 2.2 KiB/s | 182.0 B | 00m00s [ 3/184] Installing libgcc-0:16.0.1-0. 100% | 218.7 MiB/s | 223.9 KiB | 00m00s [ 4/184] Installing publicsuffix-list- 100% | 68.2 MiB/s | 69.8 KiB | 00m00s [ 5/184] Installing libssh-config-0:0. 100% | 0.0 B/s | 816.0 B | 00m00s [ 6/184] Installing fedora-release-ide 100% | 0.0 B/s | 920.0 B | 00m00s [ 7/184] Installing fedora-gpg-keys-0: 100% | 29.1 MiB/s | 179.0 KiB | 00m00s [ 8/184] Installing fedora-repos-rawhi 100% | 0.0 B/s | 2.4 KiB | 00m00s [ 9/184] Installing fedora-repos-0:44- 100% | 0.0 B/s | 5.7 KiB | 00m00s [ 10/184] Installing fedora-release-com 100% | 24.3 MiB/s | 24.9 KiB | 00m00s [ 11/184] Installing fedora-release-0:4 100% | 12.1 KiB/s | 124.0 B | 00m00s >>> Running sysusers scriptlet: setup-0:2.15.0-27.fc44.noarch >>> Finished sysusers scriptlet: setup-0:2.15.0-27.fc44.noarch >>> Scriptlet output: >>> Creating group 'adm' with GID 4. >>> Creating group 'audio' with GID 63. >>> Creating group 'cdrom' with GID 11. >>> Creating group 'clock' with GID 103. >>> Creating group 'dialout' with GID 18. >>> Creating group 'disk' with GID 6. >>> Creating group 'floppy' with GID 19. >>> Creating group 'ftp' with GID 50. >>> Creating group 'games' with GID 20. >>> Creating group 'input' with GID 104. >>> Creating group 'kmem' with GID 9. >>> Creating group 'kvm' with GID 36. >>> Creating group 'lock' with GID 54. >>> Creating group 'lp' with GID 7. >>> Creating group 'mail' with GID 12. >>> Creating group 'man' with GID 15. >>> Creating group 'mem' with GID 8. >>> Creating group 'nobody' with GID 65534. >>> Creating group 'render' with GID 105. >>> Creating group 'root' with GID 0. >>> Creating group 'sgx' with GID 106. >>> Creating group 'sys' with GID 3. >>> Creating group 'tape' with GID 33. >>> Creating group 'tty' with GID 5. >>> Creating group 'users' with GID 100. >>> Creating group 'utmp' with GID 22. >>> Creating group 'video' with GID 39. >>> Creating group 'wheel' with GID 10. >>> Creating user 'adm' (adm) with UID 3 and GID 4. >>> Creating group 'bin' with GID 1. >>> Creating user 'bin' (bin) with UID 1 and GID 1. >>> Creating group 'daemon' with GID 2. >>> Creating user 'daemon' (daemon) with UID 2 and GID 2. >>> Creating user 'ftp' (FTP User) with UID 14 and GID 50. >>> Creating user 'games' (games) with UID 12 and GID 100. >>> Creating user 'halt' (halt) with UID 7 and GID 0. >>> Creating user 'lp' (lp) with UID 4 and GID 7. >>> Creating user 'mail' (mail) with UID 8 and GID 12. >>> Creating user 'nobody' (Kernel Overflow User) with UID 65534 and GID 65534. >>> Creating user 'operator' (operator) with UID 11 and GID 0. >>> Creating user 'root' (Super User) with UID 0 and GID 0. >>> Creating user 'shutdown' (shutdown) with UID 6 and GID 0. >>> Creating user 'sync' (sync) with UID 5 and GID 0. >>> [ 12/184] Installing setup-0:2.15.0-27. 100% | 37.5 MiB/s | 730.6 KiB | 00m00s >>> [RPM] /etc/hosts created as /etc/hosts.rpmnew [ 13/184] Installing filesystem-0:3.18- 100% | 1.9 MiB/s | 212.8 KiB | 00m00s [ 14/184] Installing gnulib-l10n-0:2024 100% | 129.3 MiB/s | 661.9 KiB | 00m00s [ 15/184] Installing coreutils-common-0 100% | 287.9 MiB/s | 11.2 MiB | 00m00s [ 16/184] Installing pcre2-syntax-0:10. 100% | 277.7 MiB/s | 284.3 KiB | 00m00s [ 17/184] Installing pkgconf-m4-0:2.3.0 100% | 0.0 B/s | 14.8 KiB | 00m00s [ 18/184] Installing rust-srpm-macros-0 100% | 0.0 B/s | 6.4 KiB | 00m00s [ 19/184] Installing qt6-srpm-macros-0: 100% | 0.0 B/s | 740.0 B | 00m00s [ 20/184] Installing qt5-srpm-macros-0: 100% | 0.0 B/s | 776.0 B | 00m00s [ 21/184] Installing perl-srpm-macros-0 100% | 0.0 B/s | 1.1 KiB | 00m00s [ 22/184] Installing package-notes-srpm 100% | 0.0 B/s | 2.0 KiB | 00m00s [ 23/184] Installing openblas-srpm-macr 100% | 0.0 B/s | 392.0 B | 00m00s [ 24/184] Installing ocaml-srpm-macros- 100% | 0.0 B/s | 2.1 KiB | 00m00s [ 25/184] Installing kernel-srpm-macros 100% | 0.0 B/s | 2.3 KiB | 00m00s [ 26/184] Installing gnat-srpm-macros-0 100% | 0.0 B/s | 1.3 KiB | 00m00s [ 27/184] Installing ghc-srpm-macros-0: 100% | 0.0 B/s | 1.0 KiB | 00m00s [ 28/184] Installing gap-srpm-macros-0: 100% | 0.0 B/s | 2.7 KiB | 00m00s [ 29/184] Installing fpc-srpm-macros-0: 100% | 0.0 B/s | 420.0 B | 00m00s [ 30/184] Installing ansible-srpm-macro 100% | 35.4 MiB/s | 36.2 KiB | 00m00s [ 31/184] Installing ncurses-base-0:6.5 100% | 49.3 MiB/s | 353.5 KiB | 00m00s [ 32/184] Installing bash-0:5.3.9-1.fc4 100% | 205.7 MiB/s | 8.4 MiB | 00m00s [ 33/184] Installing glibc-common-0:2.4 100% | 57.6 MiB/s | 1.3 MiB | 00m00s [ 34/184] Installing glibc-gconv-extra- 100% | 380.1 MiB/s | 18.6 MiB | 00m00s [ 35/184] Installing glibc-0:2.42.9000- 100% | 141.8 MiB/s | 6.4 MiB | 00m00s [ 36/184] Installing ncurses-libs-0:6.5 100% | 249.5 MiB/s | 1.2 MiB | 00m00s [ 37/184] Installing glibc-minimal-lang 100% | 0.0 B/s | 124.0 B | 00m00s [ 38/184] Installing zlib-ng-compat-0:2 100% | 131.0 MiB/s | 134.1 KiB | 00m00s [ 39/184] Installing bzip2-libs-0:1.0.8 100% | 72.0 MiB/s | 73.8 KiB | 00m00s [ 40/184] Installing libgpg-error-0:1.5 100% | 48.6 MiB/s | 995.5 KiB | 00m00s [ 41/184] Installing libstdc++-0:16.0.1 100% | 315.9 MiB/s | 2.8 MiB | 00m00s [ 42/184] Installing libassuan-0:2.5.7- 100% | 212.6 MiB/s | 217.7 KiB | 00m00s [ 43/184] Installing libgcrypt-0:1.11.2 100% | 239.1 MiB/s | 1.2 MiB | 00m00s [ 44/184] Installing readline-0:8.3-3.f 100% | 184.1 MiB/s | 565.6 KiB | 00m00s [ 45/184] Installing libuuid-0:2.41.3-1 100% | 68.6 MiB/s | 70.3 KiB | 00m00s [ 46/184] Installing xz-libs-1:5.8.2-1. 100% | 197.7 MiB/s | 202.5 KiB | 00m00s [ 47/184] Installing gmp-1:6.3.0-4.fc44 100% | 214.9 MiB/s | 660.2 KiB | 00m00s [ 48/184] Installing popt-0:1.19-9.fc43 100% | 49.3 MiB/s | 151.4 KiB | 00m00s [ 49/184] Installing libzstd-0:1.5.7-3. 100% | 280.5 MiB/s | 861.7 KiB | 00m00s [ 50/184] Installing elfutils-libelf-0: 100% | 286.1 MiB/s | 1.1 MiB | 00m00s [ 51/184] Installing npth-0:1.8-3.fc43. 100% | 92.4 MiB/s | 94.6 KiB | 00m00s [ 52/184] Installing libblkid-0:2.41.3- 100% | 142.3 MiB/s | 291.4 KiB | 00m00s [ 53/184] Installing libxcrypt-0:4.5.2- 100% | 134.8 MiB/s | 276.1 KiB | 00m00s [ 54/184] Installing systemd-libs-0:259 100% | 273.6 MiB/s | 2.5 MiB | 00m00s [ 55/184] Installing sqlite-libs-0:3.51 100% | 250.2 MiB/s | 1.5 MiB | 00m00s [ 56/184] Installing libsepol-0:3.9-2.f 100% | 263.9 MiB/s | 810.8 KiB | 00m00s [ 57/184] Installing gnupg2-gpgconf-0:2 100% | 18.6 MiB/s | 323.8 KiB | 00m00s [ 58/184] Installing libattr-0:2.5.2-6. 100% | 67.8 MiB/s | 69.4 KiB | 00m00s [ 59/184] Installing libacl-0:2.3.2-4.f 100% | 67.2 MiB/s | 68.8 KiB | 00m00s [ 60/184] Installing pcre2-0:10.47-1.fc 100% | 233.0 MiB/s | 715.9 KiB | 00m00s [ 61/184] Installing libselinux-0:3.9-6 100% | 197.5 MiB/s | 202.2 KiB | 00m00s [ 62/184] Installing grep-0:3.12-2.fc43 100% | 47.2 MiB/s | 1.0 MiB | 00m00s [ 63/184] Installing sed-0:4.9-6.fc44.a 100% | 41.0 MiB/s | 881.4 KiB | 00m00s [ 64/184] Installing findutils-1:4.10.0 100% | 80.0 MiB/s | 1.9 MiB | 00m00s [ 65/184] Installing libtasn1-0:4.20.0- 100% | 108.5 MiB/s | 222.2 KiB | 00m00s [ 66/184] Installing libunistring-0:1.1 100% | 291.0 MiB/s | 1.7 MiB | 00m00s [ 67/184] Installing libidn2-0:2.3.8-2. 100% | 42.6 MiB/s | 566.7 KiB | 00m00s [ 68/184] Installing crypto-policies-0: 100% | 22.0 MiB/s | 157.7 KiB | 00m00s [ 69/184] Installing xz-1:5.8.2-1.fc44. 100% | 57.9 MiB/s | 1.4 MiB | 00m00s [ 70/184] Installing libmount-0:2.41.3- 100% | 205.6 MiB/s | 421.1 KiB | 00m00s [ 71/184] Installing gnupg2-verify-0:2. 100% | 21.0 MiB/s | 365.7 KiB | 00m00s [ 72/184] Installing dwz-0:0.16-2.fc43. 100% | 18.6 MiB/s | 324.0 KiB | 00m00s [ 73/184] Installing mpfr-0:4.2.2-2.fc4 100% | 184.9 MiB/s | 757.2 KiB | 00m00s [ 74/184] Installing gawk-0:5.3.2-2.fc4 100% | 99.3 MiB/s | 2.6 MiB | 00m00s [ 75/184] Installing libksba-0:1.6.7-4. 100% | 195.8 MiB/s | 401.0 KiB | 00m00s [ 76/184] Installing unzip-0:6.0-68.fc4 100% | 27.2 MiB/s | 473.8 KiB | 00m00s [ 77/184] Installing file-libs-0:5.46-8 100% | 516.6 MiB/s | 11.9 MiB | 00m00s [ 78/184] Installing file-0:5.46-8.fc44 100% | 8.1 MiB/s | 141.7 KiB | 00m00s [ 79/184] Installing diffutils-0:3.12-3 100% | 70.6 MiB/s | 1.6 MiB | 00m00s [ 80/184] Installing libsmartcols-0:2.4 100% | 110.0 MiB/s | 225.4 KiB | 00m00s [ 81/184] Installing libcap-ng-0:0.9-2. 100% | 158.7 MiB/s | 162.5 KiB | 00m00s [ 82/184] Installing audit-libs-0:4.1.2 100% | 239.1 MiB/s | 489.6 KiB | 00m00s [ 83/184] Installing libsemanage-0:3.9- 100% | 176.7 MiB/s | 361.9 KiB | 00m00s [ 84/184] Installing libeconf-0:0.7.9-2 100% | 80.7 MiB/s | 82.6 KiB | 00m00s [ 85/184] Installing pam-libs-0:1.7.1-4 100% | 219.7 MiB/s | 225.0 KiB | 00m00s [ 86/184] Installing libcap-0:2.77-1.fc 100% | 27.9 MiB/s | 514.0 KiB | 00m00s [ 87/184] Installing lua-libs-0:5.4.8-4 100% | 161.8 MiB/s | 331.4 KiB | 00m00s [ 88/184] Installing json-c-0:0.18-7.fc 100% | 136.7 MiB/s | 139.9 KiB | 00m00s [ 89/184] Installing alternatives-0:1.3 100% | 5.6 MiB/s | 91.8 KiB | 00m00s [ 90/184] Installing libffi-0:3.5.2-1.f 100% | 76.8 MiB/s | 157.3 KiB | 00m00s [ 91/184] Installing p11-kit-0:0.25.8-1 100% | 89.7 MiB/s | 2.5 MiB | 00m00s [ 92/184] Installing p11-kit-trust-0:0. 100% | 18.6 MiB/s | 532.0 KiB | 00m00s [ 93/184] Installing ngtcp2-0:1.19.0-1. 100% | 167.3 MiB/s | 342.6 KiB | 00m00s [ 94/184] Installing openssl-libs-1:3.5 100% | 285.4 MiB/s | 7.4 MiB | 00m00s [ 95/184] Installing coreutils-0:9.9-2. 100% | 163.1 MiB/s | 8.2 MiB | 00m00s [ 96/184] Installing ca-certificates-0: 100% | 1.4 MiB/s | 2.5 MiB | 00m02s [ 97/184] Installing gzip-0:1.14-1.fc44 100% | 21.6 MiB/s | 443.2 KiB | 00m00s [ 98/184] Installing libfsverity-0:1.6- 100% | 67.8 MiB/s | 69.4 KiB | 00m00s [ 99/184] Installing rpm-sequoia-0:1.10 100% | 288.3 MiB/s | 2.3 MiB | 00m00s [100/184] Installing libevent-0:2.1.12- 100% | 271.3 MiB/s | 1.1 MiB | 00m00s [101/184] Installing ngtcp2-crypto-ossl 100% | 66.7 MiB/s | 68.3 KiB | 00m00s [102/184] Installing util-linux-core-0: 100% | 94.7 MiB/s | 2.5 MiB | 00m00s [103/184] Installing zip-0:3.0-44.fc43. 100% | 39.4 MiB/s | 766.4 KiB | 00m00s [104/184] Installing gnupg2-keyboxd-0:2 100% | 25.4 MiB/s | 234.5 KiB | 00m00s [105/184] Installing libpsl-0:0.21.5-6. 100% | 65.2 MiB/s | 133.6 KiB | 00m00s [106/184] Installing tar-2:1.35-6.fc43. 100% | 100.1 MiB/s | 3.0 MiB | 00m00s [107/184] Installing linkdupes-0:0.7.2- 100% | 40.1 MiB/s | 780.8 KiB | 00m00s [108/184] Installing libselinux-utils-0 100% | 64.6 MiB/s | 1.4 MiB | 00m00s [109/184] Installing liblastlog2-0:2.41 100% | 15.2 MiB/s | 139.7 KiB | 00m00s [110/184] Installing libusb1-0:1.0.29-4 100% | 14.7 MiB/s | 180.6 KiB | 00m00s >>> Running sysusers scriptlet: tpm2-tss-0:4.1.3-8.fc43.aarch64 >>> Finished sysusers scriptlet: tpm2-tss-0:4.1.3-8.fc43.aarch64 >>> Scriptlet output: >>> Creating group 'tss' with GID 59. >>> Creating user 'tss' (Account used for TPM access) with UID 59 and GID 59. >>> [111/184] Installing tpm2-tss-0:4.1.3-8 100% | 215.9 MiB/s | 2.2 MiB | 00m00s [112/184] Installing gnupg2-gpg-agent-0 100% | 28.6 MiB/s | 850.7 KiB | 00m00s [113/184] Installing ima-evm-utils-libs 100% | 91.8 MiB/s | 94.0 KiB | 00m00s [114/184] Installing systemd-standalone 100% | 19.0 MiB/s | 330.2 KiB | 00m00s [115/184] Installing rpm-libs-0:6.0.1-1 100% | 243.4 MiB/s | 997.1 KiB | 00m00s [116/184] Installing libfdisk-0:2.41.3- 100% | 136.6 MiB/s | 419.8 KiB | 00m00s [117/184] Installing util-linux-0:2.41. 100% | 122.4 MiB/s | 6.9 MiB | 00m00s [118/184] Installing policycoreutils-0: 100% | 37.0 MiB/s | 1.3 MiB | 00m00s [119/184] Installing selinux-policy-0:4 100% | 1.1 MiB/s | 33.6 KiB | 00m00s [120/184] Installing selinux-policy-tar 100% | 122.6 MiB/s | 14.7 MiB | 00m00s [121/184] Installing zstd-0:1.5.7-3.fc4 100% | 25.6 MiB/s | 577.6 KiB | 00m00s [122/184] Installing nettle-0:3.10.1-2. 100% | 250.1 MiB/s | 768.4 KiB | 00m00s [123/184] Installing gnutls-0:3.8.11-6. 100% | 302.9 MiB/s | 3.6 MiB | 00m00s [124/184] Installing libxml2-0:2.12.10- 100% | 86.0 MiB/s | 1.9 MiB | 00m00s [125/184] Installing bzip2-0:1.0.8-21.f 100% | 9.5 MiB/s | 175.8 KiB | 00m00s [126/184] Installing add-determinism-0: 100% | 86.1 MiB/s | 2.0 MiB | 00m00s [127/184] Installing build-reproducibil 100% | 1.5 MiB/s | 1.5 KiB | 00m00s [128/184] Installing cpio-0:2.15-6.fc43 100% | 52.2 MiB/s | 1.1 MiB | 00m00s [129/184] Installing libgomp-0:16.0.1-0 100% | 288.8 MiB/s | 591.5 KiB | 00m00s [130/184] Installing libpkgconf-0:2.3.0 100% | 132.0 MiB/s | 135.1 KiB | 00m00s [131/184] Installing pkgconf-0:2.3.0-3. 100% | 7.0 MiB/s | 114.9 KiB | 00m00s [132/184] Installing pkgconf-pkg-config 100% | 110.8 KiB/s | 1.8 KiB | 00m00s [133/184] Installing ed-0:1.22.4-1.fc44 100% | 9.2 MiB/s | 159.5 KiB | 00m00s [134/184] Installing patch-0:2.8-3.fc44 100% | 15.2 MiB/s | 264.0 KiB | 00m00s [135/184] Installing lz4-libs-0:1.10.0- 100% | 193.9 MiB/s | 198.5 KiB | 00m00s [136/184] Installing libarchive-0:3.8.4 100% | 238.6 MiB/s | 977.2 KiB | 00m00s [137/184] Installing jansson-0:2.14-3.f 100% | 92.3 MiB/s | 94.5 KiB | 00m00s [138/184] Installing libtool-ltdl-0:2.5 100% | 92.7 MiB/s | 95.0 KiB | 00m00s [139/184] Installing gdbm-libs-1:1.23-1 100% | 230.1 MiB/s | 235.6 KiB | 00m00s [140/184] Installing cyrus-sasl-lib-0:2 100% | 100.7 MiB/s | 2.4 MiB | 00m00s [141/184] Installing openldap-0:2.6.10- 100% | 186.9 MiB/s | 765.4 KiB | 00m00s [142/184] Installing gnupg2-dirmngr-0:2 100% | 22.6 MiB/s | 648.7 KiB | 00m00s [143/184] Installing gnupg2-0:2.4.9-1.f 100% | 157.5 MiB/s | 6.5 MiB | 00m00s [144/184] Installing rpm-sign-libs-0:6. 100% | 67.0 MiB/s | 68.6 KiB | 00m00s [145/184] Installing gpgverify-0:2.2-3. 100% | 9.2 MiB/s | 9.4 KiB | 00m00s [146/184] Installing xxhash-libs-0:0.8. 100% | 85.3 MiB/s | 87.4 KiB | 00m00s [147/184] Installing libnghttp2-0:1.68. 100% | 194.4 MiB/s | 199.1 KiB | 00m00s [148/184] Installing libbrotli-0:1.2.0- 100% | 222.6 MiB/s | 911.8 KiB | 00m00s [149/184] Installing libnghttp3-0:1.14. 100% | 203.1 MiB/s | 208.0 KiB | 00m00s [150/184] Installing keyutils-libs-0:1. 100% | 97.4 MiB/s | 99.8 KiB | 00m00s [151/184] Installing libcom_err-0:1.47. 100% | 109.7 MiB/s | 112.3 KiB | 00m00s [152/184] Installing libverto-0:0.3.2-1 100% | 69.5 MiB/s | 71.2 KiB | 00m00s [153/184] Installing krb5-libs-0:1.21.3 100% | 253.1 MiB/s | 2.5 MiB | 00m00s [154/184] Installing libssh-0:0.11.3-1. 100% | 191.8 MiB/s | 589.1 KiB | 00m00s [155/184] Installing libcurl-0:8.18.0-1 100% | 239.7 MiB/s | 982.0 KiB | 00m00s [156/184] Installing curl-0:8.18.0-1.fc 100% | 15.7 MiB/s | 466.7 KiB | 00m00s [157/184] Installing rpm-0:6.0.1-1.fc44 100% | 57.0 MiB/s | 2.8 MiB | 00m00s [158/184] Installing efi-srpm-macros-0: 100% | 40.2 MiB/s | 41.2 KiB | 00m00s [159/184] Installing java-srpm-macros-0 100% | 0.0 B/s | 1.1 KiB | 00m00s [160/184] Installing lua-srpm-macros-0: 100% | 0.0 B/s | 1.9 KiB | 00m00s [161/184] Installing tree-sitter-srpm-m 100% | 9.1 MiB/s | 9.3 KiB | 00m00s [162/184] Installing zig-srpm-macros-0: 100% | 0.0 B/s | 1.9 KiB | 00m00s [163/184] Installing cmake-srpm-macros- 100% | 0.0 B/s | 804.0 B | 00m00s [164/184] Installing filesystem-srpm-ma 100% | 38.0 MiB/s | 38.9 KiB | 00m00s [165/184] Installing elfutils-default-y 100% | 291.9 KiB/s | 2.0 KiB | 00m00s [166/184] Installing elfutils-libs-0:0. 100% | 182.7 MiB/s | 748.4 KiB | 00m00s [167/184] Installing elfutils-debuginfo 100% | 7.5 MiB/s | 146.1 KiB | 00m00s [168/184] Installing elfutils-0:0.194-2 100% | 114.4 MiB/s | 3.2 MiB | 00m00s [169/184] Installing binutils-0:2.45.50 100% | 262.4 MiB/s | 30.7 MiB | 00m00s [170/184] Installing gdb-minimal-0:17.1 100% | 216.9 MiB/s | 13.7 MiB | 00m00s [171/184] Installing debugedit-0:5.2-4. 100% | 17.4 MiB/s | 321.6 KiB | 00m00s [172/184] Installing rpm-build-libs-0:6 100% | 129.4 MiB/s | 265.0 KiB | 00m00s [173/184] Installing redhat-rpm-config- 100% | 61.8 MiB/s | 189.9 KiB | 00m00s [174/184] Installing forge-srpm-macros- 100% | 39.3 MiB/s | 40.3 KiB | 00m00s [175/184] Installing fonts-srpm-macros- 100% | 55.7 MiB/s | 57.0 KiB | 00m00s [176/184] Installing go-srpm-macros-0:3 100% | 61.6 MiB/s | 63.0 KiB | 00m00s [177/184] Installing rpm-build-0:6.0.1- 100% | 29.7 MiB/s | 608.2 KiB | 00m00s [178/184] Installing pyproject-srpm-mac 100% | 2.4 MiB/s | 2.5 KiB | 00m00s [179/184] Installing python-srpm-macros 100% | 51.7 MiB/s | 52.9 KiB | 00m00s [180/184] Installing R-srpm-macros-0:1. 100% | 4.1 MiB/s | 4.2 KiB | 00m00s [181/184] Installing rpm-plugin-selinux 100% | 67.4 MiB/s | 69.0 KiB | 00m00s [182/184] Installing which-0:2.23-3.fc4 100% | 7.2 MiB/s | 125.6 KiB | 00m00s [183/184] Installing shadow-utils-2:4.1 100% | 107.0 MiB/s | 4.5 MiB | 00m00s [184/184] Installing info-0:7.2-7.fc44. 100% | 47.6 KiB/s | 422.0 KiB | 00m09s Warning: skipped OpenPGP checks for 182 packages from repository: http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch Complete! Finish: installing minimal buildroot with dnf5 Start: creating root cache Finish: creating root cache Finish: chroot init INFO: Installed packages: INFO: R-srpm-macros-1.3.4-1.fc44.noarch add-determinism-0.7.2-2.fc44.aarch64 alternatives-1.33-3.fc44.aarch64 ansible-srpm-macros-1-18.1.fc43.noarch audit-libs-4.1.2-2.fc44.aarch64 bash-5.3.9-1.fc44.aarch64 binutils-2.45.50-16.fc44.aarch64 build-reproducibility-srpm-macros-0.7.2-2.fc44.noarch bzip2-1.0.8-21.fc43.aarch64 bzip2-libs-1.0.8-21.fc43.aarch64 ca-certificates-2025.2.80_v9.0.304-2.fc44.noarch cmake-srpm-macros-3.31.10-3.fc44.noarch coreutils-9.9-2.fc44.aarch64 coreutils-common-9.9-2.fc44.aarch64 cpio-2.15-6.fc43.aarch64 crypto-policies-20251128-1.git19878fe.fc44.noarch curl-8.18.0-1.fc44.aarch64 cyrus-sasl-lib-2.1.28-33.fc44.aarch64 debugedit-5.2-4.fc44.aarch64 diffutils-3.12-3.fc43.aarch64 dwz-0.16-2.fc43.aarch64 ed-1.22.4-1.fc44.aarch64 efi-srpm-macros-6-5.fc44.noarch elfutils-0.194-2.fc44.aarch64 elfutils-debuginfod-client-0.194-2.fc44.aarch64 elfutils-default-yama-scope-0.194-2.fc44.noarch elfutils-libelf-0.194-2.fc44.aarch64 elfutils-libs-0.194-2.fc44.aarch64 fedora-gpg-keys-44-0.1.noarch fedora-release-44-0.10.noarch fedora-release-common-44-0.10.noarch fedora-release-identity-basic-44-0.10.noarch fedora-repos-44-0.1.noarch fedora-repos-rawhide-44-0.1.noarch file-5.46-8.fc44.aarch64 file-libs-5.46-8.fc44.aarch64 filesystem-3.18-50.fc43.aarch64 filesystem-srpm-macros-3.18-50.fc43.noarch findutils-4.10.0-6.fc43.aarch64 fonts-srpm-macros-5.0.0-1.fc44.noarch forge-srpm-macros-0.4.0-3.fc43.noarch fpc-srpm-macros-1.3-15.fc43.noarch gap-srpm-macros-2-1.fc44.noarch gawk-5.3.2-2.fc43.aarch64 gdb-minimal-17.1-1.fc44.aarch64 gdbm-libs-1.23-10.fc43.aarch64 ghc-srpm-macros-1.9.2-3.fc43.noarch glibc-2.42.9000-22.fc44.aarch64 glibc-common-2.42.9000-22.fc44.aarch64 glibc-gconv-extra-2.42.9000-22.fc44.aarch64 glibc-minimal-langpack-2.42.9000-22.fc44.aarch64 gmp-6.3.0-4.fc44.aarch64 gnat-srpm-macros-7-1.fc44.noarch gnulib-l10n-20241231-1.fc44.noarch gnupg2-2.4.9-1.fc44.aarch64 gnupg2-dirmngr-2.4.9-1.fc44.aarch64 gnupg2-gpg-agent-2.4.9-1.fc44.aarch64 gnupg2-gpgconf-2.4.9-1.fc44.aarch64 gnupg2-keyboxd-2.4.9-1.fc44.aarch64 gnupg2-verify-2.4.9-1.fc44.aarch64 gnutls-3.8.11-6.fc44.aarch64 go-srpm-macros-3.8.0-1.fc44.noarch gpgverify-2.2-3.fc43.noarch grep-3.12-2.fc43.aarch64 gzip-1.14-1.fc44.aarch64 ima-evm-utils-libs-1.6.2-7.fc44.aarch64 info-7.2-7.fc44.aarch64 jansson-2.14-3.fc43.aarch64 java-srpm-macros-1-7.fc43.noarch json-c-0.18-7.fc43.aarch64 kernel-srpm-macros-1.0-27.fc43.noarch keyutils-libs-1.6.3-6.fc43.aarch64 krb5-libs-1.21.3-11.fc44.aarch64 libacl-2.3.2-4.fc43.aarch64 libarchive-3.8.4-1.fc44.aarch64 libassuan-2.5.7-4.fc43.aarch64 libattr-2.5.2-6.fc43.aarch64 libblkid-2.41.3-11.fc44.aarch64 libbrotli-1.2.0-1.fc44.aarch64 libcap-2.77-1.fc44.aarch64 libcap-ng-0.9-2.fc44.aarch64 libcom_err-1.47.3-3.fc44.aarch64 libcurl-8.18.0-1.fc44.aarch64 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popt-1.19-9.fc43.aarch64 publicsuffix-list-dafsa-20250616-2.fc43.noarch pyproject-srpm-macros-1.18.6-1.fc44.noarch python-srpm-macros-3.14-9.fc44.noarch qt5-srpm-macros-5.15.18-1.fc44.noarch qt6-srpm-macros-6.10.1-1.fc44.noarch readline-8.3-3.fc44.aarch64 redhat-rpm-config-343-19.fc44.noarch rpm-6.0.1-1.fc44.aarch64 rpm-build-6.0.1-1.fc44.aarch64 rpm-build-libs-6.0.1-1.fc44.aarch64 rpm-libs-6.0.1-1.fc44.aarch64 rpm-plugin-selinux-6.0.1-1.fc44.aarch64 rpm-sequoia-1.10.0-1.fc44.aarch64 rpm-sign-libs-6.0.1-1.fc44.aarch64 rust-srpm-macros-28.4-1.fc44.noarch sed-4.9-6.fc44.aarch64 selinux-policy-42.21-1.fc44.noarch selinux-policy-targeted-42.21-1.fc44.noarch setup-2.15.0-27.fc44.noarch shadow-utils-4.18.0-7.fc44.aarch64 sqlite-libs-3.51.0-1.fc44.aarch64 systemd-libs-259-1.fc44.aarch64 systemd-standalone-sysusers-259-1.fc44.aarch64 tar-1.35-6.fc43.aarch64 tpm2-tss-4.1.3-8.fc43.aarch64 tree-sitter-srpm-macros-0.4.2-1.fc43.noarch unzip-6.0-68.fc44.aarch64 util-linux-2.41.3-11.fc44.aarch64 util-linux-core-2.41.3-11.fc44.aarch64 which-2.23-3.fc43.aarch64 xxhash-libs-0.8.3-3.fc43.aarch64 xz-5.8.2-1.fc44.aarch64 xz-libs-5.8.2-1.fc44.aarch64 zig-srpm-macros-1-7.fc44.noarch zip-3.0-44.fc43.aarch64 zlib-ng-compat-2.3.2-2.fc44.aarch64 zstd-1.5.7-3.fc44.aarch64 Start: buildsrpm Start: rpmbuild -bs Building target platforms: aarch64 Building for target aarch64 setting SOURCE_DATE_EPOCH=1768608000 Wrote: /builddir/build/SRPMS/python-pyscf-2.11.0-2.fc44.src.rpm Finish: rpmbuild -bs INFO: chroot_scan: 1 files copied to /var/lib/copr-rpmbuild/results/chroot_scan INFO: /var/lib/mock/fedora-43-aarch64-1768641411.012166/root/var/log/dnf5.log INFO: chroot_scan: creating tarball /var/lib/copr-rpmbuild/results/chroot_scan.tar.gz /bin/tar: Removing leading `/' from member names Finish: buildsrpm INFO: Done(/var/lib/copr-rpmbuild/workspace/workdir-k42prp22/python-pyscf/python-pyscf.spec) Config(child) 0 minutes 43 seconds INFO: Results and/or logs in: /var/lib/copr-rpmbuild/results INFO: Cleaning up build root ('cleanup_on_success=True') Start: clean chroot INFO: unmounting tmpfs. Finish: clean chroot INFO: Start(/var/lib/copr-rpmbuild/results/python-pyscf-2.11.0-2.fc44.src.rpm) Config(fedora-43-aarch64) Start(bootstrap): chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-43-aarch64-bootstrap-1768641411.012166/root. INFO: reusing tmpfs at /var/lib/mock/fedora-43-aarch64-bootstrap-1768641411.012166/root. INFO: calling preinit hooks INFO: enabled root cache INFO: enabled package manager cache Start(bootstrap): cleaning package manager metadata Finish(bootstrap): cleaning package manager metadata Finish(bootstrap): chroot init Start: chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-43-aarch64-1768641411.012166/root. INFO: calling preinit hooks INFO: enabled root cache Start: unpacking root cache Finish: unpacking root cache INFO: enabled package manager cache Start: cleaning package manager metadata Finish: cleaning package manager metadata INFO: enabled HW Info plugin INFO: Buildroot is handled by package management downloaded with a bootstrap image: rpm-6.0.1-1.fc43.aarch64 rpm-sequoia-1.10.0-1.fc43.aarch64 dnf5-5.2.17.0-2.fc43.aarch64 dnf5-plugins-5.2.17.0-2.fc43.aarch64 Finish: chroot init Start: build phase for python-pyscf-2.11.0-2.fc44.src.rpm Start: build setup for python-pyscf-2.11.0-2.fc44.src.rpm Building target platforms: aarch64 Building for target aarch64 setting SOURCE_DATE_EPOCH=1768608000 Wrote: /builddir/build/SRPMS/python-pyscf-2.11.0-2.fc44.src.rpm Updating and loading repositories: Additional repo http_kojipkgs_fedorapr 100% | 31.5 KiB/s | 3.9 KiB | 00m00s Copr repository 100% | 12.4 KiB/s | 1.5 KiB | 00m00s fedora 100% | 27.8 KiB/s | 14.4 KiB | 00m01s updates 100% | 31.6 KiB/s | 7.8 KiB | 00m00s Repositories loaded. 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aarch64 16.0.1-0.2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 40.0 MiB emacs-filesystem aarch64 1:30.2-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 0.0 B expat aarch64 2.7.3-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 361.0 KiB flexiblas aarch64 3.5.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 38.0 KiB flexiblas-netlib aarch64 3.5.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 14.4 MiB flexiblas-netlib64 aarch64 3.5.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 14.2 MiB flexiblas-openblas-openmp aarch64 3.5.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 67.3 KiB flexiblas-openblas-openmp64 aarch64 3.5.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 67.3 KiB gcc aarch64 16.0.1-0.2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 110.6 MiB gcc-plugin-annobin aarch64 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http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.7 MiB liblzf aarch64 3.6-33.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 153.5 KiB libmpc aarch64 1.3.1-8.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 152.7 KiB libstdc++-devel aarch64 16.0.1-0.2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 37.9 MiB libubsan aarch64 16.0.1-0.2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 475.8 KiB libuv aarch64 1:1.51.0-2.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 605.4 KiB libxc aarch64 7.0.0-8.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 103.1 MiB libxcrypt-devel aarch64 4.5.2-2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 31.0 KiB make aarch64 1:4.4.1-11.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.8 MiB mpdecimal aarch64 4.0.1-2.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 281.2 KiB openblas aarch64 0.3.29-2.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 111.7 KiB openblas-openmp aarch64 0.3.29-2.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 20.4 MiB openblas-openmp64 aarch64 0.3.29-2.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 20.2 MiB pyproject-rpm-macros noarch 1.18.6-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 115.6 KiB python-pip-wheel noarch 25.3-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.2 MiB python-rpm-macros noarch 3.14-9.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 27.6 KiB python3 aarch64 3.14.2-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 84.9 KiB python3-cached_property noarch 2.0.1-6.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 35.2 KiB python3-charset-normalizer noarch 3.4.4-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 356.2 KiB python3-coverage aarch64 7.13.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 2.1 MiB python3-coverage+toml aarch64 7.13.1-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 0.0 B python3-idna noarch 3.11-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 738.4 KiB python3-iniconfig noarch 2.3.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 49.3 KiB python3-libs aarch64 3.14.2-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 45.1 MiB python3-numpy-f2py aarch64 1:2.4.0-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 2.1 MiB python3-packaging noarch 25.0-7.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 607.4 KiB python3-platformdirs noarch 4.4.0-2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 182.4 KiB python3-pluggy noarch 1.6.0-4.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 211.0 KiB python3-pooch noarch 1.8.2-9.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 635.2 KiB python3-pygments noarch 2.19.1-8.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 11.3 MiB python3-requests noarch 2.32.5-2.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 476.9 KiB python3-rpm-generators noarch 14-13.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 81.7 KiB python3-rpm-macros noarch 3.14-9.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 6.5 KiB python3-six noarch 1.17.0-7.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 118.0 KiB python3-urllib3 noarch 2.6.3-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.1 MiB rhash aarch64 1.4.5-3.fc43 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 394.8 KiB tzdata noarch 2025c-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.2 MiB vim-filesystem noarch 2:9.1.2068-1.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 40.0 B xcfun aarch64 2.1.1-20.fc44 http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch 1.7 MiB Transaction Summary: Installing: 75 packages Total size of inbound packages is 230 MiB. Need to download 230 MiB. After this operation, 711 MiB extra will be used (install 711 MiB, remove 0 B). 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00m00s Warning: skipped OpenPGP checks for 75 packages from repository: http_kojipkgs_fedoraproject_org_repos_rawhide_latest_basearch Complete! Building target platforms: aarch64 Building for target aarch64 setting SOURCE_DATE_EPOCH=1768608000 Wrote: /builddir/build/SRPMS/python-pyscf-2.11.0-2.fc44.src.rpm Updating and loading repositories: Additional repo http_kojipkgs_fedorapr 100% | 46.6 KiB/s | 3.9 KiB | 00m00s Copr repository 100% | 18.4 KiB/s | 1.5 KiB | 00m00s fedora 100% | 37.1 KiB/s | 14.4 KiB | 00m00s updates 100% | 52.2 KiB/s | 7.8 KiB | 00m00s Repositories loaded. Package "cmake-3.31.10-3.fc44.aarch64" is already installed. Package "flexiblas-devel-3.5.0-1.fc44.aarch64" is already installed. Package "gcc-c++-16.0.1-0.2.fc44.aarch64" is already installed. Package "libcint-devel-6.1.3-1.fc44.aarch64" is already installed. Package "libxc-devel-7.0.0-8.fc44.aarch64" is already installed. Package "python3-devel-3.14.2-1.fc44.aarch64" is already installed. Package "python3-h5py-3.15.1-2.fc44.aarch64" is already installed. Package "python3-numpy-1:2.4.0-1.fc44.aarch64" is already installed. Package "python3-pytest-8.4.2-1.fc44.noarch" is already installed. Package "python3-pytest-cov-7.0.0-1.fc44.noarch" is already installed. Package "python3-scipy-1.16.2-2.fc44.aarch64" is already installed. Package "python3-setuptools-80.9.0-2.fc44.noarch" is already installed. Package "xcfun-devel-2.1.1-20.fc44.aarch64" is already installed. Nothing to do. Finish: build setup for python-pyscf-2.11.0-2.fc44.src.rpm Start: rpmbuild python-pyscf-2.11.0-2.fc44.src.rpm Building target platforms: aarch64 Building for target aarch64 setting SOURCE_DATE_EPOCH=1768608000 Executing(%mkbuilddir): /bin/sh -e /var/tmp/rpm-tmp.j1oGxT Executing(%prep): /bin/sh -e /var/tmp/rpm-tmp.0Wb47e + umask 022 + cd /builddir/build/BUILD/python-pyscf-2.11.0-build + cd /builddir/build/BUILD/python-pyscf-2.11.0-build + rm -rf pyscf-2.11.0 + /usr/lib/rpm/rpmuncompress -x /builddir/build/SOURCES/pyscf-2.11.0.tar.gz + STATUS=0 + '[' 0 -ne 0 ']' + cd pyscf-2.11.0 + /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w . + echo 'Patch #1 (pyscf-2.6.0-rpath.patch):' + /usr/bin/patch --no-backup-if-mismatch -f -p1 -b --suffix .rpath --fuzz=0 Patch #1 (pyscf-2.6.0-rpath.patch): patching file pyscf/lib/CMakeLists.txt Hunk #1 succeeded at 126 (offset 3 lines). + echo 'Patch #2 (2273.patch):' + /usr/bin/patch --no-backup-if-mismatch -f -p1 -b --suffix .2273 --fuzz=0 Patch #2 (2273.patch): patching file pyscf/dft/xc_deriv.py + echo 'Patch #3 (pyscf-2.11.0-segfault.patch):' Patch #3 (pyscf-2.11.0-segfault.patch): + /usr/bin/patch --no-backup-if-mismatch -f -p1 -b --suffix .segfault --fuzz=0 patching file pyscf/pbc/scf/rsjk.py + find pyscf -name '*.py' -exec sed -i '/#!\/usr\/bin\/env /d' '{}' ';' + find pyscf -name '*.py' -exec sed -i '/#!\/usr\/bin\/python/d' '{}' ';' + RPM_EC=0 ++ jobs -p + exit 0 Executing(%build): /bin/sh -e /var/tmp/rpm-tmp.iVOwqU + umask 022 + cd /builddir/build/BUILD/python-pyscf-2.11.0-build + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd pyscf-2.11.0 + cd pyscf/lib + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + /usr/bin/cmake -S . -B redhat-linux-build -DCMAKE_C_FLAGS_RELEASE:STRING=-DNDEBUG -DCMAKE_CXX_FLAGS_RELEASE:STRING=-DNDEBUG -DCMAKE_Fortran_FLAGS_RELEASE:STRING=-DNDEBUG -DCMAKE_VERBOSE_MAKEFILE:BOOL=ON -DCMAKE_INSTALL_DO_STRIP:BOOL=OFF -DCMAKE_INSTALL_PREFIX:PATH=/usr -DCMAKE_INSTALL_FULL_SBINDIR:PATH=/usr/bin -DCMAKE_INSTALL_SBINDIR:PATH=bin -DINCLUDE_INSTALL_DIR:PATH=/usr/include -DLIB_INSTALL_DIR:PATH=/usr/lib64 -DSYSCONF_INSTALL_DIR:PATH=/etc -DSHARE_INSTALL_PREFIX:PATH=/usr/share -DLIB_SUFFIX=64 -DBUILD_SHARED_LIBS:BOOL=ON -DENABLE_LIBXC=ON -DBUILD_LIBXC=OFF -DENABLE_XCFUN=ON -DBUILD_XCFUN=OFF -DBUILD_LIBCINT=OFF -DBLA_VENDOR=FlexiBLAS -DCMAKE_SKIP_BUILD_RPATH=1 -- The C compiler identification is GNU 16.0.1 -- The CXX compiler identification is GNU 16.0.1 -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: /usr/bin/gcc - skipped -- Detecting C compile features -- Detecting C compile features - done -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: /usr/bin/g++ - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done -- Performing Test COMPILER_SUPPORTS_SSE3 -- Performing Test COMPILER_SUPPORTS_SSE3 - Failed -- Looking for sgemm_ -- Looking for sgemm_ - found -- Found BLAS: /usr/lib64/libflexiblas.so -- Looking for ffsll -- Looking for ffsll - found -- BLAS libraries: /usr/lib64/libflexiblas.so -- Found OpenMP_C: -fopenmp (found version "5.2") -- Found OpenMP_CXX: -fopenmp (found version "5.2") -- Found OpenMP: TRUE (found version "5.2") -- Configuring done (2.0s) -- Generating done (0.0s) CMake Warning: Manually-specified variables were not used by the project: CMAKE_CXX_FLAGS_RELEASE CMAKE_C_FLAGS_RELEASE CMAKE_Fortran_FLAGS_RELEASE CMAKE_INSTALL_DO_STRIP CMAKE_INSTALL_FULL_SBINDIR CMAKE_INSTALL_SBINDIR INCLUDE_INSTALL_DIR LIB_INSTALL_DIR LIB_SUFFIX SHARE_INSTALL_PREFIX SYSCONF_INSTALL_DIR -- Build files have been written to: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build + /usr/bin/cmake --build redhat-linux-build -j4 --verbose Change Dir: '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' Run Build Command(s): /usr/bin/cmake -E env VERBOSE=1 /usr/bin/gmake -f Makefile -j4 /usr/bin/cmake -S/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -B/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build --check-build-system CMakeFiles/Makefile.cmake 0 /usr/bin/cmake -E cmake_progress_start /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/CMakeFiles /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build//CMakeFiles/progress.marks /usr/bin/gmake -f CMakeFiles/Makefile2 all gmake[1]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f np_helper/CMakeFiles/np_helper.dir/build.make np_helper/CMakeFiles/np_helper.dir/depend /usr/bin/gmake -f dft/CMakeFiles/xc_itrf.dir/build.make dft/CMakeFiles/xc_itrf.dir/depend /usr/bin/gmake -f dft/CMakeFiles/xcfun_itrf.dir/build.make dft/CMakeFiles/xcfun_itrf.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper/CMakeFiles/np_helper.dir/DependInfo.cmake "--color=" gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft/CMakeFiles/xc_itrf.dir/DependInfo.cmake "--color=" gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft/CMakeFiles/xcfun_itrf.dir/DependInfo.cmake "--color=" gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f dft/CMakeFiles/xc_itrf.dir/build.make dft/CMakeFiles/xc_itrf.dir/build /usr/bin/gmake -f np_helper/CMakeFiles/np_helper.dir/build.make np_helper/CMakeFiles/np_helper.dir/build /usr/bin/gmake -f dft/CMakeFiles/xcfun_itrf.dir/build.make dft/CMakeFiles/xcfun_itrf.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 1%] Building C object dft/CMakeFiles/xc_itrf.dir/libxc_itrf.c.o [ 1%] Building C object np_helper/CMakeFiles/np_helper.dir/transpose.c.o [ 2%] Building C object dft/CMakeFiles/xcfun_itrf.dir/xcfun_itrf.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Dxcfun_itrf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/xcfun_itrf.dir/xcfun_itrf.c.o -MF CMakeFiles/xcfun_itrf.dir/xcfun_itrf.c.o.d -o CMakeFiles/xcfun_itrf.dir/xcfun_itrf.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/xcfun_itrf.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/transpose.c.o -MF CMakeFiles/np_helper.dir/transpose.c.o.d -o CMakeFiles/np_helper.dir/transpose.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/transpose.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Dxc_itrf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/xc_itrf.dir/libxc_itrf.c.o -MF CMakeFiles/xc_itrf.dir/libxc_itrf.c.o.d -o CMakeFiles/xc_itrf.dir/libxc_itrf.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/libxc_itrf.c [ 3%] Building C object np_helper/CMakeFiles/np_helper.dir/pack_tril.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/pack_tril.c.o -MF CMakeFiles/np_helper.dir/pack_tril.c.o.d -o CMakeFiles/np_helper.dir/pack_tril.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/pack_tril.c [ 4%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libxcfun_itrf.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/cmake -E cmake_link_script CMakeFiles/xcfun_itrf.dir/link.txt --verbose=1 [ 5%] Building C object np_helper/CMakeFiles/np_helper.dir/npdot.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/npdot.c.o -MF CMakeFiles/np_helper.dir/npdot.c.o.d -o CMakeFiles/np_helper.dir/npdot.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/npdot.c [ 6%] Building C object np_helper/CMakeFiles/np_helper.dir/condense.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/condense.c.o -MF CMakeFiles/np_helper.dir/condense.c.o.d -o CMakeFiles/np_helper.dir/condense.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/condense.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/xcfun_itrf.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libxcfun_itrf.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libxcfun_itrf.so CMakeFiles/xcfun_itrf.dir/xcfun_itrf.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 -lxcfun /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 6%] Built target xcfun_itrf [ 7%] Building C object np_helper/CMakeFiles/np_helper.dir/omp_reduce.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/omp_reduce.c.o -MF CMakeFiles/np_helper.dir/omp_reduce.c.o.d -o CMakeFiles/np_helper.dir/omp_reduce.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/omp_reduce.c [ 8%] Building C object np_helper/CMakeFiles/np_helper.dir/np_helper.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer 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-I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/imatcopy.c.o -MF CMakeFiles/np_helper.dir/imatcopy.c.o.d -o CMakeFiles/np_helper.dir/imatcopy.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/imatcopy.c [ 11%] Building C object np_helper/CMakeFiles/np_helper.dir/np_broadcast.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/gcc -Dnp_helper_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT np_helper/CMakeFiles/np_helper.dir/np_broadcast.c.o -MF CMakeFiles/np_helper.dir/np_broadcast.c.o.d -o CMakeFiles/np_helper.dir/np_broadcast.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/np_broadcast.c [ 12%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/np_helper && /usr/bin/cmake -E cmake_link_script CMakeFiles/np_helper.dir/link.txt --verbose=1 /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/xc_itrf.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libxc_itrf.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libxc_itrf.so CMakeFiles/xc_itrf.dir/libxc_itrf.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 -lxc /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 12%] Built target xc_itrf /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/np_helper.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libnp_helper.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so CMakeFiles/np_helper.dir/transpose.c.o CMakeFiles/np_helper.dir/pack_tril.c.o CMakeFiles/np_helper.dir/npdot.c.o CMakeFiles/np_helper.dir/condense.c.o CMakeFiles/np_helper.dir/omp_reduce.c.o CMakeFiles/np_helper.dir/np_helper.c.o CMakeFiles/np_helper.dir/imatcopy.c.o CMakeFiles/np_helper.dir/np_broadcast.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 12%] Built target np_helper /usr/bin/gmake -f gto/CMakeFiles/cgto.dir/build.make gto/CMakeFiles/cgto.dir/depend /usr/bin/gmake -f mcscf/CMakeFiles/fci.dir/build.make mcscf/CMakeFiles/fci.dir/depend /usr/bin/gmake -f mp/CMakeFiles/mp.dir/build.make mp/CMakeFiles/mp.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto/CMakeFiles/cgto.dir/DependInfo.cmake "--color=" gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf/CMakeFiles/fci.dir/DependInfo.cmake "--color=" gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mp /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mp/CMakeFiles/mp.dir/DependInfo.cmake "--color=" gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f mp/CMakeFiles/mp.dir/build.make mp/CMakeFiles/mp.dir/build /usr/bin/gmake -f gto/CMakeFiles/cgto.dir/build.make gto/CMakeFiles/cgto.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f mcscf/CMakeFiles/fci.dir/build.make mcscf/CMakeFiles/fci.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 13%] Building C object mp/CMakeFiles/mp.dir/mp2.c.o [ 14%] Building C object mcscf/CMakeFiles/fci.dir/fci_contract.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mp && /usr/bin/gcc -Dmp_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mp -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mp/CMakeFiles/mp.dir/mp2.c.o -MF CMakeFiles/mp.dir/mp2.c.o.d -o CMakeFiles/mp.dir/mp2.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dfci_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/fci.dir/fci_contract.c.o -MF CMakeFiles/fci.dir/fci_contract.c.o.d -o CMakeFiles/fci.dir/fci_contract.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/fci_contract.c [ 15%] Building C object gto/CMakeFiles/cgto.dir/fill_nr_3c.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/fill_nr_3c.c.o -MF CMakeFiles/cgto.dir/fill_nr_3c.c.o.d -o CMakeFiles/cgto.dir/fill_nr_3c.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/fill_nr_3c.c [ 16%] Building C object gto/CMakeFiles/cgto.dir/fill_int2c.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/fill_int2c.c.o -MF CMakeFiles/cgto.dir/fill_int2c.c.o.d -o CMakeFiles/cgto.dir/fill_int2c.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/fill_int2c.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c: In function ‘MP2_contract_d’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:163:28: warning: passing argument 1 of ‘NPdcopy’ discards ‘const’ qualifier from pointer target type [-Wdiscarded-qualifiers] 163 | NPdcopy(parr_t2[ii*nocc+jj], tab, nvv); | ~~~~~~~^~~~~~~~~~~~ In file included from /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:23: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/np_helper.h:70:22: note: expected ‘double *’ but argument is of type ‘const double *’ 70 | void NPdcopy(double *out, const double *in, const size_t n); | ~~~~~~~~^~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:165:54: warning: passing argument 4 of ‘NPdtranspose’ discards ‘const’ qualifier from pointer target type [-Wdiscarded-qualifiers] 165 | NPdtranspose(nvir, nvir, tab, parr_t2[jj*nocc+ii]); | ~~~~~~~^~~~~~~~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/np_helper.h:45:52: note: expected ‘double *’ but argument is of type ‘const double *’ 45 | void NPdtranspose(int n, int m, double *a, double *at); | ~~~~~~~~^~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c: In function ‘MP2_OS_contract_d’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:259:28: warning: passing argument 1 of ‘NPdcopy’ discards ‘const’ qualifier from pointer target type [-Wdiscarded-qualifiers] 259 | NPdcopy(parr_t2[ii*noccb+jj], tab, nvv); | ~~~~~~~^~~~~~~~~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/np_helper/np_helper.h:70:22: note: expected ‘double *’ but argument is of type ‘const double *’ 70 | void NPdcopy(double *out, const double *in, const size_t n); | ~~~~~~~~^~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c: In function ‘trisolve_parallel_grp’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:514:74: warning: passing argument 10 of ‘dtrsm_’ discards ‘const’ qualifier from pointer target type [-Wdiscarded-qualifiers] 514 | dtrsm_(&SIDE, &UPLO, &TRANS, &DIAG, &n, &di, &D1, low, &n, parr_b[i0], &n); | ~~~~~~^~~~ In file included from /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:24: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/fblas.h:53:48: note: expected ‘double *’ but argument is of type ‘const double *’ 53 | double *a, const int *lda, double *b, const int *ldb); | ~~~~~~~~^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:506:14: warning: unused variable ‘bi’ [-Wunused-variable] 506 | double * bi; | ^~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:505:9: warning: unused variable ‘info’ [-Wunused-variable] 505 | int info; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mp/mp2.c:504:9: warning: unused variable ‘i’ [-Wunused-variable] 504 | int i; | ^ [ 17%] Building C object mcscf/CMakeFiles/fci.dir/fci_contract_nosym.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dfci_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/fci.dir/fci_contract_nosym.c.o -MF CMakeFiles/fci.dir/fci_contract_nosym.c.o.d -o CMakeFiles/fci.dir/fci_contract_nosym.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/fci_contract_nosym.c [ 18%] Building C object gto/CMakeFiles/cgto.dir/fill_r_3c.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/fill_r_3c.c.o -MF CMakeFiles/cgto.dir/fill_r_3c.c.o.d -o CMakeFiles/cgto.dir/fill_r_3c.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/fill_r_3c.c [ 19%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libmp.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mp && /usr/bin/cmake -E cmake_link_script CMakeFiles/mp.dir/link.txt --verbose=1 [ 20%] Building C object gto/CMakeFiles/cgto.dir/fill_int2e.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/fill_int2e.c.o -MF CMakeFiles/cgto.dir/fill_int2e.c.o.d -o CMakeFiles/cgto.dir/fill_int2e.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/fill_int2e.c [ 21%] Building C object mcscf/CMakeFiles/fci.dir/fci_rdm.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dfci_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/fci.dir/fci_rdm.c.o -MF CMakeFiles/fci.dir/fci_rdm.c.o.d -o CMakeFiles/fci.dir/fci_rdm.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/fci_rdm.c [ 22%] Building C object gto/CMakeFiles/cgto.dir/fill_r_4c.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/fill_r_4c.c.o -MF CMakeFiles/cgto.dir/fill_r_4c.c.o.d -o CMakeFiles/cgto.dir/fill_r_4c.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/fill_r_4c.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/mp.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libmp.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libmp.so CMakeFiles/mp.dir/mp2.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 22%] Built target mp [ 23%] Building C object mcscf/CMakeFiles/fci.dir/fci_string.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dfci_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/fci.dir/fci_string.c.o -MF CMakeFiles/fci.dir/fci_string.c.o.d -o CMakeFiles/fci.dir/fci_string.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/fci_string.c [ 24%] Building C object mcscf/CMakeFiles/fci.dir/fci_4pdm.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dfci_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/fci.dir/fci_4pdm.c.o -MF CMakeFiles/fci.dir/fci_4pdm.c.o.d -o CMakeFiles/fci.dir/fci_4pdm.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/fci_4pdm.c [ 25%] Building C object gto/CMakeFiles/cgto.dir/ft_ao.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/ft_ao.c.o -MF CMakeFiles/cgto.dir/ft_ao.c.o.d -o CMakeFiles/cgto.dir/ft_ao.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/ft_ao.c [ 26%] Building C object gto/CMakeFiles/cgto.dir/ft_ao_deriv.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/ft_ao_deriv.c.o -MF CMakeFiles/cgto.dir/ft_ao_deriv.c.o.d -o CMakeFiles/cgto.dir/ft_ao_deriv.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/ft_ao_deriv.c [ 27%] Building C object mcscf/CMakeFiles/fci.dir/select_ci.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dfci_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/fci.dir/select_ci.c.o -MF CMakeFiles/fci.dir/select_ci.c.o.d -o CMakeFiles/fci.dir/select_ci.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/select_ci.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/select_ci.c: In function ‘SCIcontract_2e_aaaa’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/select_ci.c:425:9: warning: ‘master’ construct deprecated since OpenMP 5.1, use ‘masked’ [-Wdeprecated-openmp] 425 | #pragma omp master | ^~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/select_ci.c: In function ‘SCIcontract_2e_aaaa_symm’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/select_ci.c:652:9: warning: ‘master’ construct deprecated since OpenMP 5.1, use ‘masked’ [-Wdeprecated-openmp] 652 | #pragma omp master | ^~~ [ 28%] Building C object gto/CMakeFiles/cgto.dir/fill_grids_int2c.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/fill_grids_int2c.c.o -MF CMakeFiles/cgto.dir/fill_grids_int2c.c.o.d -o CMakeFiles/cgto.dir/fill_grids_int2c.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/fill_grids_int2c.c [ 29%] Building C object gto/CMakeFiles/cgto.dir/grid_ao_drv.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/grid_ao_drv.c.o -MF CMakeFiles/cgto.dir/grid_ao_drv.c.o.d -o CMakeFiles/cgto.dir/grid_ao_drv.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/grid_ao_drv.c [ 30%] Building C object gto/CMakeFiles/cgto.dir/deriv1.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/deriv1.c.o -MF CMakeFiles/cgto.dir/deriv1.c.o.d -o CMakeFiles/cgto.dir/deriv1.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/deriv1.c [ 31%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libfci.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/cmake -E cmake_link_script CMakeFiles/fci.dir/link.txt --verbose=1 [ 32%] Building C object gto/CMakeFiles/cgto.dir/deriv2.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/deriv2.c.o -MF CMakeFiles/cgto.dir/deriv2.c.o.d -o CMakeFiles/cgto.dir/deriv2.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/deriv2.c [ 33%] Building C object gto/CMakeFiles/cgto.dir/nr_ecp.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib 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/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/nr_ecp_deriv.c.o -MF CMakeFiles/cgto.dir/nr_ecp_deriv.c.o.d -o CMakeFiles/cgto.dir/nr_ecp_deriv.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/nr_ecp_deriv.c [ 35%] Building C object gto/CMakeFiles/cgto.dir/autocode/auto_eval1.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/gcc -Dcgto_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT gto/CMakeFiles/cgto.dir/autocode/auto_eval1.c.o -MF CMakeFiles/cgto.dir/autocode/auto_eval1.c.o.d -o CMakeFiles/cgto.dir/autocode/auto_eval1.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/autocode/auto_eval1.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/fci.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libfci.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libfci.so CMakeFiles/fci.dir/fci_contract.c.o CMakeFiles/fci.dir/fci_contract_nosym.c.o CMakeFiles/fci.dir/fci_rdm.c.o CMakeFiles/fci.dir/fci_string.c.o CMakeFiles/fci.dir/fci_4pdm.c.o CMakeFiles/fci.dir/select_ci.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 35%] Built target fci [ 36%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/gto && /usr/bin/cmake -E cmake_link_script CMakeFiles/cgto.dir/link.txt --verbose=1 /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/cgto.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libcgto.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so CMakeFiles/cgto.dir/fill_int2c.c.o CMakeFiles/cgto.dir/fill_nr_3c.c.o CMakeFiles/cgto.dir/fill_r_3c.c.o CMakeFiles/cgto.dir/fill_int2e.c.o CMakeFiles/cgto.dir/fill_r_4c.c.o CMakeFiles/cgto.dir/ft_ao.c.o CMakeFiles/cgto.dir/ft_ao_deriv.c.o CMakeFiles/cgto.dir/fill_grids_int2c.c.o CMakeFiles/cgto.dir/grid_ao_drv.c.o CMakeFiles/cgto.dir/deriv1.c.o CMakeFiles/cgto.dir/deriv2.c.o CMakeFiles/cgto.dir/nr_ecp.c.o CMakeFiles/cgto.dir/nr_ecp_deriv.c.o CMakeFiles/cgto.dir/autocode/auto_eval1.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 36%] Built target cgto /usr/bin/gmake -f vhf/CMakeFiles/cvhf.dir/build.make vhf/CMakeFiles/cvhf.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf/CMakeFiles/cvhf.dir/DependInfo.cmake "--color=" gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f vhf/CMakeFiles/cvhf.dir/build.make vhf/CMakeFiles/cvhf.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 40%] Building C object vhf/CMakeFiles/cvhf.dir/nr_direct.c.o [ 40%] Building C object vhf/CMakeFiles/cvhf.dir/nr_incore.c.o [ 40%] Building C object vhf/CMakeFiles/cvhf.dir/optimizer.c.o [ 40%] Building C object vhf/CMakeFiles/cvhf.dir/fill_nr_s8.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/nr_incore.c.o -MF CMakeFiles/cvhf.dir/nr_incore.c.o.d -o CMakeFiles/cvhf.dir/nr_incore.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_incore.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/fill_nr_s8.c.o -MF CMakeFiles/cvhf.dir/fill_nr_s8.c.o.d -o CMakeFiles/cvhf.dir/fill_nr_s8.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/fill_nr_s8.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/nr_direct.c.o -MF CMakeFiles/cvhf.dir/nr_direct.c.o.d -o CMakeFiles/cvhf.dir/nr_direct.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/optimizer.c.o -MF CMakeFiles/cvhf.dir/optimizer.c.o.d -o CMakeFiles/cvhf.dir/optimizer.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/optimizer.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c: In function ‘CVHFdot_nrs2ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:47:19: warning: unused variable ‘jsh1’ [-Wunused-variable] 47 | const int jsh1 = jshls[1]; \ | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:122:17: note: in expansion of macro ‘DECLARE_ALL’ 122 | DECLARE_ALL; | ^~~~~~~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c: In function ‘CVHFdot_nrs2kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:51:19: warning: unused variable ‘lsh1’ [-Wunused-variable] 51 | const int lsh1 = lshls[1]; \ | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:144:17: note: in expansion of macro ‘DECLARE_ALL’ 144 | DECLARE_ALL; | ^~~~~~~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c: In function ‘CVHFdot_nrs4’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:51:19: warning: unused variable ‘lsh1’ [-Wunused-variable] 51 | const int lsh1 = lshls[1]; \ | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:171:17: note: in expansion of macro ‘DECLARE_ALL’ 171 | DECLARE_ALL; | ^~~~~~~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:47:19: warning: unused variable ‘jsh1’ [-Wunused-variable] 47 | const int jsh1 = jshls[1]; \ | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:171:17: note: in expansion of macro ‘DECLARE_ALL’ 171 | DECLARE_ALL; | ^~~~~~~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c: In function ‘CVHFdot_nrs8’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:49:19: warning: unused variable ‘ksh1’ [-Wunused-variable] 49 | const int ksh1 = kshls[1]; \ | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct.c:215:9: note: in expansion of macro ‘DECLARE_ALL’ 215 | DECLARE_ALL; | ^~~~~~~~~~~ [ 40%] Building C object vhf/CMakeFiles/cvhf.dir/nr_direct_dot.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/nr_direct_dot.c.o -MF CMakeFiles/cvhf.dir/nr_direct_dot.c.o.d -o CMakeFiles/cvhf.dir/nr_direct_dot.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nrs2ij_lk_s1ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dji’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:449:17: note: in expansion of macro ‘LOCATE’ 449 | LOCATE(vji, j, i); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nrs2kl_ji_s1kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dlk’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:589:17: note: in expansion of macro ‘LOCATE’ 589 | LOCATE(vlk, l, k); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nrs4_ji_s1kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dlk’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:775:17: note: in expansion of macro ‘LOCATE’ 775 | LOCATE(vlk, l, k); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nrs4_lk_s1ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dji’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:827:17: note: in expansion of macro ‘LOCATE’ 827 | LOCATE(vji, j, i); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nra2ij_lk_s1ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dji’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:1724:17: note: in expansion of macro ‘LOCATE’ 1724 | LOCATE(vji, j, i); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nra2kl_ji_s1kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dlk’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:1857:17: note: in expansion of macro ‘LOCATE’ 1857 | LOCATE(vlk, l, k); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nra4ij_ji_s1kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dlk’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:2037:17: note: in expansion of macro ‘LOCATE’ 2037 | LOCATE(vlk, l, k); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nra4ij_lk_s1ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dji’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:2088:17: note: in expansion of macro ‘LOCATE’ 2088 | LOCATE(vji, j, i); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nra4kl_ji_s1kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dlk’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:2437:17: note: in expansion of macro ‘LOCATE’ 2437 | LOCATE(vlk, l, k); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nra4kl_lk_s1ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dji’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:2496:17: note: in expansion of macro ‘LOCATE’ 2496 | LOCATE(vji, j, i); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nraa4_ji_s1kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dlk’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:2840:17: note: in expansion of macro ‘LOCATE’ 2840 | LOCATE(vlk, l, k); | ^~~~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c: In function ‘nraa4_lk_s1ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:181:13: warning: unused variable ‘dji’ [-Wunused-variable] 181 | int d##i##j = d##i * d##j; \ | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_direct_dot.c:2891:17: note: in expansion of macro ‘LOCATE’ 2891 | LOCATE(vji, j, i); | ^~~~~~ [ 41%] Building C object vhf/CMakeFiles/cvhf.dir/time_rev.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/time_rev.c.o -MF CMakeFiles/cvhf.dir/time_rev.c.o.d -o CMakeFiles/cvhf.dir/time_rev.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/time_rev.c [ 42%] Building C object vhf/CMakeFiles/cvhf.dir/r_direct_o1.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/r_direct_o1.c.o -MF CMakeFiles/cvhf.dir/r_direct_o1.c.o.d -o CMakeFiles/cvhf.dir/r_direct_o1.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/r_direct_o1.c [ 43%] Building C object vhf/CMakeFiles/cvhf.dir/rkb_screen.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/rkb_screen.c.o -MF CMakeFiles/cvhf.dir/rkb_screen.c.o.d -o CMakeFiles/cvhf.dir/rkb_screen.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rkb_screen.c [ 44%] Building C object vhf/CMakeFiles/cvhf.dir/r_direct_dot.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/r_direct_dot.c.o -MF CMakeFiles/cvhf.dir/r_direct_dot.c.o.d -o CMakeFiles/cvhf.dir/r_direct_dot.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/r_direct_dot.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/r_direct_dot.c: In function ‘CVHFrs4_jk_s1il’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/r_direct_dot.c:490:25: warning: variable ‘peri’ set but not used [-Wunused-but-set-variable=] 490 | double complex *peri = eri; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/r_direct_dot.c: In function ‘CVHFrs4_li_s1kj’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/r_direct_dot.c:555:25: warning: variable ‘peri’ set but not used [-Wunused-but-set-variable=] 555 | double complex *peri = eri; | ^~~~ [ 45%] Building C object vhf/CMakeFiles/cvhf.dir/rah_direct_dot.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/rah_direct_dot.c.o -MF CMakeFiles/cvhf.dir/rah_direct_dot.c.o.d -o CMakeFiles/cvhf.dir/rah_direct_dot.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rah_direct_dot.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rah_direct_dot.c: In function ‘CVHFrah4_jk_s1il’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rah_direct_dot.c:294:25: warning: variable ‘peri’ set but not used [-Wunused-but-set-variable=] 294 | double complex *peri = eri; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rah_direct_dot.c: In function ‘CVHFrah4_li_s1kj’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rah_direct_dot.c:354:25: warning: variable ‘peri’ set but not used [-Wunused-but-set-variable=] 354 | double complex *peri = eri; | ^~~~ [ 46%] Building C object vhf/CMakeFiles/cvhf.dir/rha_direct_dot.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/rha_direct_dot.c.o -MF CMakeFiles/cvhf.dir/rha_direct_dot.c.o.d -o CMakeFiles/cvhf.dir/rha_direct_dot.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rha_direct_dot.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rha_direct_dot.c: In function ‘CVHFrha4_jk_s1il’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rha_direct_dot.c:291:25: warning: variable ‘peri’ set but not used [-Wunused-but-set-variable=] 291 | double complex *peri = eri; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rha_direct_dot.c: In function ‘CVHFrha4_li_s1kj’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/rha_direct_dot.c:351:25: warning: variable ‘peri’ set but not used [-Wunused-but-set-variable=] 351 | double complex *peri = eri; | ^~~~ [ 47%] Building C object vhf/CMakeFiles/cvhf.dir/hessian_screen.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/hessian_screen.c.o -MF CMakeFiles/cvhf.dir/hessian_screen.c.o.d -o CMakeFiles/cvhf.dir/hessian_screen.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/hessian_screen.c [ 48%] Building C object vhf/CMakeFiles/cvhf.dir/nr_sgx_direct.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/nr_sgx_direct.c.o -MF CMakeFiles/cvhf.dir/nr_sgx_direct.c.o.d -o CMakeFiles/cvhf.dir/nr_sgx_direct.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sgx_direct.c [ 49%] Building C object vhf/CMakeFiles/cvhf.dir/nr_sr_vhf.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/gcc -Dcvhf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT vhf/CMakeFiles/cvhf.dir/nr_sr_vhf.c.o -MF CMakeFiles/cvhf.dir/nr_sr_vhf.c.o.d -o CMakeFiles/cvhf.dir/nr_sr_vhf.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c: In function ‘CVHFdot_sr_nrs2ij’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c:170:13: warning: unused variable ‘jsh1’ [-Wunused-variable] 170 | int jsh1 = jshls[1]; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c: In function ‘CVHFdot_sr_nrs2kl’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c:307:13: warning: unused variable ‘lsh1’ [-Wunused-variable] 307 | int lsh1 = lshls[1]; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c: In function ‘CVHFnr_sr_direct_drv’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c:715:13: warning: unused variable ‘nlsh’ [-Wunused-variable] 715 | int nlsh = lsh1 - lsh0; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c:714:13: warning: unused variable ‘nksh’ [-Wunused-variable] 714 | int nksh = ksh1 - ksh0; | ^~~~ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/vhf/nr_sr_vhf.c:713:13: warning: unused variable ‘njsh’ [-Wunused-variable] 713 | int njsh = jsh1 - jsh0; | ^~~~ [ 50%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/vhf && /usr/bin/cmake -E cmake_link_script CMakeFiles/cvhf.dir/link.txt --verbose=1 /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/cvhf.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libcvhf.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so CMakeFiles/cvhf.dir/fill_nr_s8.c.o CMakeFiles/cvhf.dir/nr_incore.c.o CMakeFiles/cvhf.dir/nr_direct.c.o CMakeFiles/cvhf.dir/optimizer.c.o CMakeFiles/cvhf.dir/nr_direct_dot.c.o CMakeFiles/cvhf.dir/time_rev.c.o CMakeFiles/cvhf.dir/r_direct_o1.c.o CMakeFiles/cvhf.dir/rkb_screen.c.o CMakeFiles/cvhf.dir/r_direct_dot.c.o CMakeFiles/cvhf.dir/rah_direct_dot.c.o CMakeFiles/cvhf.dir/rha_direct_dot.c.o CMakeFiles/cvhf.dir/hessian_screen.c.o CMakeFiles/cvhf.dir/nr_sgx_direct.c.o CMakeFiles/cvhf.dir/nr_sr_vhf.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so -lcint /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 50%] Built target cvhf /usr/bin/gmake -f ao2mo/CMakeFiles/ao2mo.dir/build.make ao2mo/CMakeFiles/ao2mo.dir/depend /usr/bin/gmake -f pbc/CMakeFiles/pbc.dir/build.make pbc/CMakeFiles/pbc.dir/depend /usr/bin/gmake -f agf2/CMakeFiles/agf2.dir/build.make agf2/CMakeFiles/agf2.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo/CMakeFiles/ao2mo.dir/DependInfo.cmake "--color=" gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/agf2 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2/CMakeFiles/agf2.dir/DependInfo.cmake "--color=" gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc/CMakeFiles/pbc.dir/DependInfo.cmake "--color=" gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f ao2mo/CMakeFiles/ao2mo.dir/build.make ao2mo/CMakeFiles/ao2mo.dir/build /usr/bin/gmake -f pbc/CMakeFiles/pbc.dir/build.make pbc/CMakeFiles/pbc.dir/build /usr/bin/gmake -f agf2/CMakeFiles/agf2.dir/build.make agf2/CMakeFiles/agf2.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 51%] Building C object ao2mo/CMakeFiles/ao2mo.dir/restore_eri.c.o [ 51%] Building C object agf2/CMakeFiles/agf2.dir/ragf2.c.o [ 53%] Building C object pbc/CMakeFiles/pbc.dir/ft_ao.c.o [ 52%] Building C object agf2/CMakeFiles/agf2.dir/uagf2.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2 && /usr/bin/gcc -Dagf2_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2 -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/agf2 -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT agf2/CMakeFiles/agf2.dir/ragf2.c.o -MF CMakeFiles/agf2.dir/ragf2.c.o.d -o CMakeFiles/agf2.dir/ragf2.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/agf2/ragf2.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo && /usr/bin/gcc -Dao2mo_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo 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/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo/restore_eri.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/ft_ao.c.o -MF CMakeFiles/pbc.dir/ft_ao.c.o.d -o CMakeFiles/pbc.dir/ft_ao.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/ft_ao.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2 && /usr/bin/gcc -Dagf2_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2 -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/agf2 -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT agf2/CMakeFiles/agf2.dir/uagf2.c.o -MF CMakeFiles/agf2.dir/uagf2.c.o.d -o CMakeFiles/agf2.dir/uagf2.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/agf2/uagf2.c [ 54%] Building C object ao2mo/CMakeFiles/ao2mo.dir/nr_ao2mo.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo && /usr/bin/gcc -Dao2mo_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT ao2mo/CMakeFiles/ao2mo.dir/nr_ao2mo.c.o -MF CMakeFiles/ao2mo.dir/nr_ao2mo.c.o.d -o CMakeFiles/ao2mo.dir/nr_ao2mo.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo/nr_ao2mo.c [ 55%] Building C object ao2mo/CMakeFiles/ao2mo.dir/nr_incore.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo && /usr/bin/gcc -Dao2mo_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT ao2mo/CMakeFiles/ao2mo.dir/nr_incore.c.o -MF CMakeFiles/ao2mo.dir/nr_incore.c.o.d -o CMakeFiles/ao2mo.dir/nr_incore.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo/nr_incore.c [ 56%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libagf2.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/agf2 && /usr/bin/cmake -E cmake_link_script CMakeFiles/agf2.dir/link.txt --verbose=1 [ 57%] Building C object pbc/CMakeFiles/pbc.dir/fill_ints.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/fill_ints.c.o -MF CMakeFiles/pbc.dir/fill_ints.c.o.d -o CMakeFiles/pbc.dir/fill_ints.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/fill_ints.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/agf2.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libagf2.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libagf2.so CMakeFiles/agf2.dir/ragf2.c.o CMakeFiles/agf2.dir/uagf2.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a -lcint /usr/lib64/libflexiblas.so gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 57%] Built target agf2 [ 58%] Building C object ao2mo/CMakeFiles/ao2mo.dir/r_ao2mo.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo && /usr/bin/gcc -Dao2mo_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT ao2mo/CMakeFiles/ao2mo.dir/r_ao2mo.c.o -MF CMakeFiles/ao2mo.dir/r_ao2mo.c.o.d -o CMakeFiles/ao2mo.dir/r_ao2mo.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo/r_ao2mo.c [ 59%] Building C object ao2mo/CMakeFiles/ao2mo.dir/nrr_ao2mo.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo && /usr/bin/gcc -Dao2mo_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ao2mo -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection 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-mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/grid_ao.c.o -MF CMakeFiles/pbc.dir/grid_ao.c.o.d -o CMakeFiles/pbc.dir/grid_ao.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/grid_ao.c [ 63%] Building C object pbc/CMakeFiles/pbc.dir/nr_direct.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/nr_direct.c.o -MF CMakeFiles/pbc.dir/nr_direct.c.o.d -o CMakeFiles/pbc.dir/nr_direct.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/nr_direct.c [ 64%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libao2mo.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ao2mo && /usr/bin/cmake -E cmake_link_script CMakeFiles/ao2mo.dir/link.txt --verbose=1 [ 65%] Building C object pbc/CMakeFiles/pbc.dir/symmetry.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer 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-Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/inner_dot.c.o -MF CMakeFiles/pbc.dir/inner_dot.c.o.d -o CMakeFiles/pbc.dir/inner_dot.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/inner_dot.c [ 67%] Building C object pbc/CMakeFiles/pbc.dir/cint2e.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/cint2e.c.o -MF CMakeFiles/pbc.dir/cint2e.c.o.d -o CMakeFiles/pbc.dir/cint2e.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/cint2e.c [ 68%] Building C object pbc/CMakeFiles/pbc.dir/cint3c2e.c.o cd 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-Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/nr_ecp.c.o -MF CMakeFiles/pbc.dir/nr_ecp.c.o.d -o CMakeFiles/pbc.dir/nr_ecp.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/nr_ecp.c [ 70%] Building C object pbc/CMakeFiles/pbc.dir/transform_mo.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/transform_mo.c.o -MF CMakeFiles/pbc.dir/transform_mo.c.o.d -o CMakeFiles/pbc.dir/transform_mo.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/transform_mo.c [ 71%] Building C object pbc/CMakeFiles/pbc.dir/neighbor_list.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/neighbor_list.c.o -MF CMakeFiles/pbc.dir/neighbor_list.c.o.d -o CMakeFiles/pbc.dir/neighbor_list.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/neighbor_list.c [ 72%] Building C object pbc/CMakeFiles/pbc.dir/cell.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/cell.c.o -MF CMakeFiles/pbc.dir/cell.c.o.d -o CMakeFiles/pbc.dir/cell.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/cell.c [ 73%] Building C object pbc/CMakeFiles/pbc.dir/pp.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/pp.c.o -MF CMakeFiles/pbc.dir/pp.c.o.d -o CMakeFiles/pbc.dir/pp.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/pp.c [ 74%] Building C object pbc/CMakeFiles/pbc.dir/hf_grad.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/hf_grad.c.o -MF CMakeFiles/pbc.dir/hf_grad.c.o.d -o CMakeFiles/pbc.dir/hf_grad.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/hf_grad.c [ 75%] Building C object pbc/CMakeFiles/pbc.dir/fill_ints_screened.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/gcc -Dpbc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pbc/CMakeFiles/pbc.dir/fill_ints_screened.c.o -MF CMakeFiles/pbc.dir/fill_ints_screened.c.o.d -o CMakeFiles/pbc.dir/fill_ints_screened.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/fill_ints_screened.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/ao2mo.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libao2mo.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libao2mo.so CMakeFiles/ao2mo.dir/restore_eri.c.o CMakeFiles/ao2mo.dir/nr_ao2mo.c.o CMakeFiles/ao2mo.dir/nr_incore.c.o CMakeFiles/ao2mo.dir/r_ao2mo.c.o CMakeFiles/ao2mo.dir/nrr_ao2mo.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so -lcint /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 75%] Built target ao2mo /usr/bin/gmake -f mcscf/CMakeFiles/mcscf.dir/build.make mcscf/CMakeFiles/mcscf.dir/depend /usr/bin/gmake -f cc/CMakeFiles/cc.dir/build.make cc/CMakeFiles/cc.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf 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/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc/CMakeFiles/cc.dir/DependInfo.cmake "--color=" /usr/bin/gmake -f ri/CMakeFiles/ri.dir/build.make ri/CMakeFiles/ri.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ri /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ri /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ri/CMakeFiles/ri.dir/DependInfo.cmake "--color=" gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f cc/CMakeFiles/cc.dir/build.make cc/CMakeFiles/cc.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f mcscf/CMakeFiles/mcscf.dir/build.make mcscf/CMakeFiles/mcscf.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f ri/CMakeFiles/ri.dir/build.make ri/CMakeFiles/ri.dir/build [ 76%] Building C object cc/CMakeFiles/cc.dir/ccsd_pack.c.o gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 77%] Building C object mcscf/CMakeFiles/mcscf.dir/nevpt_contract.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc && /usr/bin/gcc -Dcc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT cc/CMakeFiles/cc.dir/ccsd_pack.c.o -MF CMakeFiles/cc.dir/ccsd_pack.c.o.d -o CMakeFiles/cc.dir/ccsd_pack.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/ccsd_pack.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/gcc -Dmcscf_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT mcscf/CMakeFiles/mcscf.dir/nevpt_contract.c.o -MF CMakeFiles/mcscf.dir/nevpt_contract.c.o.d -o CMakeFiles/mcscf.dir/nevpt_contract.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/mcscf/nevpt_contract.c [ 78%] Building C object ri/CMakeFiles/ri.dir/r_df_incore.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ri && /usr/bin/gcc -Dri_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ri -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ri -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT ri/CMakeFiles/ri.dir/r_df_incore.c.o -MF CMakeFiles/ri.dir/r_df_incore.c.o.d -o CMakeFiles/ri.dir/r_df_incore.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/ri/r_df_incore.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/ccsd_pack.c: In function ‘CCmake_0213’: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/ccsd_pack.c:35:25: warning: variable ‘n’ set but not used [-Wunused-but-set-variable=] 35 | int i, j, k, l, n; | ^ [ 79%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libri.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/ri && /usr/bin/cmake -E cmake_link_script CMakeFiles/ri.dir/link.txt --verbose=1 [ 80%] Building C object cc/CMakeFiles/cc.dir/ccsd_grad.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc && /usr/bin/gcc -Dcc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT cc/CMakeFiles/cc.dir/ccsd_grad.c.o -MF CMakeFiles/cc.dir/ccsd_grad.c.o.d -o CMakeFiles/cc.dir/ccsd_grad.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/ccsd_grad.c [ 81%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libmcscf.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/mcscf && /usr/bin/cmake -E cmake_link_script CMakeFiles/mcscf.dir/link.txt --verbose=1 [ 82%] Building C object cc/CMakeFiles/cc.dir/ccsd_t.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc && /usr/bin/gcc -Dcc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT cc/CMakeFiles/cc.dir/ccsd_t.c.o -MF CMakeFiles/cc.dir/ccsd_t.c.o.d -o CMakeFiles/cc.dir/ccsd_t.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/ccsd_t.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/ri.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libri.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libri.so CMakeFiles/ri.dir/r_df_incore.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libao2mo.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 82%] Built target ri [ 83%] Building C object cc/CMakeFiles/cc.dir/ccsd_t_lambda.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc && /usr/bin/gcc -Dcc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT cc/CMakeFiles/cc.dir/ccsd_t_lambda.c.o -MF CMakeFiles/cc.dir/ccsd_t_lambda.c.o.d -o CMakeFiles/cc.dir/ccsd_t_lambda.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/ccsd_t_lambda.c /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/mcscf.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libmcscf.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libmcscf.so CMakeFiles/mcscf.dir/nevpt_contract.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libfci.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libao2mo.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a -lcint /usr/lib64/libflexiblas.so [ 84%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libpbc.so gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pbc && /usr/bin/cmake -E cmake_link_script CMakeFiles/pbc.dir/link.txt --verbose=1 [ 84%] Built target mcscf [ 85%] Building C object cc/CMakeFiles/cc.dir/uccsd_t.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc && /usr/bin/gcc -Dcc_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT cc/CMakeFiles/cc.dir/uccsd_t.c.o -MF CMakeFiles/cc.dir/uccsd_t.c.o.d -o CMakeFiles/cc.dir/uccsd_t.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/cc/uccsd_t.c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pbc/fill_ints_sr.c:36:5: warning: type of ‘GTOmax_cache_size’ does not match original declaration [-Wlto-type-mismatch] 36 | int GTOmax_cache_size(int (*intor)(), int *shls_slice, int ncenter, | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/gto.h:17:8: note: return value type mismatch 17 | size_t GTOmax_cache_size(int (*intor)(), int *shls_slice, int ncenter, | ^ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/gto.h:17:8: note: type ‘size_t’ should match type ‘int’ /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/gto.h:17:8: note: ‘GTOmax_cache_size’ was previously declared here /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/gto.h:17:8: note: code may be misoptimized unless ‘-fno-strict-aliasing’ is used [ 86%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcc.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/cc && /usr/bin/cmake -E cmake_link_script CMakeFiles/cc.dir/link.txt --verbose=1 /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/cc.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libcc.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcc.so CMakeFiles/cc.dir/ccsd_pack.c.o CMakeFiles/cc.dir/ccsd_grad.c.o CMakeFiles/cc.dir/ccsd_t.c.o CMakeFiles/cc.dir/ccsd_t_lambda.c.o CMakeFiles/cc.dir/uccsd_t.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libao2mo.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a -lcint /usr/lib64/libflexiblas.so gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 86%] Built target cc /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/pbc.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libpbc.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libpbc.so CMakeFiles/pbc.dir/ft_ao.c.o CMakeFiles/pbc.dir/fill_ints.c.o CMakeFiles/pbc.dir/fill_ints_sr.c.o CMakeFiles/pbc.dir/optimizer.c.o CMakeFiles/pbc.dir/grid_ao.c.o CMakeFiles/pbc.dir/nr_direct.c.o CMakeFiles/pbc.dir/symmetry.c.o CMakeFiles/pbc.dir/inner_dot.c.o CMakeFiles/pbc.dir/cint2e.c.o CMakeFiles/pbc.dir/cint3c2e.c.o CMakeFiles/pbc.dir/nr_ecp.c.o CMakeFiles/pbc.dir/transform_mo.c.o CMakeFiles/pbc.dir/neighbor_list.c.o CMakeFiles/pbc.dir/cell.c.o CMakeFiles/pbc.dir/pp.c.o CMakeFiles/pbc.dir/hf_grad.c.o CMakeFiles/pbc.dir/fill_ints_screened.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so 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-mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/CxLebedevGrid.c.o -MF CMakeFiles/dft.dir/CxLebedevGrid.c.o.d -o CMakeFiles/dft.dir/CxLebedevGrid.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/CxLebedevGrid.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/grid_basis.c.o -MF CMakeFiles/dft.dir/grid_basis.c.o.d -o CMakeFiles/dft.dir/grid_basis.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_basis.c cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft 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dft/CMakeFiles/dft.dir/numint_uniform_grid.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/numint_uniform_grid.c.o -MF CMakeFiles/dft.dir/numint_uniform_grid.c.o.d -o CMakeFiles/dft.dir/numint_uniform_grid.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/numint_uniform_grid.c [ 92%] Building C object dft/CMakeFiles/dft.dir/xc_deriv.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/xc_deriv.c.o -MF CMakeFiles/dft.dir/xc_deriv.c.o.d -o CMakeFiles/dft.dir/xc_deriv.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/xc_deriv.c [ 93%] Building C object dft/CMakeFiles/dft.dir/nr_numint_sparse.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/nr_numint_sparse.c.o -MF CMakeFiles/dft.dir/nr_numint_sparse.c.o.d -o CMakeFiles/dft.dir/nr_numint_sparse.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/nr_numint_sparse.c [ 94%] Building C object dft/CMakeFiles/dft.dir/multigrid.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/multigrid.c.o -MF CMakeFiles/dft.dir/multigrid.c.o.d -o CMakeFiles/dft.dir/multigrid.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/multigrid.c [ 95%] Building C object dft/CMakeFiles/dft.dir/grid_common.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/grid_common.c.o -MF CMakeFiles/dft.dir/grid_common.c.o.d -o CMakeFiles/dft.dir/grid_common.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_common.c In file included from /usr/include/string.h:580, from /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_common.c:21: In function ‘memset’, inlined from ‘_orth_components’ at /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_common.c:286:9: /usr/include/bits/string_fortified.h:59:10: warning: ‘memset’ specified bound between 18446744056529682432 and 18446744073709551600 exceeds maximum object size 9223372036854775807 [-Wstringop-overflow=] 59 | return __builtin___memset_chk (__dest, __ch, __len, | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | __glibc_objsize0 (__dest)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~ [ 96%] Building C object dft/CMakeFiles/dft.dir/grid_collocate.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/grid_collocate.c.o -MF CMakeFiles/dft.dir/grid_collocate.c.o.d -o CMakeFiles/dft.dir/grid_collocate.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_collocate.c [ 97%] Building C object dft/CMakeFiles/dft.dir/grid_integrate.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/gcc -Ddft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT dft/CMakeFiles/dft.dir/grid_integrate.c.o -MF CMakeFiles/dft.dir/grid_integrate.c.o.d -o CMakeFiles/dft.dir/grid_integrate.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_integrate.c [ 98%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libdft.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/dft && /usr/bin/cmake -E cmake_link_script CMakeFiles/dft.dir/link.txt --verbose=1 In function ‘memset’, inlined from ‘_orth_components’ at /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/dft/grid_common.c:286:9: /usr/include/bits/string_fortified.h:59:10: warning: ‘__builtin_memset’ specified bound between 18446744056529682432 and 18446744073709551600 exceeds maximum object size 9223372036854775807 [-Wstringop-overflow=] 59 | return __builtin___memset_chk (__dest, __ch, __len, | ^ /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/dft.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libdft.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libdft.so CMakeFiles/dft.dir/CxLebedevGrid.c.o CMakeFiles/dft.dir/grid_basis.c.o CMakeFiles/dft.dir/nr_numint.c.o CMakeFiles/dft.dir/r_numint.c.o CMakeFiles/dft.dir/numint_uniform_grid.c.o CMakeFiles/dft.dir/xc_deriv.c.o CMakeFiles/dft.dir/nr_numint_sparse.c.o CMakeFiles/dft.dir/multigrid.c.o CMakeFiles/dft.dir/grid_common.c.o CMakeFiles/dft.dir/grid_collocate.c.o CMakeFiles/dft.dir/grid_integrate.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libpbc.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 98%] Built target dft /usr/bin/gmake -f pdft/CMakeFiles/pdft.dir/build.make pdft/CMakeFiles/pdft.dir/depend gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pdft /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pdft /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pdft/CMakeFiles/pdft.dir/DependInfo.cmake "--color=" gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/gmake -f pdft/CMakeFiles/pdft.dir/build.make pdft/CMakeFiles/pdft.dir/build gmake[2]: Entering directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [ 99%] Building C object pdft/CMakeFiles/pdft.dir/nr_numint.c.o cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pdft && /usr/bin/gcc -Dpdft_EXPORTS -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pdft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pdft -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/include -I/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -std=gnu99 -fPIC -fopenmp -MD -MT pdft/CMakeFiles/pdft.dir/nr_numint.c.o -MF CMakeFiles/pdft.dir/nr_numint.c.o.d -o CMakeFiles/pdft.dir/nr_numint.c.o -c /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/pdft/nr_numint.c [100%] Linking C shared library /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libpdft.so cd /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/pdft && /usr/bin/cmake -E cmake_link_script CMakeFiles/pdft.dir/link.txt --verbose=1 /usr/bin/gcc -fPIC -Wall -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -O2 -g -DNDEBUG -Wl,--dependency-file=CMakeFiles/pdft.dir/link.d -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes -shared -Wl,-soname,libpdft.so -o /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libpdft.so CMakeFiles/pdft.dir/nr_numint.c.o -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib -L/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/deps/lib64 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libdft.so /usr/lib64/libflexiblas.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libpbc.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcvhf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libcgto.so -lcint /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/libnp_helper.so /usr/lib64/libflexiblas.so /usr/lib/gcc/aarch64-redhat-linux/16/libgomp.so /usr/lib64/libpthread.a gmake[2]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' [100%] Built target pdft gmake[1]: Leaving directory '/builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build' /usr/bin/cmake -E cmake_progress_start /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/redhat-linux-build/CMakeFiles 0 + RPM_EC=0 ++ jobs -p + exit 0 Executing(%install): /bin/sh -e /var/tmp/rpm-tmp.E9qd2n + umask 022 + cd /builddir/build/BUILD/python-pyscf-2.11.0-build + '[' /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT '!=' / ']' + rm -rf /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT ++ dirname /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT + mkdir -p /builddir/build/BUILD/python-pyscf-2.11.0-build + mkdir /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd pyscf-2.11.0 ++ find pyscf -name '*.py' + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/post_scf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/post_scf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/__config__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__config__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/__all__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__all__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/x2c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/x2c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/tdscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/tdscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/stability.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/stability.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/sfx2c1e_hess.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/sfx2c1e_hess.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/sfx2c1e_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/sfx2c1e_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/sfx2c1e.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/sfx2c1e.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/newton_ah.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/newton_ah.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/dft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/dft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/_response_functions.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/_response_functions.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/test/test_x2c_hess.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/test_x2c_hess.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/test/test_x2c_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/test_x2c_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/test/test_x2c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/test_x2c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/test/test_tdscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/test_tdscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/x2c/test/test_dft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/test_dft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/wfn_format.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/wfn_format.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/ring.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/ring.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/qcschema.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/qcschema.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/molden.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/molden.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/mo_mapping.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/mo_mapping.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/finite_diff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/finite_diff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/fcidump.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/fcidump.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/dump_mat.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/dump_mat.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/cubegen.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/cubegen.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/chkfile_util.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/chkfile_util.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/chgcar.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/chgcar.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/c60struct.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/c60struct.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/test/test_qcschema.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/test/test_qcschema.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/test/test_molden.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/test/test_molden.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/test/test_mo_mapping.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/test/test_mo_mapping.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/test/test_finite_diff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/test/test_finite_diff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/test/test_fcidump.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/test/test_fcidump.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tools/test/test_cubegen.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tools/test/test_cubegen.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/gks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/gks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/ghf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/ghf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/dks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/dks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/dhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/dhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/_lr_eig.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/_lr_eig.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tduks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tduks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tduhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tduhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tdrks_vv10.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tdrks_vv10.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tdrks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tdrks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tdrhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tdrhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tdgks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tdgks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tdscf/test/test_tddks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tdscf/test/test_tddks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/tddft/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/tddft/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/sph.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/sph.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/param.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/param.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/msym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/msym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/geom.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/geom.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/cg.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/cg.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/basis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/basis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/Dmatrix.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/Dmatrix.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/test/test_sph.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/test/test_sph.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/test/test_geom.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/test/test_geom.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/test/test_basis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/test/test_basis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/symm/test/test_Dmatrix.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/symm/test/test_Dmatrix.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/soscf/newton_ah.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/soscf/newton_ah.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/soscf/ciah.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/soscf/ciah.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/soscf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/soscf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/soscf/test/test_newton_ah.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/soscf/test/test_newton_ah.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/smd_experiment.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/smd_experiment.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/smd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/smd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/pol_embed.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/pol_embed.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/pcm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/pcm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/ddpcm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/ddpcm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/ddcosmo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/ddcosmo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/cosmors.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/cosmors.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/_attach_solvent.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/_attach_solvent.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_smd_hessian.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_smd_hessian.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_smd_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_smd_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_smd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_smd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_pol_embed.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_pol_embed.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_pcm_tdscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_pcm_tdscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_pcm_hessian.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_pcm_hessian.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_pcm_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_pcm_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_pcm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_pcm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_ddpcm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_ddpcm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_ddcosmo_tdscf_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_ddcosmo_tdscf_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_ddcosmo_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_ddcosmo_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_ddcosmo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_ddcosmo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/test/test_cosmors.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_cosmors.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/hessian/smd_experiment.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/hessian/smd_experiment.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/hessian/smd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/hessian/smd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/hessian/pcm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/hessian/pcm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/hessian/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/hessian/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/grad/smd_experiment.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/grad/smd_experiment.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/grad/smd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/grad/smd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/grad/pcm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/grad/pcm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/grad/ddcosmo_tdscf_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/grad/ddcosmo_tdscf_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/grad/ddcosmo_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/grad/ddcosmo_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/solvent/grad/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/solvent/grad/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/sgx/sgx_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/sgx/sgx_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/sgx/sgx.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/sgx/sgx.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/sgx/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/sgx/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/sgx/test/test_sgx_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/sgx/test/test_sgx_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/sgx/test/test_sgx.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/sgx/test/test_sgx.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/uhf_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/uhf_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/ucphf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/ucphf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/stability_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/stability_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/stability.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/stability.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/rohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/rohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/hf_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/hf_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/hf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/hf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/ghf_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/ghf_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/ghf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/ghf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/dispersion.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/dispersion.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/diis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/diis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/dhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/dhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/cphf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/cphf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/atom_ks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/atom_ks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/atom_hf_pp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/atom_hf_pp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/atom_hf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/atom_hf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/_vhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/_vhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/_response_functions.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/_response_functions.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_vhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_vhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_stability.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_stability.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_response_function.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_response_function.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_he.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_he.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_h2o_vdz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_h2o_vdz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_ghf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_ghf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_diis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_diis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_dhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_dhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_bz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_bz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/scf/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/scf/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/mm_mole.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/mm_mole.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/itrf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/itrf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/test/test_itrf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/test/test_itrf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/test/test_grad_mm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/test/test_grad_mm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/pbc/mm_mole.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/pbc/mm_mole.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/pbc/itrf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/pbc/itrf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/pbc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/pbc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/qmmm/pbc/test/test_qmmm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/qmmm/pbc/test/test_qmmm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/__all__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/__all__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/x2c/x2c1e.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/x2c/x2c1e.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/x2c/sfx2c1e.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/x2c/sfx2c1e.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/x2c/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/x2c/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/x2c/test/test_x2c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/x2c/test/test_x2c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/tril.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/tril.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/pywannier90.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/pywannier90.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/pyscf_ase.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/pyscf_ase.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/print_funcs.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/print_funcs.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/pbc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/pbc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/make_test_cell.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/make_test_cell.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/lattice.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/lattice.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/k2gamma.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/k2gamma.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/test/test_pbc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/test/test_pbc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tools/test/test_k2gamma.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tools/test/test_k2gamma.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/kuks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/kuks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/kuhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/kuhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/krks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/krks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/krhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/krhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_kuks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_kuks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_kuhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_kuhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_krks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_krks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tdscf/test/test_krhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tdscf/test/test_krhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/tddft/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/tddft/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/tables.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/tables.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/symmetry.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/symmetry.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/space_group.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/space_group.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/pyscf_spglib.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/pyscf_spglib.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/group.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/group.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/geom.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/geom.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/basis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/basis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/test/test_spg.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/test/test_spg.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/symm/test/test_basis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/symm/test/test_basis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/rsjk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/rsjk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/stability.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/stability.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/scfint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/scfint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/rohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/rohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/newton_ah.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/newton_ah.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/kuhf_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/kuhf_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/kuhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/kuhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/krohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/krohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/khf_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/khf_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/khf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/khf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/kghf_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/kghf_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/kghf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/kghf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/hf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/hf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/ghf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/ghf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/cphf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/cphf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/_response_functions.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/_response_functions.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_stability.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_stability.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_scfint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_scfint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_rsjk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_rsjk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_rohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_rohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_newton.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_newton.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_mulliken_meta.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_mulliken_meta.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_khf_ksym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_khf_ksym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_khf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_khf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_hf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_hf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_band.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_band.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/scf/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/scf/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpitools/mpi_pool.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpitools/mpi_pool.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpitools/mpi_load_balancer.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpitools/mpi_load_balancer.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpitools/mpi_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpitools/mpi_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpitools/mpi_blksize.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpitools/mpi_blksize.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpitools/mpi.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpitools/mpi.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpitools/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpitools/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpicc/mpi_kpoint_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpicc/mpi_kpoint_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpicc/kintermediates_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpicc/kintermediates_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpicc/kccsd_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpicc/kccsd_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mpicc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mpicc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/mp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/mp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/kump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/kump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/kmp2_stagger.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/kmp2_stagger.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/kmp2_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/kmp2_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/kmp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/kmp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_scs.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_scs.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_padding.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_padding.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_mask_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_mask_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_mask.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_mask.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_ksym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_ksym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_kpoint_stagger.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_kpoint_stagger.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_kpoint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_kpoint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/mp/test/test_dm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/mp/test/test_dm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/linalg_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/linalg_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/ktensor.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/ktensor.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/kpts_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/kpts_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/kpts.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/kpts.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/arnoldi.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/arnoldi.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/test/test_kpts_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/test/test_kpts_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/lib/test/test_kpts.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/lib/test/test_kpts.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/kugw_ac.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/kugw_ac.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/krgw_cd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/krgw_cd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/krgw_ac.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/krgw_ac.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/kgw_slow_supercell.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/kgw_slow_supercell.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/kgw_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/kgw_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/gw_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/gw_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/test/test_kugw.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/test/test_kugw.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gw/test/test_krgw.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gw/test/test_krgw.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/neighborlist.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/neighborlist.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/ewald_methods.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/ewald_methods.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/eval_gto.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/eval_gto.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/ecp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/ecp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/cell.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/cell.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/_pbcintor.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/_pbcintor.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/test/test_rcut.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/test/test_rcut.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/test/test_cell.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/test/test_cell.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/pseudo/split_GTH_POTENTIALS.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/split_GTH_POTENTIALS.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/pseudo/pp_int.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/pp_int.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/pseudo/pp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/pp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/pseudo/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/pseudo/test/test_pp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/test/test_pp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/basis/split_HFX_BASIS.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/split_HFX_BASIS.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/basis/split_GTH_BASIS_SETS.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/split_GTH_BASIS_SETS.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/basis/split_BASIS_MOLOPT.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/split_BASIS_MOLOPT.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/gto/basis/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/uks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/uks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/rks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/rks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/kukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/kukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/kuks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/kuks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/kuks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/kuks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/kuhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/kuhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/krkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/krkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/krks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/krks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/krks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/krks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/krhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/krhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_uks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_uks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_rks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_rks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_kukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_kukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_kuks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_kuks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_kuks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_kuks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_kuhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_kuhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_krkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_krkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_krks_stress.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_krks_stress.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_krks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_krks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/grad/test/test_krhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/grad/test/test_krhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/geomopt/geometric_solver.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/geomopt/geometric_solver.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/geomopt/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/geomopt/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/eph/eph_fd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/eph/eph_fd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/eph/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/eph/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/roks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/roks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/numint2c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/numint2c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/numint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/numint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/kukspu_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/kukspu_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/kukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/kukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/kuks_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/kuks_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/kuks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/kuks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/kroks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/kroks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/krkspu_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/krkspu_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/krkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/krkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/krks_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/krks_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/krks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/krks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/kgks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/kgks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/gks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/gks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/gen_grid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/gen_grid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/cdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/cdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_sampling.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_sampling.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_numint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_numint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_multigrid2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_multigrid2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_multigrid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_multigrid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_kukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_kukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_kuks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_kuks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_krkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_krkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_krks_ksym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_krks_ksym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_krks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_krks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_kgks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_kgks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_gks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_gks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_gen_grid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_gen_grid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/test/test_gamma_vs_ks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/test/test_gamma_vs_ks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/multigrid/utils.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/multigrid/utils.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/multigrid/pp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/multigrid/pp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/multigrid/multigrid_pair.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/multigrid/multigrid_pair.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/multigrid/multigrid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/multigrid/multigrid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/multigrid/_backend_c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/multigrid/_backend_c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/dft/multigrid/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/dft/multigrid/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/rsdf_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/rsdf_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/rsdf_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/rsdf_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/rsdf_builder.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/rsdf_builder.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/rsdf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/rsdf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/mdf_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/mdf_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/mdf_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/mdf_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/mdf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/mdf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/gdf_builder.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/gdf_builder.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/ft_ao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/ft_ao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/fft_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/fft_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/fft_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/fft_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/fft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/fft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/df_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/df_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/df_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/df_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/aft_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/aft_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/aft_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/aft_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/aft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/aft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_rsdf_scf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_rsdf_scf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_rsdf_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_rsdf_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_rsdf_builder.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_rsdf_builder.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_rsdf_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_rsdf_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_rsdf_1.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_rsdf_1.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_rsdf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_rsdf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_mdf_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_mdf_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_mdf_builder.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_mdf_builder.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_mdf_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_mdf_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_mdf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_mdf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_gdf_builder.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_gdf_builder.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_ft_ao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_ft_ao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_fft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_fft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_df_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_df_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_df_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_df_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_band.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_band.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_aft_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_aft_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_aft_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_aft_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/df/test/test_aft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/df/test/test_aft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ci/kcis_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ci/kcis_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ci/cisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ci/cisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ci/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ci/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ci/test/test_cisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ci/test/test_cisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ci/test/test_ci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ci/test/test_ci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kuccsd_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kuccsd_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kintermediates_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kintermediates_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kintermediates_rhf_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kintermediates_rhf_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kintermediates_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kintermediates_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kintermediates.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kintermediates.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd_t_rhf_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd_t_rhf_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd_t_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd_t_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd_rhf_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd_rhf_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/kccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/kccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/eom_kccsd_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/eom_kccsd_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/eom_kccsd_rhf_ip.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/eom_kccsd_rhf_ip.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/eom_kccsd_rhf_ea.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/eom_kccsd_rhf_ea.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/eom_kccsd_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/eom_kccsd_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/eom_kccsd_ghf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/eom_kccsd_ghf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/ccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/ccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_rccsd_t_shift.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_rccsd_t_shift.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_kuccsd_supercell_vs_kpts.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_kuccsd_supercell_vs_kpts.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_kuccsd_openshell.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_kuccsd_openshell.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_kuccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_kuccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_krccsd_gamma.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_krccsd_gamma.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_krccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_krccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_kgccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_kgccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_kccsd_ksymm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_kccsd_ksymm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_h_3x3x1.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_h_3x3x1.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_h_2x2x1.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_h_2x2x1.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_eom_kuccsd_diag.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_eom_kuccsd_diag.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_eom_kuccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_eom_kuccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_eom_krccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_eom_krccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_eom_kgccsd_diag.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_eom_kgccsd_diag.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/cc/test/test_eom_kgccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/cc/test/test_eom_kgccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ao2mo/eris.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ao2mo/eris.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/ao2mo/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/ao2mo/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/kadc_rhf_ip.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/kadc_rhf_ip.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/kadc_rhf_ea.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/kadc_rhf_ea.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/kadc_rhf_amplitudes.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/kadc_rhf_amplitudes.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/kadc_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/kadc_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/kadc_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/kadc_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/dfadc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/dfadc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_kadc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_kadc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_k_vs_supercell_ip_highcost.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_k_vs_supercell_ip_highcost.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_k_vs_supercell_ip.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_k_vs_supercell_ip.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_k_vs_supercell_ea_highcost.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_k_vs_supercell_ea_highcost.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_k_vs_supercell_ea.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_k_vs_supercell_ea.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_k_ip.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_k_ip.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_k_ea.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_k_ea.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/pbc/adc/test/test_ground_state_energy.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/adc/test/test_ground_state_energy.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/nac/sacasscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/nac/sacasscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/nac/mspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/nac/mspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/nac/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/nac/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/nac/test/test_sacasscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/nac/test/test_sacasscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/nac/test/test_cmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/nac/test/test_cmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mrpt/nevpt2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mrpt/nevpt2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mrpt/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mrpt/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mrpt/test/test_nevpt2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mrpt/test/test_nevpt2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/ump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/ump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/mp2f12_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/mp2f12_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/mp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/mp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/gmp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/gmp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfump2_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfump2_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfump2_native.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfump2_native.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfmp2_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfmp2_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfmp2_native.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfmp2_native.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfmp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfmp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/dfgmp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/dfgmp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_ump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_ump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_mp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_mp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_gmp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_gmp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_f12.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_f12.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_dfump2_native.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_dfump2_native.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_dfump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_dfump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_dfmp2_native.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_dfmp2_native.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mp/test/test_dfmp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mp/test/test_dfmp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/integrators.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/integrators.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/distributions.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/distributions.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/test/test_velocverlet.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/test/test_velocverlet.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/test/test_prop.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/test/test_prop.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/test/test_distributions.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/test/test_distributions.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/md/test/test_NVTBerendson.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/md/test/test_NVTBerendson.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/umc_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/umc_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/umc2step.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/umc2step.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/umc1step.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/umc1step.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/ucasci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/ucasci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/newton_casscf_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/newton_casscf_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/newton_casscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/newton_casscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/mc_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/mc_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/mc2step.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/mc2step.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/mc1step_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/mc1step_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/mc1step.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/mc1step.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/dmet_cas.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/dmet_cas.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/casci_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/casci_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/casci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/casci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/avas.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/avas.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/apc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/apc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/PiOS.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/PiOS.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_umc1step.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_umc1step.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_ucasci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_ucasci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_newton_casscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_newton_casscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_n2_df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_n2_df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_n2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_n2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_mcao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_mcao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_mc1step.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_mc1step.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_casci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_casci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_c2h4.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_c2h4.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_bz_df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_bz_df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_bz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_bz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_avas.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_avas.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_apc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_apc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcscf/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcscf/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/xmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/xmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/tfnal_derivs.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/tfnal_derivs.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/pdft_veff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/pdft_veff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/pdft_feff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/pdft_feff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/pdft_eff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/pdft_eff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/otpd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/otpd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/otfnal.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/otfnal.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/mspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/mspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/mcpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/mcpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/lpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/lpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/cmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/cmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/_libxc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/_libxc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/_dms.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/_dms.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_xmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_xmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_spingaps_atoms.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_spingaps_atoms.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_pdft_veff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_pdft_veff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_pdft_feff.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_pdft_feff.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_otpd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_otpd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_otfnal.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_otfnal.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_mspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_mspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_mgga.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_mgga.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_mcpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_mcpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_lpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_lpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_diatomic_energies.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_diatomic_energies.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/mcpdft/test/test_cmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/mcpdft/test/test_cmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/vvo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/vvo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/pipek_jacobi.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/pipek_jacobi.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/pipek.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/pipek.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/orth.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/orth.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/nao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/nao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/ibo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/ibo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/iao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/iao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/edmiston.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/edmiston.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/cholesky.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/cholesky.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/boys.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/boys.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_vvo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_vvo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_pipek.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_pipek.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_orth.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_orth.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_nao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_nao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_localizer.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_localizer.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_ibo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_ibo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_iao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_iao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lo/test/test_cholesky.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lo/test/test_cholesky.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/scipy_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/scipy_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/parameters.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/parameters.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/numpy_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/numpy_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/misc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/misc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/logger.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/logger.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/linalg_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/linalg_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/exceptions.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/exceptions.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/diis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/diis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/vhf/test/test_nr_direct.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/vhf/test/test_nr_direct.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_scipy_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_scipy_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_numpy_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_numpy_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_numint_uniform_grid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_numint_uniform_grid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_misc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_misc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_linalg_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_linalg_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_einsum.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_einsum.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_diis.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_diis.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/test/test_chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/test/test_chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/gto/test/test_gridao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/gto/test/test_gridao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/gto/test/test_ecp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/gto/test/test_ecp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/dft/test/test_sparse_dot.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/dft/test/test_sparse_dot.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/dft/test/test_libdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/dft/test/test_libdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/lib/ao2mo/test/test_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/ao2mo/test/test_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/thermo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/thermo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/dispersion.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/dispersion.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/test/test_vv10_hessian.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/test/test_vv10_hessian.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/test/test_uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/test/test_uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/test/test_thermo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/test/test_thermo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/test/test_rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/test/test_rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/hessian/test/test_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/hessian/test/test_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/urpa.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/urpa.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/ugw_ac.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/ugw_ac.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/rpa.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/rpa.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/gw_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/gw_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/gw_exact.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/gw_exact.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/gw_cd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/gw_cd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/gw_ac.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/gw_ac.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/test/test_ugw.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/test/test_ugw.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gw/test/test_gw.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gw/test/test_gw.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/pp_int.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/pp_int.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/moleintor.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/moleintor.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/mole.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/mole.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/ft_ao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/ft_ao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/eval_gto.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/eval_gto.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/ecp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/ecp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/cmd_args.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/cmd_args.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_tao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_tao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_pp_int.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_pp_int.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_moleintor.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_moleintor.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_mole.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_mole.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_ft_ao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_ft_ao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_eval_gto.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_eval_gto.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_ecp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_ecp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/test/test_basis_parser.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/test/test_basis_parser.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_nwchem_ecp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_nwchem_ecp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_nwchem.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_nwchem.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_molpro.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_molpro.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_gaussian.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_gaussian.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_cp2k_pp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_cp2k_pp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_cp2k.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_cp2k.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/parse_bfd_pp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/parse_bfd_pp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/minao.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/minao.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/iglo3.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/iglo3.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/faegre_dz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/faegre_dz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dzp_dunning.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dzp_dunning.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall_tz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall_tz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall_qz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall_qz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall_dz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall_dz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/bse.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/bse.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_v4z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_v4z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_v3z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_v3z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_v2z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_v2z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_cv4z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_cv4z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_cv3z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_cv3z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_cv2z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_cv2z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_av4z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_av4z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_av3z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_av3z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_av2z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_av2z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_ae4z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_ae4z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_ae3z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_ae3z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_ae2z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_ae2z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_acv4z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_acv4z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_acv3z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_acv3z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_acv2z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_acv2z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_aae4z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_aae4z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_aae3z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_aae3z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_aae2z.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_aae2z.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_4zp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_4zp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_3zp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_3zp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/dyall_2zp.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/dyall_2zp.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/gto/basis/dyall-basis/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dyall-basis/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ucisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ucisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/uccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/uccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/uccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/uccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/tduks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/tduks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/tduhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/tduhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/tdrks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/tdrks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/tdrhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/tdrhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/sacasscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/sacasscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/roks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/roks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/rohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/rohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/rkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/rkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/mspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/mspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/mp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/mp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/mcpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/mcpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/lpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/lpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/lagrange.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/lagrange.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/dispersion.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/dispersion.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/dhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/dhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/cmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/cmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/cisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/cisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ccsd_t_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ccsd_t_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ccsd_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ccsd_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/ccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/ccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/casscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/casscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/casci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/casci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_ump2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_ump2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_ukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_ukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_ucisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_ucisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_tduks_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_tduks_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_tduhf_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_tduhf_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_tdrks_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_tdrks_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_tdrhf_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_tdrhf_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_roks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_roks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_rohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_rohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_rkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_rkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_pdft_h2co_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_pdft_h2co_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_pdft_h2co.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_pdft_h2co.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_pdft_diatomic_gradients.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_pdft_diatomic_gradients.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_mspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_mspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_mp2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_mp2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_metagga_mcpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_metagga_mcpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_mcpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_mcpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_lpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_lpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_hf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_hf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_dhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_dhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_cmspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_cmspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_cisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_cisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_ccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_ccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_ccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_ccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_casscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_casscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/grad/test/test_casci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/grad/test/test_casci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/geometric_solver.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/geometric_solver.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/berny_solver.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/berny_solver.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/test/test_geometric_solver.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/test/test_geometric_solver.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/test/test_berny_solver.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/test/test_berny_solver.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/geomopt/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/geomopt/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/spin_op.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/spin_op.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/selected_ci_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/selected_ci_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/selected_ci_spin0_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/selected_ci_spin0_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/selected_ci_spin0.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/selected_ci_spin0.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/selected_ci_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/selected_ci_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/selected_ci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/selected_ci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/fci_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/fci_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/fci_dhf_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/fci_dhf_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_spin1_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_spin1_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_spin1_cyl_sym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_spin1_cyl_sym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_spin1.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_spin1.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_spin0_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_spin0_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_spin0.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_spin0.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_nosym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_nosym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/direct_ep.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/direct_ep.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/cistring.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/cistring.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_symm_init_guess.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_symm_init_guess.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_spin_op.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_spin_op.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_spin1_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_spin1_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_spin1_cyl_sym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_spin1_cyl_sym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_spin1.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_spin1.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_spin0_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_spin0_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_spin0.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_spin0.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_selected_ci.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_selected_ci.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_ep.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_ep.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_direct_nosym.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_direct_nosym.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_dhf_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_dhf_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_cistring.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_cistring.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/fci/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/fci/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/eph_fd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/eph_fd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/test/test_uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/test/test_uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/test/test_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/test/test_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/test/test_rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/test/test_rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/eph/test/test_rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/eph/test/test_rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/xc_deriv.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/xc_deriv.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/xcfun.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/xcfun.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/ukspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/ukspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/uks_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/uks_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/sap_data.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/sap_data.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/sap.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/sap.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/roks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/roks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/rkspu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/rkspu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/rks_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/rks_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/radi.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/radi.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/r_numint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/r_numint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/numint2c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/numint2c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/numint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/numint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/libxc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/libxc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/gks_symm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/gks_symm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/gks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/gks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/gen_grid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/gen_grid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/dks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/dks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/dft_parser.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/dft_parser.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/LebedevGrid.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/LebedevGrid.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/xc/utils.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/xc/utils.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/xc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/xc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_xcfun.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_xcfun.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_xc_deriv.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_xc_deriv.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_r_numint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_r_numint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_numint2c.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_numint2c.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_numint.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_numint.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_libxc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_libxc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_he.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_he.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_grids.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_grids.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_gks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_gks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_dks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_dks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/dft/test/test_dftu.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/dft/test/test_dftu.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/r_incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/r_incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/df_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/df_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/autoaux.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/autoaux.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_df_jk.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_df_jk.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_df_hessian.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_df_hessian.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_df_grad.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_df_grad.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_df.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_df.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/hessian/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/hessian/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/hessian/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/hessian/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/hessian/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/hessian/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/hessian/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/hessian/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/hessian/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/hessian/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/uks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/uks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/sacasscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/sacasscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/roks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/roks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/rohf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/rohf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/rks.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/rks.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/rhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/rhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/mspdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/mspdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/mcpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/mcpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/lpdft.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/lpdft.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/casscf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/casscf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/casdm2_util.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/casdm2_util.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/df/grad/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/df/grad/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/data/radii.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/radii.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/data/nucprop.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/nucprop.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/data/nist.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/nist.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/data/gyro.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/gyro.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/data/elements.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/elements.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/data/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/ucisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/ucisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/gcisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/gcisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/cisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/cisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/test/test_ucisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/test/test_ucisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/test/test_gcisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/test/test_gcisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ci/test/test_cisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ci/test/test_cisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uintermediates_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uintermediates_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uintermediates.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uintermediates.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_t_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_t_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_t_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_t_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_t_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_t_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/uccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/uccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/rintermediates.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/rintermediates.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/rccsd_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/rccsd_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/rccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/rccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/rccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/rccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/qcisd_t_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/qcisd_t_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/qcisd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/qcisd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/qcisd_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/qcisd_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/qcisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/qcisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/momgfccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/momgfccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gintermediates.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gintermediates.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd_t_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd_t_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd_t_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd_t_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd_t_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd_t_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/gccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/gccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/eom_uccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/eom_uccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/eom_rccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/eom_rccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/eom_gccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/eom_gccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/dfuccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/dfuccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/dfccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/dfccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_t_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_t_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_t_rdm_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_t_rdm_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_t_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_t_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_t_lambda_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_t_lambda_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_t_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_t_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_rdm_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_rdm_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_rdm.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_rdm.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/ccd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/ccd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/bccd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/bccd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/_ccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/_ccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_uccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_uccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_uccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_uccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_uccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_uccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_rccsd_t_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_rccsd_t_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_rccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_rccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_rccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_rccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_qcisd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_qcisd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_momgfccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_momgfccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_gccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_gccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_gccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_gccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_gccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_gccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_fno_uhf.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_fno_uhf.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_fno.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_fno.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_eom_uccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_eom_uccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_eom_rccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_eom_rccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_eom_gccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_eom_gccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_dfuccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_dfuccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_dfccsd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_dfccsd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_ccsd_t.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_ccsd_t.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_ccsd_lambda.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_ccsd_lambda.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_ccd.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_ccd.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_bz.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_bz.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/cc/test/test_2e.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/cc/test/test_2e.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/semi_incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/semi_incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/r_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/r_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/nrr_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/nrr_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_semi_incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_semi_incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_r_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_r_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_nrr_outcore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_nrr_outcore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_init.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_init.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_incore.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_incore.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/test_addons.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/test_addons.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/ao2mo/test/bz_nr.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/ao2mo/test/bz_nr.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/uagf2_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/uagf2_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/uagf2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/uagf2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/ragf2_slow.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/ragf2_slow.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/ragf2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/ragf2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/mpi_helper.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/mpi_helper.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/dfuagf2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/dfuagf2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/dfragf2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/dfragf2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/chkfile.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/chkfile.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/chempot.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/chempot.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/aux_space.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/aux_space.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/_agf2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/_agf2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_uagf2_slow_beh.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_uagf2_slow_beh.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_uagf2_beh.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_uagf2_beh.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_ragf2_slow_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_ragf2_slow_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_ragf2_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_ragf2_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_dfuagf2_beh.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_dfuagf2_beh.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_dfragf2_h2o.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_dfragf2_h2o.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/agf2/test/test_c_agf2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/agf2/test/test_c_agf2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc_ip_cvs.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc_ip_cvs.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc_ip.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc_ip.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc_ee.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc_ee.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc_ea.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc_ea.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc_amplitudes.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc_amplitudes.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/uadc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/uadc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc_ip_cvs.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc_ip_cvs.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc_ip.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc_ip.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc_ee.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc_ee.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc_ea.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc_ea.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc_ao2mo.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc_ao2mo.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc_amplitudes.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc_amplitudes.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/radc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/radc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/dfadc.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/dfadc.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/__init__.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__init__.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_outcore_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_outcore_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_cvs_P.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_cvs_P.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_cvs_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_cvs_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_cvs_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_cvs_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_P.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_P.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ip_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ip_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_rohf_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_rohf_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_rohf_O2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_rohf_O2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_rohf_CN.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_rohf_CN.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_rohf_O2_high_cost.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_rohf_O2_high_cost.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_rohf_CN_high_cost.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_rohf_CN_high_cost.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_O2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_O2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_F2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_F2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_outcore_CN_high_cost.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_outcore_CN_high_cost.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_rohf_CN_high_cost.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_rohf_CN_high_cost.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_O2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_O2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_F2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_F2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_df_CN.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_df_CN.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_O2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_O2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_F2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_F2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ee_CN.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ee_CN.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ea_outcore_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ea_outcore_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ea_P.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ea_P.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ea_OH.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ea_OH.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_ea_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_ea_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_uadc/test_approx_trans_moments_CN.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_uadc/test_approx_trans_moments_CN.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ip_outcore_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ip_outcore_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ip_ea_df_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ip_ea_df_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ip_cvs_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ip_cvs_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ip_cvs_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ip_cvs_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ip_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ip_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ip_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ip_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ee_outcore_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ee_outcore_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ee_df_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ee_df_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ee_df_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ee_df_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ee_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ee_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ee_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ee_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ea_outcore_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ea_outcore_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ea_N2.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ea_N2.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_ea_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_ea_H2O.py + for f in $(find pyscf -name \*.py) + install -D -p -m 644 pyscf/adc/test/test_radc/test_approx_trans_mom_H2O.py /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/test/test_radc/test_approx_trans_mom_H2O.py ++ find pyscf -name '*.dat' + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-pbesol.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-pbesol.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-pbe.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-pbe.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-pade.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-pade.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-olyp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-olyp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-hf.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-hf.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-hf-rev.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-hf-rev.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-hcth407.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-hcth407.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-hcth120.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-hcth120.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-bp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-bp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/pseudo/gth-blyp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/pseudo/gth-blyp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-tzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-tzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-tzvp-molopt.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-tzvp-molopt.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-tzv2px-molopt.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-tzv2px-molopt.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-tzv2p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-tzv2p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-tzv2p-molopt.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-tzv2p-molopt.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-szvp-molopt-sr-q9.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-szvp-molopt-sr-q9.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-szv.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-szv.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-szv-molopt.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-szv-molopt.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-szv-molopt-sr.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-szv-molopt-sr.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-szv-molopt-sr-q9.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-szv-molopt-sr-q9.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-qzv3p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-qzv3p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-qzv2p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-qzv2p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-dzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-dzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-dzvp-molopt.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-dzvp-molopt.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-dzvp-molopt-sr.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-dzvp-molopt-sr.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-dzvp-molopt-sr-q9.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-dzvp-molopt-sr-q9.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-dzv.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-dzv.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-cc-tzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-cc-tzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-cc-qzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-cc-qzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-cc-dzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-cc-dzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-aug-tzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-aug-tzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-aug-tzv2p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-aug-tzv2p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-aug-qzv3p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-aug-qzv3p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-aug-qzv2p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-aug-qzv2p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/pbc/gto/basis/gth-aug-dzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/pbc/gto/basis/gth-aug-dzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/weigend_cfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/weigend_cfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/tzv.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/tzv.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/tzp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/tzp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/tzp-dkh.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/tzp-dkh.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/stuttgart_rsc.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/stuttgart_rsc.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/stuttgart_dz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/stuttgart_dz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/sto-6g.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/sto-6g.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/sto-3g.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/sto-3g.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS92MDFBSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS92MDFBSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS92MDFBQSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS92MDFBQSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS78MDFSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS78MDFSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS60MWBSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS60MWBSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS60MDFSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS60MDFSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS46MDFSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS46MDFSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS28MWBSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS28MWBSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS28MDFSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS28MDFSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/soecp/ECPDS10MDFSO.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/soecp/ECPDS10MDFSO.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/sbkjc.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/sbkjc.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/sarc-dkh2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/sarc-dkh2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/sap_grasp_small.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/sap_grasp_small.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/sap_grasp_large.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/sap_grasp_large.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/roos-tz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/roos-tz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/roos-dz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/roos-dz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/qzp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/qzp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/qzp-dkh.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/qzp-dkh.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31Gss.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31Gss.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-f.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-f.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-d.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-d.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-3p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-3p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-3d.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-3d.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-2p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-2p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-polarization-2d.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-polarization-2d.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31G-diffuse.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31G-diffuse.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311Gss.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311Gss.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-f.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-f.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-d.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-d.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-3p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-3p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-3d.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-3d.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-2p.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-2p.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-polarization-2d.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-polarization-2d.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311G-diffuse.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311G-diffuse.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311+Gss.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311+Gss.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311+Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311+Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311+G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311+G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311++Gss.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311++Gss.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311++Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311++Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-311++G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-311++G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31+Gss.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31+Gss.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31+Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31+Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31+G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31+G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31++Gss.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31++Gss.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31++Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31++Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/6-31++G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/6-31++G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/4-31G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/4-31G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/3-21Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/3-21Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/3-21G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/3-21G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/3-21G-polarization.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/3-21G-polarization.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/3-21G-diffuse.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/3-21G-diffuse.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/3-21++Gs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/3-21++Gs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pople-basis/3-21++G.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pople-basis/3-21++G.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pob-tzvpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pob-tzvpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pob-tzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pob-tzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pcseg-4.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pcseg-4.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pcseg-3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pcseg-3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pcseg-2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pcseg-2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pcseg-1.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pcseg-1.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pcseg-0.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pcseg-0.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pc-4.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pc-4.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pc-3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pc-3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pc-2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pc-2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pc-1.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pc-1.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/pc-0.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/pc-0.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ma-def2-tzvpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ma-def2-tzvpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ma-def2-tzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ma-def2-tzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ma-def2-svpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ma-def2-svpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ma-def2-svp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ma-def2-svp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ma-def2-qzvpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ma-def2-qzvpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ma-def2-qzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ma-def2-qzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/lanl2tz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/lanl2tz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/lanl2dz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/lanl2dz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/lanl08.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/lanl08.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/heavy-aug-cc-pvtz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/heavy-aug-cc-pvtz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/heavy-aug-cc-pvtz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/heavy-aug-cc-pvtz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/heavy-aug-cc-pvdz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/heavy-aug-cc-pvdz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/heavy-aug-cc-pvdz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/heavy-aug-cc-pvdz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVTZ-F12rev2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVTZ-F12rev2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVTZ-F12-nZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVTZ-F12-nZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVTZ-F12-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVTZ-F12-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVQZ-F12rev2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVQZ-F12rev2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVQZ-F12-nZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVQZ-F12-nZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVQZ-F12-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVQZ-F12-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVDZ-F12rev2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVDZ-F12rev2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVDZ-F12-nZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVDZ-F12-nZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pVDZ-F12-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pVDZ-F12-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pV5Z-F12rev2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pV5Z-F12rev2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pV5Z-F12.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pV5Z-F12.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pCVTZ-F12-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pCVTZ-F12-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pCVQZ-F12-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pCVQZ-F12-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/cc-pCVDZ-F12-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/cc-pCVDZ-F12-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/aug-cc-pVTZ-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/aug-cc-pVTZ-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/aug-cc-pVQZ-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/aug-cc-pVQZ-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/aug-cc-pVDZ-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/aug-cc-pVDZ-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/f12-basis/aug-cc-pV5Z-OptRI.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/f12-basis/aug-cc-pV5Z-OptRI.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/dzvp2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dzvp2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/dzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/dzp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dzp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/dzp-dkh.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dzp-dkh.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/dz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/dz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/demon_cfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/demon_cfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-universal-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-universal-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-universal-jfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-universal-jfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvppd.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvppd.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvppd-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvppd-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvpp-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvpp-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvpd.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvpd.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvpd-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvpd-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-tzvp-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-tzvp-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-svpd.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-svpd.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-svpd-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-svpd-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-svp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-svp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-svp-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-svp-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvppd.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvppd.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvppd-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvppd-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvpp-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvpp-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvpd.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvpd.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-qzvp-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-qzvp-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-mtzvpp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-mtzvpp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/def2-mtzvp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/def2-mtzvp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/crystal-cc-pvdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/crystal-cc-pvdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/crenbs.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/crenbs.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/crenbl.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/crenbl.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_cc-pV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP_aug-cc-pV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_reg/ccECP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pV6Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pV6Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_cc-pV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pV6Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pV6Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP_aug-cc-pV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP_He_core/ccECP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pV6Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pV6Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_cc-pV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pV6Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pV6Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP_aug-cc-pV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ccecp-basis/ccECP/ccECP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ccecp-basis/ccECP/ccECP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVTZ_MP2FIT.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVTZ_MP2FIT.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVTZ-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVTZ-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVTZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVTZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVTZ-DK.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVTZ-DK.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVQZ-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVQZ-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVQZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVQZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVQZ-DK.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVQZ-DK.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVDZ-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVDZ-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCVDZ-DK.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCVDZ-DK.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCV5Z-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCV5Z-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pwCV5Z-DK.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pwCV5Z-DK.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvtz_fit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvtz_fit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvtz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvtz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvtz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvtz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvtz-pp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvtz-pp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvtz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvtz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvtz-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvtz-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvqz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvqz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvqz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvqz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvqz-pp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvqz-pp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvqz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvqz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvqz-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvqz-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdz_fit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdz_fit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdz-pp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdz-pp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdz-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdz-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pvdpdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pvdpdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pv5z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pv5z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pv5z-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pv5z-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pv5z-pp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pv5z-pp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pv5z-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pv5z-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pv5z-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pv5z-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pVTZ-PP-NR.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pVTZ-PP-NR.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pVTZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pVTZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pVQZ_MP2FIT.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pVQZ_MP2FIT.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pVQZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pVQZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pVDZ-PP-NR.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pVDZ-PP-NR.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pV5Z_MP2FIT.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pV5Z_MP2FIT.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pCVTZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pCVTZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pCVQZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pCVQZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pCVDZ.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pCVDZ.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pCV6Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pCV6Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/cc-pCV5Z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/cc-pCV5Z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/bfd_vtz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/bfd_vtz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/bfd_vqz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/bfd_vqz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/bfd_vdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/bfd_vdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/bfd_v5z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/bfd_v5z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/bfd_pp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/bfd_pp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pcseg-4.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pcseg-4.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pcseg-3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pcseg-3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pcseg-2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pcseg-2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pcseg-1.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pcseg-1.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pcseg-0.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pcseg-0.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pc-4.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pc-4.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pc-3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pc-3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pc-2.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pc-2.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pc-1.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pc-1.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-pc-0.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-pc-0.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwcvtz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwcvtz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwcvqz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwcvqz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwcvdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwcvdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwcv5z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwcv5z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwcv5z-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwcv5z-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwCVTZ_MP2FIT.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwCVTZ_MP2FIT.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwCVTZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwCVTZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwCVTZ-DK.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwCVTZ-DK.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwCVQZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwCVQZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pwCVQZ-DK.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pwCVQZ-DK.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvtz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvtz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvtz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvtz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvtz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvtz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvtz-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvtz-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvqz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvqz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvqz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvqz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvqz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvqz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvqz-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvqz-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdzp-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdzp-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdzp-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdzp-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdz-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdz-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdz-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdz-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdz-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdz-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pvdpdz.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pvdpdz.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pv5z.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pv5z.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pv5z-ri.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pv5z-ri.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pv5z-jkfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pv5z-jkfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pv5z-dk.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pv5z-dk.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pVTZ-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pVTZ-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pVTZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pVTZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pVQZ_MP2FIT.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pVQZ_MP2FIT.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pVQZ-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pVQZ-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pVQZ-DK3.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pVQZ-DK3.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pVDZ-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pVDZ-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pV5Z_MP2FIT.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pV5Z_MP2FIT.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aug-cc-pV5Z-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aug-cc-pV5Z-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/atzp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/atzp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/aqzp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/aqzp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ano.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ano.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/ahlrichs_cfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/ahlrichs_cfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/adzp.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/adzp.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/DgaussA2_dft_xfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/DgaussA2_dft_xfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/DgaussA2_dft_cfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/DgaussA2_dft_cfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/DgaussA1_dft_xfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/DgaussA1_dft_xfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/DgaussA1_dft_cfit.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/DgaussA1_dft_cfit.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/gto/basis/Burkatzi-Filippi-Dolg-PP.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/gto/basis/Burkatzi-Filippi-Dolg-PP.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/data/solvents.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/solvents.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/data/nuclear_g_factor.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/nuclear_g_factor.dat + for f in $(find pyscf -name \*.dat) + install -D -p -m 644 pyscf/data/gyromagnetic_ratio.dat /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/data/gyromagnetic_ratio.dat ++ find pyscf -name '*.so' + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libpdft.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libpdft.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libdft.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libdft.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libcc.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libcc.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libpbc.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libpbc.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libmcscf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libmcscf.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libri.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libri.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libao2mo.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libao2mo.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libagf2.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libagf2.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libcvhf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libcvhf.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libcgto.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libcgto.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libfci.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libfci.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libmp.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libmp.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libnp_helper.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libnp_helper.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libxc_itrf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libxc_itrf.so + for f in $(find pyscf -name \*.so) + install -D -p -m 755 pyscf/lib/libxcfun_itrf.so /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/lib/libxcfun_itrf.so + /usr/bin/find-debuginfo -j4 --strict-build-id -m -i --build-id-seed 2.11.0-2.fc44 --unique-debug-suffix -2.11.0-2.fc44.aarch64 --unique-debug-src-base python-pyscf-2.11.0-2.fc44.aarch64 --run-dwz --dwz-low-mem-die-limit 10000000 --dwz-max-die-limit 50000000 --remove-section .gnu.build.attributes -S debugsourcefiles.list /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0 find-debuginfo: starting Extracting debug info from 15 files DWARF-compressing 15 files sepdebugcrcfix: Updated 15 CRC32s, 0 CRC32s did match. Creating .debug symlinks for symlinks to ELF files Copying sources found by 'debugedit -l' to /usr/src/debug/python-pyscf-2.11.0-2.fc44.aarch64 find-debuginfo: done + /usr/lib/rpm/check-buildroot + /usr/lib/rpm/redhat/brp-ldconfig + COMPRESS='gzip -9 -n' + COMPRESS_EXT=.gz + /usr/lib/rpm/brp-compress + /usr/lib/rpm/redhat/brp-strip-lto /usr/bin/strip + /usr/lib/rpm/check-rpaths + /usr/lib/rpm/redhat/brp-mangle-shebangs + /usr/lib/rpm/brp-remove-la-files + /usr/lib/rpm/redhat/brp-python-rpm-in-distinfo + env /usr/lib/rpm/redhat/brp-python-bytecompile '' 1 0 -j4 Bytecompiling .py files below /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib/debug/usr/lib64/python3.14 using python3.14 Bytecompiling .py files below /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14 using python3.14 /usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_cosmors.py:77: SyntaxWarning: "\[" is an invalid escape sequence. Such sequences will not work in the future. Did you mean "\\["? A raw string is also an option. /usr/lib64/python3.14/site-packages/pyscf/solvent/test/test_cosmors.py:77: SyntaxWarning: "\[" is an invalid escape sequence. Such sequences will not work in the future. Did you mean "\\["? A raw string is also an option. + /usr/lib/rpm/redhat/brp-python-hardlink + /usr/bin/add-det --brp -j4 /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__pycache__/post_scf.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__pycache__/__config__.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__pycache__/__all__.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/__pycache__/__init__.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc_ip.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc_ea.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc_ao2mo.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc_ip_cvs.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc_ip_cvs.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc_amplitudes.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc_ee.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc_ip.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc.cpython-314.opt-1.pyc: replacing with normalized version /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc_ao2mo.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/uadc.cpython-314.pyc: replacing with normalized version /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc_amplitudes.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc_ea.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/dfadc.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/adc/__pycache__/radc.cpython-314.opt-1.pyc: replacing with normalized version 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/builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/__pycache__/test_x2c.cpython-314.opt-1.pyc: rewriting with normalized contents /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr/lib64/python3.14/site-packages/pyscf/x2c/test/__pycache__/test_x2c_hess.cpython-314.opt-1.pyc: rewriting with normalized contents Scanned 297 directories and 3624 files, processed 1378 inodes, 1378 modified (648 replaced + 730 rewritten), 0 unsupported format, 0 errors + /usr/bin/linkdupes --brp /builddir/build/BUILD/python-pyscf-2.11.0-build/BUILDROOT/usr Scanned 296 directories and 3624 files, considered 3624 files, read 247 files, linked 8 files, 0 errors sum of sizes of linked files: 244590 bytes Reading /builddir/build/BUILD/python-pyscf-2.11.0-build/SPECPARTS/rpm-debuginfo.specpart Executing(%check): /bin/sh -e /var/tmp/rpm-tmp.dgM6Qn + umask 022 + cd /builddir/build/BUILD/python-pyscf-2.11.0-build + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -mbranch-protection=standard -fasynchronous-unwind-tables -fstack-clash-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd pyscf-2.11.0 + bash .github/workflows/run_tests.sh .github/workflows/run_tests.sh: line 12: python: command not found ============================= test session starts ============================== platform linux -- Python 3.14.2, pytest-8.4.2, pluggy-1.6.0 rootdir: /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0 configfile: pytest.ini plugins: cov-7.0.0 output file: /dev/null output file: /dev/null This module is deprecated and will be removed in future release. Please use cell.pbc_intor and pbc.hf.get_hcore. collected 3236 items / 251 deselected / 2985 selected pyscf/adc/test/test_radc/test_approx_trans_mom_H2O.py .. pyscf/adc/test/test_radc/test_ea_H2O.py FFF pyscf/adc/test/test_radc/test_ea_N2.py F.FF pyscf/adc/test/test_radc/test_ea_outcore_H2O.py .. pyscf/adc/test/test_radc/test_ee_H2O.py ..F pyscf/adc/test/test_radc/test_ee_N2.py ..F pyscf/adc/test/test_radc/test_ee_df_H2O.py ..F pyscf/adc/test/test_radc/test_ee_df_N2.py ..F pyscf/adc/test/test_radc/test_ee_outcore_H2O.py ..F pyscf/adc/test/test_radc/test_ip_H2O.py FFF pyscf/adc/test/test_radc/test_ip_N2.py F.FF pyscf/adc/test/test_radc/test_ip_cvs_H2O.py .F. pyscf/adc/test/test_radc/test_ip_cvs_N2.py ..F pyscf/adc/test/test_radc/test_ip_ea_df_N2.py .F... pyscf/adc/test/test_radc/test_ip_outcore_H2O.py ..F pyscf/adc/test/test_uadc/test_approx_trans_moments_CN.py .F. pyscf/adc/test/test_uadc/test_ea_N2.py ...F pyscf/adc/test/test_uadc/test_ea_OH.py ...F pyscf/adc/test/test_uadc/test_ea_P.py ..F pyscf/adc/test/test_uadc/test_ea_outcore_OH.py .. pyscf/adc/test/test_uadc/test_ee_CN.py FFF pyscf/adc/test/test_uadc/test_ee_F2.py FFF pyscf/adc/test/test_uadc/test_ee_H2O.py FFF pyscf/adc/test/test_uadc/test_ee_O2.py FFF pyscf/adc/test/test_uadc/test_ee_OH.py FFF pyscf/adc/test/test_uadc/test_ee_df_CN.py FFF pyscf/adc/test/test_uadc/test_ee_df_F2.py FFF pyscf/adc/test/test_uadc/test_ee_df_H2O.py FFF pyscf/adc/test/test_uadc/test_ee_df_O2.py FFF pyscf/adc/test/test_uadc/test_ee_df_OH.py FFF pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py FFF pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py FFF pyscf/adc/test/test_uadc/test_ee_outcore_F2.py FFF pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py FFF pyscf/adc/test/test_uadc/test_ee_outcore_O2.py FFF pyscf/adc/test/test_uadc/test_ee_outcore_OH.py FFF pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py FFF pyscf/adc/test/test_uadc/test_ee_rohf_CN.py FFF pyscf/adc/test/test_uadc/test_ee_rohf_O2.py FFF pyscf/adc/test/test_uadc/test_ee_rohf_OH.py FFF pyscf/adc/test/test_uadc/test_ip_N2.py ... pyscf/adc/test/test_uadc/test_ip_OH.py ..FF pyscf/adc/test/test_uadc/test_ip_P.py ..F pyscf/adc/test/test_uadc/test_ip_cvs_N2.py .. pyscf/adc/test/test_uadc/test_ip_cvs_OH.py ..F pyscf/adc/test/test_uadc/test_ip_cvs_P.py .. pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py .FF.F pyscf/adc/test/test_uadc/test_ip_outcore_OH.py .. pyscf/agf2/test/test_c_agf2.py .... pyscf/agf2/test/test_dfragf2_h2o.py EEE pyscf/agf2/test/test_dfuagf2_beh.py EEE pyscf/agf2/test/test_ragf2_h2o.py EEEEEEE pyscf/agf2/test/test_uagf2_beh.py EEEEEE pyscf/ao2mo/test/test_addons.py ...... pyscf/ao2mo/test/test_incore.py F. pyscf/ao2mo/test/test_init.py .... pyscf/ao2mo/test/test_nrr_outcore.py output file: /dev/null Foutput file: /dev/null F pyscf/ao2mo/test/test_outcore.py .... pyscf/ao2mo/test/test_r_outcore.py output file: /dev/null F.. pyscf/ao2mo/test/test_semi_incore.py FF pyscf/cc/test/test_2e.py F pyscf/cc/test/test_addons.py output file: /dev/null F... pyscf/cc/test/test_ccd.py output file: /dev/null .F pyscf/cc/test/test_ccsd_lambda.py output file: /dev/null FF pyscf/cc/test/test_ccsd_t.py output file: /dev/null CCSD(T) correction = -45.9602870517531 CCSD(T) correction = -45.9602870517531 .CCSD(T) correction = -0.987569101397208 .converged SCF energy = -75.9570720864205 E(CCSD) = -76.10231441007031 E_corr = -0.1452423236497694 CCSD(T) correction = -0.000995245367040057 F... pyscf/cc/test/test_dfccsd.py output file: /dev/null .FFF......FFFWARN: CCSD detected DF being used in the HF object. MO integrals are computed based on the DF 3-index tensors. It's recommended to use dfccsd.CCSD for the DF-CCSD calculations . pyscf/cc/test/test_dfuccsd.py output file: /dev/null EEEEEEEEEEEE pyscf/cc/test/test_eom_gccsd.py output file: /dev/null EEEEEEEEEEEEE pyscf/cc/test/test_eom_rccsd.py EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE pyscf/cc/test/test_eom_uccsd.py EEEEEEEEEEEEEEEEEEE pyscf/cc/test/test_fno.py does not have attributes delta_emp2 output file: /dev/null .. does not have attributes delta_emp2 output file: /dev/null .. pyscf/cc/test/test_fno_uhf.py does not have attributes delta_emp2 output file: /dev/null FF pyscf/cc/test/test_gccsd.py WARN: system HOMO 0.12399495943727 >= system LUMO -0.474582388935664 output file: /dev/null EEEEEEEEEEEEE pyscf/cc/test/test_gccsd_lambda.py converged SCF energy = -75.9747238131997 E(CCSD) = -76.1192038254041 E_corr = -0.1444800122043561 Fconverged SCF energy = -75.7263969090357 = 2.0038016 2S+1 = 3.0025333 . pyscf/cc/test/test_gccsd_t.py WARN: system HOMO 0.15521155033593 >= system LUMO -0.461751483408136 output file: /dev/null EEE pyscf/cc/test/test_h2o.py output file: /dev/null ...FF.. pyscf/cc/test/test_momgfccsd.py EEEEEEEEEEEEE pyscf/cc/test/test_qcisd.py output file: /dev/null output file: /dev/null .output file: /dev/null . pyscf/cc/test/test_rccsd.py output file: /dev/null EEEEEEEEEEEEEEEEEEEE pyscf/cc/test/test_rccsd_lambda.py output file: /dev/null FFFF pyscf/cc/test/test_rccsd_t_lambda.py output file: /dev/null FF pyscf/cc/test/test_uccsd.py output file: /dev/null EEEEEEEEEEEEEEEEEEEEEE pyscf/cc/test/test_uccsd_lambda.py converged SCF energy = -75.7263969090357 = 2.0038016 2S+1 = 3.0025333 FF pyscf/cc/test/test_uccsd_t.py WARN: system HOMO 0.155211550335933 >= system LUMO -0.461751483408137 output file: /dev/null EEE pyscf/ci/test/test_cisd.py .....converged SCF energy = -75.9839484981054 converged SCF energy = -75.9839484981056 E(RCISD_Scanner) = -76.11407702150422 E_corr = -0.1301285233985903 ....Foutput file: /dev/null ...converged SCF energy = -75.9839484981053 E(RCISD_Scanner) = -76.11407702160155 E_corr = -0.1301285234962508 converged SCF energy = -75.9797437122864 E(RCISD_Scanner) = -76.1046342897222 E_corr = -0.1248905774358073 ...converged SCF energy = -74.9630631297276 RCISD root 0 E = -74.97957319008326 RCISD root 1 E = -74.4223097377598 RCISD root 0 E = -74.99171437606927 RCISD root 1 E = -74.52184774467389 RCISD root 0 E = -74.97957052564576 RCISD root 1 E = -74.51172556789621 RCISD root 0 E = -74.96774861270049 RCISD root 1 E = -74.40678479500477 .. pyscf/ci/test/test_gcisd.py ........output file: /dev/null ..output file: /dev/null .WARN: system HOMO 0.123994959437268 >= system LUMO -0.474582388935663 output file: /dev/null ..converged SCF energy = -74.9630631297277 GCISD root 0 E = -74.98930350089036 GCISD root 1 E = -74.58506475379208 GCISD root 2 E = -74.54980774039208 GCISD root 0 E = -74.98579707120022 GCISD root 1 E = -74.58506475379208 GCISD root 2 E = -74.54980481455478 . pyscf/ci/test/test_ucisd.py ...WARN: RCISD method does not support ROHF method. ROHF object is converted to UHF object and UCISD method is called. output file: /dev/null ..F.WARN: system HOMO 0.426381156259209 >= system LUMO -0.39307763933098 output file: /dev/null .converged SCF energy = -74.9630631297288 = 1.622702e-12 2S+1 = 1 UCISD root 0 E = -74.97145934633076 UCISD root 1 E = -74.54243831698481 UCISD root 0 E = -74.98256256756451 UCISD root 1 E = -74.54979573092957 UCISD root 0 E = -74.9656249917566 UCISD root 1 E = -74.52709834846861 UCISD root 0 E = -74.96775221800993 UCISD root 1 E = -74.45880145449355 .converged SCF energy = -75.9832108869505 WARN: DF-UCISD for DFHF method is not available. Normal UCISD method is called. Fconverged SCF energy = -75.7256085746603 = 2.0037873 2S+1 = 3.0025238 WARN: DF-UCISD for DFHF method is not available. Normal UCISD method is called. F pyscf/df/test/test_addons.py . WARN: Even tempered Gaussians are generated as DF auxbasis for He .. pyscf/df/test/test_df.py .WARN: Value of _cderi is ignored. DF integrals will be saved in file /tmp/tmp6ymvpac_ . ...... pyscf/df/test/test_df_grad.py FFFFFFFFFconverged SCF energy = -75.3510315748547 = 0.75157967 2S+1 = 2.001579 converged SCF energy = -75.3510128482145 = 0.75157972 2S+1 = 2.0015791 --------------- UKS gradients --------------- x y z 0 O 0.0000000000 -0.0000000000 0.0532918595 1 H -0.0000000000 0.0675276806 -0.0266519956 2 H -0.0000000000 -0.0675276806 -0.0266519956 ---------------------------------------------- FF pyscf/df/test/test_df_hessian.py FFFFFFF pyscf/df/test/test_df_jk.py output file: /dev/null output file: /dev/null .converged SCF energy = -1.06610864931794 converged SCF energy = -1.06610864931794 ............... pyscf/df/test/test_incore.py ...... pyscf/df/test/test_outcore.py output file: /dev/null .. pyscf/dft/test/test_dftu.py converged SCF energy = -76.2512755088974 converged SCF energy = -76.2660138488192 converged SCF energy = -76.2604853864528 converged SCF energy = -76.254958825152 converged SCF energy = -76.2475930402609 converged SCF energy = -76.2420709289557 converged SCF energy = -76.2365507308819 Uresp = 5.892604, chi0 = -0.087351, chif = -0.057668 .converged SCF energy = -76.2512755088973 = 1.1413093e-12 2S+1 = 1 converged SCF energy = -76.2660138488192 = 8.8817842e-16 2S+1 = 1 converged SCF energy = -76.2604853864528 = -1.7763568e-15 2S+1 = 1 converged SCF energy = -76.254958825152 = -2.6645353e-15 2S+1 = 1 converged SCF energy = -76.2475930402608 = -6.2172489e-15 2S+1 = 1 converged SCF energy = -76.2420709289556 = -2.6645353e-15 2S+1 = 1 converged SCF energy = -76.2365507308819 = 4.4408921e-15 2S+1 = 1 Uresp = 5.892598, chi0 = -0.087351, chif = -0.057668 . pyscf/dft/test/test_dks.py output file: /dev/null ...... pyscf/dft/test/test_gks.py output file: /dev/null ......... pyscf/dft/test/test_grids.py output file: /dev/null ..WARN: n_ang 11 for atom 0 O is not the supported Lebedev angular grids. Set n_ang to 50 WARN: n_ang 11 for atom 1 H is not the supported Lebedev angular grids. Set n_ang to 50 ....... pyscf/dft/test/test_h2o.py output file: /dev/null output file: /dev/null output file: /dev/null output file: /dev/null .........WARN: B1 HOMO -0.402195769494033 > system LUMO -0.402195769494033 WARN: B1 LUMO -0.402195769494033 < system HOMO -0.402195769494033 ......................WARN: alpha-B1 HOMO -0.426962052077929 > system LUMO -0.426962052077929 ..WARN: alpha-B1 HOMO -0.402195769494033 > system LUMO -0.402195769494033 ..WARN: alpha-B1 HOMO -0.426962052077927 > system LUMO -0.426962052077927 .WARN: system HOMO -0.429615333437157 >= system LUMO -0.429615333437157 ..WARN: alpha-B1 HOMO -0.402195769494033 > system LUMO -0.402195769494033 ........ pyscf/dft/test/test_he.py output file: /dev/null converged SCF energy = -0.435670232979571 converged SCF energy = -0.435670232979571 .....converged SCF energy = -1.93633205864862 converged SCF energy = -1.93633205864862 ............ pyscf/dft/test/test_libxc.py .............Possible xc_code ['GGA_X_APBE', 'GGA_K_APBE'] matches APBE. XC parser takes GGA_X_APBE You can add prefix to APBE for a specific functional (e.g. GGA_X_APBE, HYB_MGGA_X_APBE) ... pyscf/dft/test/test_numint.py output file: /dev/null .WARN: eval_rho1 does not support complex density, eval_rho is called instead WARN: eval_rho1 does not support complex density, eval_rho is called instead .........F...... pyscf/dft/test/test_numint2c.py .... pyscf/dft/test/test_r_numint.py ....... pyscf/dft/test/test_xc_deriv.py ............... pyscf/dft/test/test_xcfun.py .........Possible xc_code ['GGA_X_APBE', 'GGA_K_APBE'] matches APBE. XC parser takes GGA_X_APBE You can add prefix to APBE for a specific functional (e.g. GGA_X_APBE, HYB_MGGA_X_APBE) .Possible xc_code ['GGA_X_APBE', 'GGA_K_APBE'] matches APBE. XC parser takes GGA_X_APBE You can add prefix to APBE for a specific functional (e.g. GGA_X_APBE, HYB_MGGA_X_APBE) . pyscf/eph/test/test_rhf.py output file: /dev/null . pyscf/eph/test/test_rks.py output file: /dev/null . pyscf/eph/test/test_uhf.py output file: /dev/null . pyscf/eph/test/test_uks.py output file: /dev/null . pyscf/fci/test/test_addons.py .............. pyscf/fci/test/test_cistring.py ......... pyscf/fci/test/test_direct_nosym.py ..... pyscf/fci/test/test_ep.py ..check 1e DM check 2e DM check 2e DM check phonon DM . pyscf/fci/test/test_rdm.py ....... pyscf/fci/test/test_selected_ci.py converged SCF energy = -1.06610864931794 WARN: This is an inefficient dialect of Selected CI using the same structure as determinant based FCI algorithm. For the efficient Selected CI programs, it is recommended to use the Dice program (https://github.com/sanshar/Dice.git). CASCI E = -1.10115033023262 E(CI) = -1.63032754115262 S^2 = 0.0000000 ............. WARN: This is an inefficient dialect of Selected CI using the same structure as determinant based FCI algorithm. For the efficient Selected CI programs, it is recommended to use the Dice program (https://github.com/sanshar/Dice.git). ..icycle 0 ci.shape (19, 19) E = -5.44934589231441 icycle 1 ci.shape (20, 20) E = -5.72512544614135 . WARN: Selected-CI space generated from HF ground state (by double exciting) is not enough for excited states. HOMO->LUMO excitations are included in the initial guess. NOTE: This may introduce excited states of different symmetry. .......... pyscf/fci/test/test_spin0.py ......... pyscf/fci/test/test_spin0_symm.py ..converged SCF energy = -14.8482663177551 . pyscf/fci/test/test_spin1.py ..... WARN: Not enough eigenvectors (len(x0)=21, nroots=36) ...... pyscf/fci/test/test_spin1_cyl_sym.py converged SCF energy = -6.75843091884253 Fconverged SCF energy = -8.02332500600904 F.converged SCF energy = 2.316702515009 CASCI E = 2.65619565854096 E(CI) = 2.21521464944096 S^2 = 2.0000000 Fconverged SCF energy = -108.677513841467 CASCI E = -108.683383594712 E(CI) = -10.0100865091894 S^2 = 5.9999999 Fconverged SCF energy = -149.528366066495 Fconverged SCF energy = 0.951830724693638 F pyscf/fci/test/test_spin1_symm.py ....converged SCF energy = -75.3005074778384 CASCI E = -75.4345364744247 E(CI) = -4.20588957821452 S^2 = 0.0000000 ...converged SCF energy = -14.8482663177551 .. pyscf/fci/test/test_spin_op.py .local spin for H1+H2 = 0 local spin for H1 = 0.75 local spin for H2 = 0.75 tot spin for HH = 0 ..F pyscf/fci/test/test_symm_init_guess.py .. pyscf/fci/test/test_uhf.py ........ pyscf/geomopt/test/test_addons.py . pyscf/geomopt/test/test_berny_solver.py ss pyscf/geomopt/test/test_geometric_solver.py sss pyscf/grad/test/test_casci.py output file: /dev/null FWARN: Mulitple states found in CASCI solver. First state is used to compute the Fock matrix and natural orbitals in active space. FFFconverged SCF energy = -1.08110417598159 CASCI E = -1.09796314384443 E(CI) = -1.59144800869320 S^2 = 0.0000000 FFFFconverged SCF energy = -108.835774209929 CASCI E = -108.929969056254 E(CI) = -5.41670929735658 S^2 = 0.0000000 FFF pyscf/grad/test/test_casscf.py output file: /dev/null FFFFFFFFFFF pyscf/grad/test/test_ccsd.py output file: /dev/null FFFconverged SCF energy = -108.835774209929 E(CCSD) = -109.0871974240834 E_corr = -0.2514232141542889 FFF pyscf/grad/test/test_ccsd_t.py output file: /dev/null FF pyscf/grad/test/test_cisd.py does not have attributes state output file: /dev/null . does not have attributes state ....converged SCF energy = -108.835774209929 E(RCISD) = -109.0670408144827 E_corr = -0.231266604553606 WARN: Unable to to identify input symmetry using original axes. Different symmetry axes will be used. --------- RCISD gradients for state 0 ---------- x y z 0 N 0.0000000000 0.0000000000 -0.1703958326 1 N 0.0000000000 0.0000000000 0.1703958326 ---------------------------------------------- . pyscf/grad/test/test_cmspdft.py F. pyscf/grad/test/test_h2o.py output file: /dev/null output file: /dev/null output file: /dev/null F...WARN: system HOMO 0.123994959437268 >= system LUMO 0.123994959437268 .WARN: Singularity detected in overlap matrix (condition number = 2.02e+06). SCF may be inaccurate and hard to converge. ......WARN: system HOMO 0.0219877438540785 >= system LUMO 0.0219877438540785 .WARN: system HOMO -0.4022041750771 >= system LUMO -0.4022041750771 . pyscf/grad/test/test_hf.py output file: /dev/null FF..... pyscf/grad/test/test_lpdft.py FFFFFFFFFFF pyscf/grad/test/test_mcpdft.py FFFF pyscf/grad/test/test_metagga_mcpdft.py FFFFF pyscf/grad/test/test_mp2.py output file: /dev/null ..WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.003 MB .converged SCF energy = -75.9843317684121 E(RMP2) = -76.110693660292 E_corr = -0.126361891879914 E(SCS-RMP2) = -76.1102537694334 E_corr = -0.125922001021286 --------------- RMP2 gradients --------------- x y z 0 O -0.0000000000 0.0063634746 0.0445078865 1 H 0.0000000000 0.0371735629 -0.0202297876 2 H 0.0000000000 -0.0435370375 -0.0242780989 ---------------------------------------------- ..converged SCF energy = -108.835774209929 E(RMP2) = -109.110014957886 E_corr = -0.274240747956732 E(SCS-RMP2) = -109.098212333674 E_corr = -0.262438123744904 WARN: Unable to to identify input symmetry using original axes. Different symmetry axes will be used. --------------- RMP2 gradients --------------- x y z 0 N 0.0000000000 0.0000000000 -0.0714308209 1 N 0.0000000000 0.0000000000 0.0714308209 ---------------------------------------------- ..F pyscf/grad/test/test_mspdft.py F.F pyscf/grad/test/test_pdft_diatomic_gradients.py FFFFFFFFFFFF pyscf/grad/test/test_pdft_h2co.py FF pyscf/grad/test/test_rhf.py output file: /dev/null FECP lanl2dz not found for H ECP lanl2dz not found for H ECP lanl2dz not found for H ECP lanl2dz not found for H ECP lanl2dz not found for H .F.F....F pyscf/grad/test/test_rks.py output file: /dev/null .F.......converged SCF energy = -99.7487247853424 --------------- RKS gradients --------------- x y z 0 H 0.0000000000 0.0000000000 -0.0026893519 1 F -0.0000000000 0.0000000000 0.0026933205 ---------------------------------------------- converged SCF energy = -99.7487249060315 --------------- RKS gradients --------------- x y z 0 H 0.0000000000 0.0000000000 -0.0026893161 1 F -0.0000000000 0.0000000000 0.0026891135 ---------------------------------------------- . pyscf/grad/test/test_rkspu.py converged SCF energy = -112.705745479498 ... pyscf/grad/test/test_rohf.py output file: /dev/null output file: /dev/null F.SCF not converged. SCF energy = -75.5783963795899 --------------- ROHF gradients --------------- x y z 0 O -0.0000000000 0.0000000000 0.0028164587 1 H -0.0000000000 0.0428113397 -0.0014082294 2 H 0.0000000000 -0.0428113397 -0.0014082294 ---------------------------------------------- .converged SCF energy = -75.9839484981057 --------------- ROHF gradients --------------- x y z 0 O 0.0000000000 0.0000000000 -0.0241134257 1 H 0.0000000000 0.0043969052 0.0120567128 2 H -0.0000000000 -0.0043969052 0.0120567128 ---------------------------------------------- . pyscf/grad/test/test_roks.py output file: /dev/null F.converged SCF energy = -75.924136449846 --------------- ROKS gradients --------------- x y z 0 O 0.0000000000 -0.0000000000 0.0516999581 1 H -0.0000000000 0.0638666247 -0.0258541336 2 H -0.0000000000 -0.0638666247 -0.0258541336 ---------------------------------------------- --------------- ROKS gradients --------------- x y z 0 O 0.0000000000 -0.0000000000 0.0516940493 1 H -0.0000000000 0.0638566407 -0.0258470246 2 H -0.0000000000 -0.0638566407 -0.0258470246 ---------------------------------------------- converged SCF energy = -75.9265400254143 --------------- ROKS gradients --------------- x y z 0 O -0.0000000000 0.0000000000 0.0395990903 1 H -0.0000000000 0.0586841786 -0.0198038246 2 H -0.0000000000 -0.0586841786 -0.0198038246 ---------------------------------------------- .converged SCF energy = -99.5748529729374 --------------- ROKS gradients --------------- x y z 0 H 0.0000000000 -0.0000000000 -0.1479101548 1 F -0.0000000000 0.0000000000 0.1479140856 ---------------------------------------------- converged SCF energy = -99.5748530769592 --------------- ROKS gradients --------------- x y z 0 H 0.0000000000 -0.0000000000 -0.1479101103 1 F -0.0000000000 0.0000000000 0.1479099091 ---------------------------------------------- .converged SCF energy = -75.3503514141293 --------------- ROKS gradients --------------- x y z 0 O 0.0000000000 0.0000000000 0.0529837148 1 H -0.0000000000 0.0673568412 -0.0264979195 2 H -0.0000000000 -0.0673568412 -0.0264979195 ---------------------------------------------- --------------- ROKS gradients --------------- x y z 0 O 0.0000000000 0.0000000000 0.0529917547 1 H -0.0000000000 0.0673570500 -0.0264958773 2 H -0.0000000000 -0.0673570500 -0.0264958773 ---------------------------------------------- . pyscf/grad/test/test_tdrhf_grad.py output file: /dev/null converged SCF energy = -108.835774209929 FFFFF pyscf/grad/test/test_tdrks_grad.py FFFFFFF pyscf/grad/test/test_tduhf_grad.py WARN: system HOMO -0.657640956457277 >= system LUMO -0.657640956457278 output file: /dev/null FF pyscf/grad/test/test_tduks_grad.py WARN: system HOMO -0.378610208755902 >= system LUMO -0.378610208755903 WARN: system HOMO -0.402961503965004 >= system LUMO -0.402961503965011 output file: /dev/null FFFFWARN: system HOMO -0.52539915738465 >= system LUMO -0.525399157384651 FF pyscf/grad/test/test_ucisd.py WARN: system HOMO 0.12399495943727 >= system LUMO -0.474582388935663 does not have attributes state output file: /dev/null .WARN: system HOMO 0.123994959437271 >= system LUMO -0.474582388935664 .. pyscf/grad/test/test_uhf.py WARN: system HOMO 0.426371235761396 >= system LUMO 0.426371235761396 output file: /dev/null output file: /dev/null FWARN: system HOMO 0.426381156259209 >= system LUMO 0.426381156259209 WARN: system HOMO -0.0656000550145197 >= system LUMO -0.0656000550145197 .converged SCF energy = -75.5805198440488 = 0.75528458 2S+1 = 2.0052776 --------------- UHF gradients --------------- x y z 0 O 0.0000000000 -0.0000000000 0.0032777494 1 H -0.0000000000 0.0431591308 -0.0016388747 2 H 0.0000000000 -0.0431591308 -0.0016388747 ---------------------------------------------- .converged SCF energy = -2.85516047724274 = -4.4408921e-16 2S+1 = 1 --------------- UHF gradients --------------- x y z 0 He 0.0000000000 0.0000000000 0.0000000000 ---------------------------------------------- .converged SCF energy = -75.9839484981056 = -2.6645353e-15 2S+1 = 1 --------------- UHF gradients --------------- x y z 0 O 0.0000000000 0.0000000000 -0.0241134240 1 H -0.0000000000 0.0043969054 0.0120567120 2 H 0.0000000000 -0.0043969054 0.0120567120 ---------------------------------------------- . pyscf/grad/test/test_uks.py WARN: system HOMO -0.40220417567342 >= system LUMO -0.40220417567342 output file: /dev/null .F.WARN: system HOMO -0.426968666148784 >= system LUMO -0.426968666148784 WARN: system HOMO -0.403556164845613 >= system LUMO -0.403556164845613 .WARN: system HOMO -0.412606810789275 >= system LUMO -0.412606810789275 .WARN: system HOMO -0.402237385896595 >= system LUMO -0.402237385896595 ...converged SCF energy = -99.5749115402541 = 0.75006089 2S+1 = 2.0000609 --------------- UKS gradients --------------- x y z 0 H 0.0000000000 0.0000000000 -0.1481125372 1 F -0.0000000000 0.0000000000 0.1481164669 ---------------------------------------------- converged SCF energy = -99.5749116439894 = 0.75006089 2S+1 = 2.0000609 --------------- UKS gradients --------------- x y z 0 H -0.0000000000 0.0000000000 -0.1481124983 1 F 0.0000000000 -0.0000000000 0.1481122971 ---------------------------------------------- . pyscf/grad/test/test_ukspu.py converged SCF energy = -112.458697679853 = 2.0271776 2S+1 = 3.018064 .. pyscf/grad/test/test_ump2.py WARN: system HOMO 0.12399495943727 >= system LUMO -0.474582388935664 output file: /dev/null FFFF pyscf/gto/test/test_basis_parser.py ................ pyscf/gto/test/test_ecp.py WARN: ECP for Cu not specified. The basis set lanl2dz include an ECP. Recommended ECP: LANL2DZ. WARN: ECP for Cu not specified. The basis set lanl2dz include an ECP. Recommended ECP: LANL2DZ. WARN: ECP for Cu not specified. The basis set lanl2dz include an ECP. Recommended ECP: LANL2DZ. ........ WARN: ECP for Cu not specified. The basis set lanl2dz include an ECP. Recommended ECP: LANL2DZ. WARN: ECP for Cu not specified. The basis set lanl2dz include an ECP. Recommended ECP: LANL2DZ. WARN: ECP for Cu not specified. The basis set lanl2dz include an ECP. Recommended ECP: LANL2DZ. ...converged SCF energy = -5.66197937620795 converged SCF energy = -5.66198034773817 WARNING! Size of vacuum may not be enough. The recommended vacuum size is 22.563481813201317 AA (42.63880104355518 Bohr) ... pyscf/gto/test/test_eval_gto.py .. pyscf/gto/test/test_ft_ao.py ....... pyscf/gto/test/test_mole.py ECP lanl2dz not found for O1 overwrite output file: /tmp/tmps_tn2i7r ..WARN: alpha-B1 HOMO -0.296386608205432 > system LUMO -0.296386608205432 .....Warning: Basis not found for atom 0 H Warning: Basis not found for atom 1 H Warning: Basis not found for atom 3 H Warning: Basis not found for atom 4 H Warning: Basis not found for atom 6 H Warning: Basis not found for atom 7 H .....ECP lanl2dz not found for O1 ......Assigning the first argument He to mol.atom ..Warning: Basis not found for atom 1 H Warning: Basis not found for atom 2 H .. WARN: Mole.unit (angstrom) is changed to Angstrom True True True . WARN: Mole.unit (angstrom) is changed to Angstrom True True True .converged SCF energy = -2.80778395753997 converged SCF energy = -2.80778395753997 converged SCF energy = -2.77188604437939 converged SCF energy = -2.8443618818369 converged SCF energy = -2.85273153347586 ..output file: /dev/null .ECP lanl2dz not found for H ECP lanl2dz not found for O1 ECP lanl08 not found for O ECP lanl2dz not found for H ...WARN: This version does not support symmetry Dooh for cartesian GTO basis. Its subgroup D2h is used output file: /dev/null output file: /dev/null WARN: len(magmom) != natm. Set magmom to zero WARN: len(magmom) != natm. Set magmom to zero .ECP lanl2dz not found for O1 #INFO: **** input file is /usr/bin/pytest **** #! /usr/bin/python3 -P import sys from pytest import console_main if __name__ == '__main__': if sys.argv[0].endswith('.exe'): sys.argv[0] = sys.argv[0][:-4] sys.exit(console_main()) #INFO: ******************** input file end ******************** System: uname_result(system='Linux', node='2e6d45c7d0094a44af6076e4b8511ec4', release='6.16.7-200.fc42.aarch64', version='#1 SMP PREEMPT_DYNAMIC Thu Sep 11 17:27:40 UTC 2025', machine='aarch64') Threads 4 Python 3.14.2 (main, Dec 5 2025, 00:00:00) [GCC 15.2.1 20251111 (Red Hat 15.2.1-4)] numpy 2.4.0 scipy 1.16.2 h5py 3.15.1 Date: Sat Jan 17 09:24:22 2026 PySCF version 2.11.0 PySCF path /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf [CONFIG] ARGPARSE = False [CONFIG] DEBUG = False [CONFIG] MAX_MEMORY = 4000 [CONFIG] TMPDIR = ./pyscftmpdir [CONFIG] UNIT = angstrom [CONFIG] VERBOSE = 3 [CONFIG] conf_file = /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/.pyscf_conf.py [CONFIG] dftd3_DFTD3PATH = ./pyscf/lib/deps/lib [CONFIG] pbc_tools_pbc_fft_engine = NUMPY+BLAS [CONFIG] scf_hf_SCF_mute_chkfile = True [INPUT] verbose = 7 [INPUT] max_memory = 4000 [INPUT] num. atoms = 3 [INPUT] num. electrons = 9 [INPUT] charge = 1 [INPUT] spin (= nelec alpha-beta = 2S) = 1 [INPUT] symmetry True subgroup None [INPUT] Mole.unit = Ang [INPUT] Symbol X Y Z unit X Y Z unit Magmom [INPUT] 1 H 0.000000000000 1.000000000000 1.000000000000 AA 0.000000000000 1.889726124565 1.889726124565 Bohr 0.0 [INPUT] 2 O 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 0.0 [INPUT] 3 H 1.000000000000 1.000000000000 0.000000000000 AA 1.889726124565 1.889726124565 0.000000000000 Bohr 0.0 [INPUT] Gaussian nuclear model for atoms dict_keys(['O', 3]) [INPUT] ---------------- BASIS SET ---------------- [INPUT] l, kappa, [nprim/nctr], expnt, c_1 c_2 ... [INPUT] O [INPUT] 0 0 [6 /1 ] 3047.5249 0.0018347 457.36951 0.0140373 103.94869 0.0688426 29.210155 0.2321844 9.286663 0.4679413 3.163927 0.362312 [INPUT] 0 0 [3 /1 ] 7.8682724 -0.1193324 1.8812885 -0.1608542 0.5442493 1.1434564 [INPUT] 0 0 [1 /1 ] 0.1687144 1 [INPUT] 1 0 [3 /1 ] 7.8682724 0.0689991 1.8812885 0.316424 0.5442493 0.7443083 [INPUT] 1 0 [1 /1 ] 0.1687144 1 [INPUT] H [INPUT] 0 0 [3 /1 ] 18.731137 0.0334946 2.8253937 0.23472695 0.6401217 0.81375733 [INPUT] 0 0 [1 /1 ] 0.1612778 1 nuclear repulsion = 6.36114150294557 point group symmetry = C2v symmetry origin: [0.18897261 0.37794522 0.18897261] symmetry axis x: [ 0.57735027 -0.57735027 0.57735027] symmetry axis y: [ 0.70710678 0. -0.70710678] symmetry axis z: [0.40824829 0.81649658 0.40824829] num. orbitals of irrep A1 = 7 num. orbitals of irrep B1 = 2 num. orbitals of irrep B2 = 4 number of shells = 9 number of NR pGTOs = 30 number of NR cGTOs = 13 basis = {'O': [[0, [3047.5249, 0.0018347], [457.36951, 0.0140373], [103.94869, 0.0688426], [29.210155, 0.2321844], [9.286663, 0.4679413], [3.163927, 0.362312]], [0, [7.8682724, -0.1193324], [1.8812885, -0.1608542], [0.5442493, 1.1434564]], [0, [0.1687144, 1.0]], [1, [7.8682724, 0.0689991], [1.8812885, 0.316424], [0.5442493, 0.7443083]], [1, [0.1687144, 1.0]]], 'H': '6-31g'} ecp = {'O1': 'lanl2dz'} bas 0, expnt(s) = [18.731137 2.8253937 0.6401217] bas 1, expnt(s) = [0.1612778] bas 2, expnt(s) = [3047.5249 457.36951 103.94869 29.210155 9.286663 3.163927] bas 3, expnt(s) = [7.8682724 1.8812885 0.5442493] bas 4, expnt(s) = [0.1687144] bas 5, expnt(s) = [7.8682724 1.8812885 0.5442493] bas 6, expnt(s) = [0.1687144] bas 7, expnt(s) = [18.731137 2.8253937 0.6401217] bas 8, expnt(s) = [0.1612778] CPU time: 629.93 ......output file: /dev/null ......ECP lanl2dz not found for O1 WARN: len(magmom) != natm. Set magmom to zero .. WARN: Mole.unit (angstrom) is changed to B New geometry 1 H 0.000000000000 1.000000000000 1.000000000000 AA 0.000000000000 1.889726124565 1.889726124565 Bohr 2 O1 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 3 H 1.000000000000 1.000000000000 0.000000000000 AA 1.889726124565 1.889726124565 0.000000000000 Bohr New geometry 1 H 0.000000000000 1.000000000000 1.000000000000 AA 0.000000000000 1.889726124565 1.889726124565 Bohr 2 O1 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 3 H 1.000000000000 1.000000000000 0.000000000000 AA 1.889726124565 1.889726124565 0.000000000000 Bohr New geometry 1 H 0.000000000000 1.000000000000 1.000000000000 AA 0.000000000000 1.889726124565 1.889726124565 Bohr 2 O1 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 3 H 1.000000000000 1.000000000000 0.000000000000 AA 1.889726124565 1.889726124565 0.000000000000 Bohr New geometry 1 H 0.000000000000 1.000000000000 1.000000000000 AA 0.000000000000 1.889726124565 1.889726124565 Bohr 2 O1 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 3 H 1.000000000000 1.000000000000 0.000000000000 AA 1.889726124565 1.889726124565 0.000000000000 Bohr WARN: Mole.unit (B) is changed to 1.0 New geometry 1 H 0.000000000000 1.000000000000 1.000000000000 AA 0.000000000000 1.889726124565 1.889726124565 Bohr 2 O1 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 3 H 1.000000000000 1.000000000000 0.000000000000 AA 1.889726124565 1.889726124565 0.000000000000 Bohr WARN: Mole.unit (1.0) is changed to Ang New geometry 1 H 0.000000000000 1.889726124565 1.889726124565 AA 0.000000000000 3.571064825864 3.571064825864 Bohr 2 O1 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 3 H 1.889726124565 1.889726124565 0.000000000000 AA 3.571064825864 3.571064825864 0.000000000000 Bohr . WARN: This version does not support symmetry Dooh for cartesian GTO basis. Its subgroup D2h is used WARN: This version does not support symmetry Dooh for cartesian GTO basis. Its subgroup D2h is used ...converged SCF energy = -76.0267656731176 ...... pyscf/gto/test/test_moleintor.py ECP LANL2DZ not found for C1 ................. pyscf/gto/test/test_pp_int.py output file: /dev/null . pyscf/gto/test/test_tao.py pass . pyscf/gw/test/test_gw.py WARN: Ground state SCF is not converged output file: /dev/null output file: /dev/null FWARN: GW QP energies may not be sorted from min to max ... pyscf/gw/test/test_ugw.py WARN: beta nocc = 3 HOMO -0.350826694589575 >= LUMO -0.350826694589574 WARN: system HOMO -0.350826694589573 >= system LUMO -0.350826694589574 WARN: GW QP energies may not be sorted from min to max output file: /dev/null .. pyscf/hessian/test/test_rhf.py output file: /dev/null ...F.. pyscf/hessian/test/test_rks.py output file: /dev/null .... pyscf/hessian/test/test_thermo.py ..converged SCF energy = -74.9630631297292 Mode 0 1 2 Irrep Freq [cm^-1] 2044.5497 4486.6573 4788.2700 Reduced mass [au] 1.0816 1.0465 1.0820 Force const [Dyne/A] 2.6639 12.4120 14.6156 Char temp [K] 2941.6518 6455.3009 6889.2545 Normal mode x y z x y z x y z 0 O 0.00 -0.00 -0.07 -0.00 -0.00 -0.05 -0.00 -0.07 0.00 1 H -0.00 -0.42 0.53 0.00 0.57 0.39 -0.00 0.54 0.42 2 H -0.00 0.42 0.53 0.00 -0.57 0.39 0.00 0.54 -0.42 temperature 298.1500 [K] pressure 101325.00 [Pa] Rotational constants [GHz] 819.20368 437.45654 285.17335 Symmetry number 2 Zero-point energy (ZPE) 0.02579 [Eh] 67705.508 [J/mol] tot elec trans rot vib Entropy [J/mol/K] 188.538 0.000 144.804 43.730 0.005 Cv [J/mol/K] 24.985 0.000 12.472 12.472 0.042 Cp [J/mol/K] 33.300 0.000 20.786 12.472 0.042 Internal energy [J/mol] 3718.434 3718.434 67706.777 Internal energy [Eh] -74.93444 -74.96306 Enthalpy [J/mol] 6197.391 3718.434 67706.777 Enthalpy [Eh] -74.93350 Gibbs free energy [J/mol] -36975.931 -9319.578 67705.379 Gibbs free energy [Eh] -74.95491 . pyscf/hessian/test/test_uhf.py WARN: system HOMO 0.123994959437269 >= system LUMO -0.474582388935664 output file: /dev/null ..WARN: system HOMO 0.123994959437268 >= system LUMO -0.474582388935664 .WARN: system HOMO 0.123994959437271 >= system LUMO -0.474582388935664 . pyscf/hessian/test/test_uks.py WARN: system HOMO -0.423203467980705 >= system LUMO -0.423203467980705 output file: /dev/null .WARN: system HOMO -0.402204175673421 >= system LUMO -0.402204175673421 .WARN: system HOMO -0.412602341413477 >= system LUMO -0.412602341413477 WARN: MGGA Hessian is sensitive to dft grids. grids.level 4 may not be dense enough. .WARN: system HOMO -0.460823893561094 >= system LUMO -0.460823893561094 .WARN: system HOMO -0.428901550855981 >= system LUMO -0.428901550855981 . pyscf/hessian/test/test_vv10_hessian.py output file: /dev/null .test_vv10_only_hessian_density_fitting F.F pyscf/lib/ao2mo/test/test_ao2mo.py . pyscf/lib/dft/test/test_libdft.py . pyscf/lib/dft/test/test_sparse_dot.py ......... pyscf/lib/gto/test/test_ecp.py ........... pyscf/lib/gto/test/test_gridao.py .................. pyscf/lib/test/test_chkfile.py .. pyscf/lib/test/test_diis.py .... pyscf/lib/test/test_einsum.py .FFFF.................... pyscf/lib/test/test_linalg_helper.py .. WARN: QR decomposition removed 1 vectors. WARN: Not enough eigenvectors (len(x0)=1, nroots=3) ....0.09751010162622811 0.08627525506097918 0.08978682056959614 .davidson 0 1 |r|= 1.6e+04 e= [40.40943951] max|de|= 40.4 lindep= 0.0303 davidson 1 2 |r|= 281 e= [21.38743586 33.69376254] max|de|= 33.7 lindep= 0.0216 davidson 2 4 |r|= 191 e= [ 7.32531567 53.84534357] max|de|= 53.8 lindep= 0.0302 davidson 3 6 |r|= 38.2 e= [-2.74962377 17.48554403] max|de|= 17.5 lindep= 0.166 davidson 4 8 |r|= 3.53 e= [-1.03060773 43.27107087] max|de|= 43.3 lindep= 0.613 davidson 5 10 |r|= 9.92 e= [-0.80144762 9.40212493] max|de|= 9.4 lindep= 0.184 davidson 6 12 |r|= 8.56 e= [12.7901674 23.94855606] max|de|= 23.9 lindep= 0.137 Old state -> New state 0 -> 1 davidson 7 14 |r|= 0.497 e= [1.07278653 1.92622984] max|de|= -11.7 lindep= 0.242 davidson 8 16 |r|= 0.202 e= [0.98024661 2.06957245] max|de|= 0.143 lindep= 0.091 davidson 9 18 |r|= 0.0618 e= [0.98643562 2.10048729] max|de|= 0.0309 lindep= 0.0201 davidson 10 20 |r|= 0.0587 e= [0.99199459 2.0897071 ] max|de|= -0.0108 lindep= 0.00619 davidson 11 22 |r|= 0.0538 e= [0.99750359 2.05302372] max|de|= -0.0367 lindep= 0.0169 davidson 12 24 |r|= 0.0535 e= [0.99970039 2.01364014] max|de|= -0.0394 lindep= 0.00837 davidson 13 26 |r|= 0.0231 e= [0.99998354 2.00128937] max|de|= -0.0124 lindep= 0.00369 davidson 14 2 |r|= 0.0231 e= [0.99998354 2.00128937] max|de|= -4.49e-13 lindep= 0.994 Old state -> New state 0 -> 1 davidson 15 4 |r|= 12.8 e= [-128.63978738 1.00006399] max|de|= -130 lindep= 0.000536 Old state -> New state 1 -> 0 0 -> 1 davidson 16 6 |r|= 0.00607 e= [1.00000839 2.00012679] max|de|= 131 lindep= 0.000816 davidson 17 8 |r|= 0.00508 e= [1.00001875 1.99988462] max|de|= -0.000242 lindep= 0.000294 davidson 18 10 |r|= 0.00509 e= [0.99999936 2.00011443] max|de|= 0.00023 lindep= 0.000548 davidson 19 12 |r|= 0.00323 e= [1.00001144 1.99997817] max|de|= -0.000136 lindep= 0.000239 davidson 20 14 |r|= 0.00327 e= [1.00000686 1.99995994] max|de|= -1.82e-05 lindep= 0.000298 davidson 21 16 |r|= 0.00213 e= [1.00001221 1.99989223] max|de|= -6.77e-05 lindep= 0.000143 davidson 22 18 |r|= 0.00141 e= [1.00003009 1.99959994] max|de|= -0.000292 lindep= 0.00011 davidson 23 20 |r|= 0.00116 e= [1.00001833 1.99970235] max|de|= 0.000102 lindep= 3.48e-05 davidson 24 22 |r|= 0.0011 e= [1.00000173 1.99989816] max|de|= 0.000196 lindep= 7.62e-05 davidson 25 24 |r|= 0.000741 e= [0.99998866 2.00003012] max|de|= 0.000132 lindep= 4.53e-05 root 0 converged |r|= 4.41e-05 e= 0.9999883396003311 max|de|= -3.23e-07 davidson 26 26 |r|= 0.00075 e= [0.99998834 2.00012249] max|de|= 9.24e-05 lindep= 0.000693 root 1 converged |r|= 0.00075 e= 2.000122487795307 max|de|= 6e-14 converged 27 2 |r|= 0.00075 e= [0.99998834 2.00012249] max|de|= 6e-14 ...... pyscf/lib/test/test_misc.py ....... pyscf/lib/test/test_numint_uniform_grid.py ....................... pyscf/lib/test/test_numpy_helper.py ..................... pyscf/lib/test/test_scipy_helper.py ...... pyscf/lib/vhf/test/test_nr_direct.py .... pyscf/lo/test/test_cholesky.py ... pyscf/lo/test/test_iao.py output file: /dev/null . pyscf/lo/test/test_ibo.py output file: /dev/null .Overwritten attributes atomic_pops of F pyscf/lo/test/test_localizer.py output file: /dev/null ...F.FF pyscf/lo/test/test_nao.py ... pyscf/lo/test/test_orth.py ...... pyscf/lo/test/test_pipek.py output file: /dev/null .F pyscf/lo/test/test_vvo.py output file: /dev/null .F. pyscf/mcpdft/test/test_cmspdft.py FFF pyscf/mcpdft/test/test_diatomic_energies.py FFFFFFFFF pyscf/mcpdft/test/test_lpdft.py ....... pyscf/mcpdft/test/test_mcpdft.py ........converged SCF energy = -0.745871793035567 CASSCF energy = -0.745871793035567 CASCI E = -0.745871793035567 E(CI) = -1.27504900395557 S^2 = 2.0000000 MC-PDFT state 0 E = -0.7470290393938751, Eot(tPBE) = -0.8376844530798241 ....... pyscf/mcpdft/test/test_mgga.py ......... pyscf/mcpdft/test/test_mspdft.py EEEE pyscf/mcpdft/test/test_otfnal.py ... pyscf/mcpdft/test/test_otpd.py .. pyscf/mcpdft/test/test_pdft_feff.py .... pyscf/mcpdft/test/test_pdft_veff.py .. pyscf/mcpdft/test/test_spingaps_atoms.py . pyscf/mcpdft/test/test_xmspdft.py ... pyscf/mcscf/test/test_addons.py output file: /dev/null ...converged SCF energy = -112.082590552836 E(RMP2) = -112.306856460794 E_corr = -0.224265907958677 E(SCS-RMP2) = -112.299038991277 E_corr = -0.216448438441427 Fconverged SCF energy = -148.766722176949 = 2.0191588 2S+1 = 3.0127455 E(UMP2) = -149.005501433402 E_corr = -0.238779256452784 E(SCS-UMP2) = -148.98466883231 E_corr = -0.217946655360828 F...................... pyscf/mcscf/test/test_apc.py converged SCF energy = -77.3553819527406 ** APC Active Space Selection ** Calculating APC entropies (N=2)... ROHF object found. APC uses summed K Transforming F and K to MO basis... Calculating initial APC entropies... Maximum entropy: 0.30982 Setting maximum virtual orbitals [np.int64(8)] to occupation 1... Calculating APC entropies (Round 1)... Maximum entropy: 0.22509 Setting maximum virtual orbitals [np.int64(8), np.int64(10)] to occupation 1... Calculating final APC entropies... Maximum entropy: 0.20153 Choosing active space with ranked orbital approach (max_size = (10, 10))... Singly occupied orbitals found, setting them to have entropy of max + 0.01... Initial active space of (15,24) has size 78564646600.0 Maximum active space size set to 19404.0 Active space of (15,24) has size 78564646600.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0.0046)... Orbital has been dropped Active space of (13,23) has size 8249287893.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 1 (occ=2, S=0.0046)... Orbital has been dropped Active space of (11,22) has size 717329382.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 22 (occ=0, S=0.0452)... Orbital has been dropped Active space of (11,21) has size 408282336.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 15 (occ=0, S=0.0517)... Orbital has been dropped Active space of (11,20) has size 225350640.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 19 (occ=0, S=0.0552)... Orbital has been dropped Active space of (11,19) has size 120187008.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 23 (occ=0, S=0.059)... Orbital has been dropped Active space of (11,18) has size 61674912.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 16 (occ=0, S=0.0655)... Orbital has been dropped Active space of (11,17) has size 30296448.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 21 (occ=0, S=0.0666)... Orbital has been dropped Active space of (11,16) has size 14158144.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 20 (occ=0, S=0.0669)... Orbital has been dropped Active space of (11,15) has size 6246240.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 17 (occ=0, S=0.069)... Orbital has been dropped Active space of (11,14) has size 2576574.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 14 (occ=0, S=0.0693)... Orbital has been dropped Active space of (11,13) has size 981552.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 13 (occ=0, S=0.0695)... Orbital has been dropped Active space of (11,12) has size 339768.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 11 (occ=0, S=0.0724)... Orbital has been dropped Active space of (11,11) has size 104544.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 12 (occ=0, S=0.0772)... Orbital has been dropped Active space of (11,10) has size 27720.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 18 (occ=0, S=0.0809)... Orbital has been dropped Final selected active space: ((6, 5),9) converged SCF energy = -77.3649789551275 = 1.0142152 2S+1 = 2.2487465 ** APC Active Space Selection ** Calculating APC entropies (N=2)... UHF object found. APC uses averaged F, summed K, summed occupation, and alpha orbitals. Transforming F and K to MO basis... Calculating initial APC entropies... Maximum entropy: 0.41627 Setting maximum virtual orbitals [np.int64(8)] to occupation 1... Calculating APC entropies (Round 1)... Maximum entropy: 0.24779 Setting maximum virtual orbitals [np.int64(8), np.int64(10)] to occupation 1... Calculating final APC entropies... Maximum entropy: 0.22345 Choosing active space with ranked orbital approach (max_size = (10, 10))... Singly occupied orbitals found, setting them to have entropy of max + 0.01... Initial active space of (15,24) has size 78564646600.0 Maximum active space size set to 19404.0 Active space of (15,24) has size 78564646600.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0.0047)... Orbital has been dropped Active space of (13,23) has size 8249287893.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 1 (occ=2, S=0.0047)... Orbital has been dropped Active space of (11,22) has size 717329382.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 22 (occ=0, S=0.0465)... Orbital has been dropped Active space of (11,21) has size 408282336.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 19 (occ=0, S=0.0564)... Orbital has been dropped Active space of (11,20) has size 225350640.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 23 (occ=0, S=0.0595)... Orbital has been dropped Active space of (11,19) has size 120187008.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 16 (occ=0, S=0.0613)... Orbital has been dropped Active space of (11,18) has size 61674912.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 15 (occ=0, S=0.062)... Orbital has been dropped Active space of (11,17) has size 30296448.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 14 (occ=0, S=0.0653)... Orbital has been dropped Active space of (11,16) has size 14158144.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 20 (occ=0, S=0.0666)... Orbital has been dropped Active space of (11,15) has size 6246240.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 13 (occ=0, S=0.0701)... Orbital has been dropped Active space of (11,14) has size 2576574.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 21 (occ=0, S=0.0702)... Orbital has been dropped Active space of (11,13) has size 981552.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 12 (occ=0, S=0.0813)... Orbital has been dropped Active space of (11,12) has size 339768.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 11 (occ=0, S=0.0817)... Orbital has been dropped Active space of (11,11) has size 104544.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 18 (occ=0, S=0.0821)... Orbital has been dropped Active space of (11,10) has size 27720.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 17 (occ=0, S=0.0835)... Orbital has been dropped Final selected active space: ((6, 5),9) .converged SCF energy = -75.9838934605484 ** APC Active Space Selection ** Calculating APC entropies (N=2)... Transforming F and K to MO basis... Calculating initial APC entropies... Maximum entropy: 0.1657 Setting maximum virtual orbitals [np.int64(8)] to occupation 1... Calculating APC entropies (Round 1)... Maximum entropy: 0.14617 Setting maximum virtual orbitals [np.int64(8), np.int64(5)] to occupation 1... Calculating final APC entropies... Maximum entropy: 0.12146 Choosing active space with ranked orbital approach (max_size = (10, 10))... Initial active space of (10,13) has size 429429.0 Maximum active space size set to 19404.0 Active space of (10,13) has size 429429.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0.0014)... Orbital has been dropped Active space of (8,12) has size 70785.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 12 (occ=0, S=0.0451)... Orbital has been dropped Active space of (8,11) has size 32670.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 7 (occ=0, S=0.0536)... Orbital has been dropped Final selected active space: ((4, 4),10) ** APC Active Space Selection ** Calculating APC entropies (N=2)... Transforming F and K to MO basis... Calculating initial APC entropies... Maximum entropy: 0.1657 Setting maximum virtual orbitals [np.int64(8)] to occupation 1... Calculating APC entropies (Round 1)... Maximum entropy: 0.14617 Setting maximum virtual orbitals [np.int64(8), np.int64(5)] to occupation 1... Calculating final APC entropies... Maximum entropy: 0.12146 Choosing active space with ranked orbital approach (max_size = 12)... Initial active space of (10,13) has size 13 Maximum active space size set to 12 Active space of (10,13) has size 13 larger than 12 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0.0014)... Orbital has been dropped Final selected active space: ((4, 4),12) ** APC Active Space Selection ** Calculating APC entropies (N=2)... Transforming F and K to MO basis... Calculating initial APC entropies... Maximum entropy: 0.1657 Setting maximum virtual orbitals [np.int64(8)] to occupation 1... Calculating APC entropies (Round 1)... Maximum entropy: 0.14617 Setting maximum virtual orbitals [np.int64(8), np.int64(5)] to occupation 1... Calculating final APC entropies... Maximum entropy: 0.12146 Choosing active space with ranked orbital approach (max_size = (8, 8))... Fixed selection of AS size (8,8)... Final selected active space: ((4, 4),8) ** APC Active Space Selection ** Calculating APC entropies (N=0)... Transforming F and K to MO basis... Calculating initial APC entropies... Calculating final APC entropies... Maximum entropy: 0.1657 Choosing active space with ranked orbital approach (max_size = (2, 2))... Initial active space of (10,13) has size 429429.0 Maximum active space size set to 3.0 Active space of (10,13) has size 429429.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0.0018)... Orbital has been dropped Active space of (8,12) has size 70785.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 12 (occ=0, S=0.0451)... Orbital has been dropped Active space of (8,11) has size 32670.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 7 (occ=0, S=0.0536)... Orbital has been dropped Active space of (8,10) has size 13860.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 10 (occ=0, S=0.0684)... Orbital has been dropped Active space of (8,9) has size 5292.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 11 (occ=0, S=0.0687)... Orbital has been dropped Active space of (8,8) has size 1764.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 1 (occ=2, S=0.0774)... Orbital has been dropped Active space of (6,7) has size 490.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 9 (occ=0, S=0.0928)... Orbital has been dropped Active space of (6,6) has size 175.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 6 (occ=0, S=0.0956)... Orbital has been dropped Active space of (6,5) has size 50.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 5 (occ=0, S=0.0964)... Orbital has been dropped Active space of (6,4) has size 10.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 8 (occ=0, S=0.1015)... Active space is not reasonable! Nactel: 6.0, Nactorbs: 3, Num OS: 0 Condition 2 not met Active space becomes unreasonable if this orbital is dropped, trying next option... Attempting to drop orbital 2 (occ=2, S=0.1317)... Orbital has been dropped Active space of (4,3) has size 6.0 larger than 3.0 Dropping lowest entropy orbital... Attempting to drop orbital 8 (occ=0, S=0.1015)... Active space is not reasonable! Nactel: 4.0, Nactorbs: 2, Num OS: 0 Condition 2 not met Active space becomes unreasonable if this orbital is dropped, trying next option... Attempting to drop orbital 3 (occ=2, S=0.1544)... Orbital has been dropped Final selected active space: ((1, 1),2) Initial active space of (10,13) has size 429429.0 Maximum active space size set to 1764.0 Active space of (10,13) has size 429429.0 larger than 1764.0 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0)... Orbital has been dropped Active space of (8,12) has size 70785.0 larger than 1764.0 Dropping lowest entropy orbital... Attempting to drop orbital 12 (occ=0, S=1)... Orbital has been dropped Active space of (8,11) has size 32670.0 larger than 1764.0 Dropping lowest entropy orbital... Attempting to drop orbital 3 (occ=2, S=2)... Orbital has been dropped Active space of (6,10) has size 4950.0 larger than 1764.0 Dropping lowest entropy orbital... Attempting to drop orbital 5 (occ=0, S=3)... Orbital has been dropped Active space of (6,9) has size 2520.0 larger than 1764.0 Dropping lowest entropy orbital... Attempting to drop orbital 6 (occ=0, S=4)... Orbital has been dropped Final selected active space: ((3, 3),8) converged SCF energy = -75.8180359048882 ** APC Active Space Selection ** Calculating APC entropies (N=2)... Transforming F and K to MO basis... Calculating initial APC entropies... Maximum entropy: 0.18606 Setting maximum virtual orbitals [np.int64(6)] to occupation 1... Calculating APC entropies (Round 1)... Maximum entropy: 0.1518 Setting maximum virtual orbitals [np.int64(6), np.int64(5)] to occupation 1... Calculating final APC entropies... Maximum entropy: 0.11265 Choosing active space with ranked orbital approach (max_size = (10, 10))... Initial active space of (10,13) has size 429429.0 Maximum active space size set to 19404.0 Active space of (10,13) has size 429429.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 0 (occ=2, S=0.0015)... Orbital has been dropped Active space of (8,12) has size 70785.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 12 (occ=0, S=0.045)... Orbital has been dropped Active space of (8,11) has size 32670.0 larger than 19404.0 Dropping lowest entropy orbital... Attempting to drop orbital 7 (occ=0, S=0.0517)... Orbital has been dropped Final selected active space: ((4, 4),10) . pyscf/mcscf/test/test_avas.py output file: /dev/null . pyscf/mcscf/test/test_c2h4.py output file: /dev/null ... pyscf/mcscf/test/test_casci.py output file: /dev/null output file: /dev/null .converged SCF energy = -54.3884142370103 WARN: Wave-function symmetry for SO3 not supported. Wfn symmetry is mapped to D2h/C2v group. WARN: mwfnsym Id 4 not found in group SO3. This might be caused by the projection from high-symmetry group to D2h symmetry. CASSCF energy = -54.3884142370103 CASCI E = -54.3884142370103 E(CI) = -9.65585922972874 S^2 = 3.7500000 .WARN: Mulitple states found in CASCI solver. First state is used to compute the Fock matrix and natural orbitals in active space. WARN: Mulitple states found in CASCI/CASSCF solver. Density matrix of the first state is generated in .analyze() function. ....WARN: Mulitple states found in CASCI solver. First state is used to compute the Fock matrix and natural orbitals in active space. WARN: Mulitple states found in CASCI/CASSCF solver. Density matrix of the first state is generated in .analyze() function. .WARN: mc1step_symm symmetrizes input orbitals ..WARN: mc1step_symm symmetrizes input orbitals ...... pyscf/mcscf/test/test_h2o.py output file: /dev/null output file: /dev/null ...WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. ..WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. ..WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. ..WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. . pyscf/mcscf/test/test_mc1step.py ...................... pyscf/mcscf/test/test_mcao2mo.py output file: /dev/null .WARN: system HOMO -0.478461393546185 >= system LUMO -0.478461393546185 output file: /dev/null . pyscf/mcscf/test/test_n2.py output file: /dev/null output file: /dev/null ...........WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. .WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. ... pyscf/mcscf/test/test_n2_df.py output file: /dev/null output file: /dev/null ................. pyscf/mcscf/test/test_newton_casscf.py WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. WARN: HOMO -0.0931797107742214 == LUMO -0.0925136982211491 WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. WARN: SO-CASSCF (Second order CASSCF) is an experimental feature. Its performance is bad for large systems. output file: /dev/null output file: /dev/null ..... pyscf/mcscf/test/test_ucasci.py WARN: system HOMO 0.12399495943727 >= system LUMO -0.474582388935663 WARN: alpha-A1 HOMO 0.12399495943727 > system LUMO -0.474582388935663 WARN: alpha-B1 HOMO -0.474582388935663 > system LUMO -0.474582388935663 WARN: beta-A1 LUMO 0.12399495943727 < system HOMO 0.12399495943727 output file: /dev/null output file: /dev/null ...WARN: Mulitple states found in UCASCI solver. Density matrix of first state is generated in .analyze() function. ... pyscf/mcscf/test/test_umc1step.py WARN: system HOMO 0.123994959437269 >= system LUMO -0.474582388935664 output file: /dev/null converged SCF energy = -2.83567987364057 = 0 2S+1 = 1 UCASSCF energy = -2.85057669964974 UCASCI E = -2.85057669964974 E(CI) = -2.85057669964974 S^2 = 0.0000000 UCASSCF energy = -2.83567987364057 UCASCI E = -2.83567987364057 E(CI) = -2.83567987364057 S^2 = 0.0000000 UCASSCF energy = -2.83567987364057 UCASCI E = -2.83567987364057 E(CI) = 0 S^2 = 0.0000000 ......... pyscf/md/test/test_NVTBerendson.py WARN: Mole.unit (angstrom) is changed to B output file: /dev/null . pyscf/md/test/test_distributions.py . pyscf/md/test/test_prop.py output file: /dev/null output file: /dev/null .. pyscf/md/test/test_velocverlet.py WARN: Mole.unit (angstrom) is changed to B output file: /dev/null output file: /dev/null .WARN: Mole.unit (angstrom) is changed to B .F pyscf/mp/test/test_dfmp2.py output file: /dev/null ..WARN: DF-HF is found. (ia|jb) is computed based on the DF 3-tensor integrals. You can switch to dfmp2.MP2 for better performance .WARN: PBC mean-field does not support direct DFMP2. Caching AO 3c integrals now. WARN: Overwritting j3c in /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscftmpdir/tmprm51jt51. output file: /dev/null .... pyscf/mp/test/test_dfmp2_native.py ...FF...FFF..FF pyscf/mp/test/test_dfump2.py WARN: system HOMO -0.476818251418643 >= system LUMO -0.476818251418643 WARN: system HOMO -0.476751467460372 >= system LUMO -0.476751467460372 output file: /dev/null ..WARN: UMP2 detected DF being used in the HF object. MO integrals are computed based on the DF 3-index tensors. It's recommended to use DF-UMP2 module. .WARN: PBC mean-field does not support direct DFMP2. Caching AO 3c integrals now. WARN: Overwritting j3c in /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscftmpdir/tmpfiac6o2h. output file: /dev/null .... pyscf/mp/test/test_dfump2_native.py ...FFFFFFF.FF pyscf/mp/test/test_f12.py . pyscf/mp/test/test_gmp2.py WARN: system HOMO 0.123994959437269 >= system LUMO -0.474582388935664 output file: /dev/null ....Overwritten attributes ao2mo of .... pyscf/mp/test/test_mp2.py output file: /dev/null converged SCF energy = -0.466581849557275 WARN: RMP2 method does not support ROHF method. ROHF object is converted to UHF object and UMP2 method is called. WARN: RMP2 method does not support ROHF method. ROHF object is converted to UHF object and UMP2 method is called. WARN: RMP2 method does not support ROHF method. ROHF object is converted to UHF object and UMP2 method is called. .WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.10108 MB ..WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.04332 MB WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.04332 MB WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.04332 MB .F.WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.10108 MB .WARN: Not enough memory for integral transformation. Available mem 0 MB, required mem 0.012288 MB ..Overwritten attributes ao2mo of WARN: DF-HF is found. (ia|jb) is computed based on the DF 3-tensor integrals. You can switch to dfmp2.MP2 for better performance .WARN: DF-HF is found. (ia|jb) is computed based on the DF 3-tensor integrals. You can switch to dfmp2.MP2 for better performance .... pyscf/mp/test/test_ump2.py WARN: system HOMO 0.100626554688217 >= system LUMO -0.476818251418643 WARN: system HOMO 0.100626554688216 >= system LUMO -0.476818251418644 output file: /dev/null ........Overwritten attributes ao2mo of WARN: UMP2 detected DF being used in the HF object. MO integrals are computed based on the DF 3-index tensors. It's recommended to use DF-UMP2 module. .WARN: UMP2 detected DF being used in the HF object. MO integrals are computed based on the DF 3-index tensors. It's recommended to use DF-UMP2 module. . pyscf/mrpt/test/test_nevpt2.py WARN: Singularity detected in overlap matrix (condition number = 11.2). SCF may be inaccurate and hard to converge. output file: /dev/null .........Warning: must be initialized before calling SCF. Initialize in .converged SCF energy = -75.5982536370609 CASSCF energy = -75.7956510716015 CASCI E = -75.7956510716015 E(CI) = -20.2461903117022 S^2 = 0.0000000 CASCI state-averaged energy = -75.7956510716015 CASCI energy for each state State 0 weight 0.5 E = -75.8131973212191 S^2 = 0.0000000 State 1 weight 0.5 E = -75.778104821984 S^2 = 0.0000000 WARN: Mulitple states found in CASCI solver. First state is used to compute the Fock matrix and natural orbitals in active space. CASCI state 0 E = -75.8131973212383 E(CI) = -20.2637365613390 S^2 = 0.0000000 CASCI state 1 E = -75.7781048220074 E(CI) = -20.2286440621080 S^2 = 0.0000000 Sr (-1)', E = -0.01606952661811 Si (+1)', E = -0.00000216319999 Sijrs (0) , E = -0.00019249170258 Sijr (+1) , E = -0.00007143417899 Srsi (-1) , E = -0.00041881987576 Srs (-2) , E = -0.03696070012973 Sij (+2) , E = -0.00000418152588 Sir (0)' , E = -0.00025525995867 Nevpt2 Energy = -0.053974577189712 Sr (-1)', E = -0.01302922228704 Si (+1)', E = -0.00000195513560 Sijrs (0) , E = -0.00019253933324 Sijr (+1) , E = -0.00006992244724 Srsi (-1) , E = -0.00042339666019 Srs (-2) , E = -0.03638413890329 Sij (+2) , E = -0.00000240828694 Sir (0)' , E = -0.00026022066879 Nevpt2 Energy = -0.050363803722339 .. pyscf/nac/test/test_cmspdft.py FFFFFF pyscf/nac/test/test_sacasscf.py FFFFFF pyscf/pbc/adc/test/test_ground_state_energy.py .MPn: -0.020957664336199788 . pyscf/pbc/adc/test/test_k_ea.py MPn: -0.020957664336199534 . pyscf/pbc/adc/test/test_k_ip.py MPn: -0.020957664336199663 .MPn: -0.021717744463064372 . pyscf/pbc/adc/test/test_k_vs_supercell_ea.py .MPn: -0.020957664336199812 .MPn: -0.020957664336199812 .F pyscf/pbc/adc/test/test_k_vs_supercell_ip.py .MPn: -0.02095766433619949 .MPn: -0.02095766433619949 .MPn: -0.020836668484091013 . pyscf/pbc/adc/test/test_kadc.py WARN: Even tempered Gaussians are generated as DF auxbasis for C output file: /dev/null MPn: -0.1146481899102742 MPn: -0.1146481899102742 MPn: -0.1146481899102742 MPn: -0.003532118672187503 . pyscf/pbc/cc/test/test_eom_kgccsd.py WARN: HOMO 1.08912682984 == LUMO 1.0891268972 does not have attributes kpts khelper output file: /dev/null EEEE pyscf/pbc/cc/test/test_eom_kgccsd_diag.py output file: /dev/null FFF pyscf/pbc/cc/test/test_eom_krccsd.py WARN: HOMO 1.08912682984 == LUMO 1.0891268972 output file: /dev/null FFFFFFoutput file: /dev/null F pyscf/pbc/cc/test/test_eom_kuccsd.py WARN: HOMO 1.08912682984 == LUMO 1.0891268972 output file: /dev/null FFF pyscf/pbc/cc/test/test_eom_kuccsd_diag.py converged SCF energy = -3.88042270970072 Fconverged SCF energy = -3.88042270970072 Fconverged SCF energy = -3.88042270970072 Fconverged SCF energy = -3.88042270970072 Fconverged SCF energy = -4.27149921464943 Fconverged SCF energy = -4.27149921464943 F pyscf/pbc/cc/test/test_kccsd_ksymm.py output file: /dev/null EE pyscf/pbc/cc/test/test_kgccsd.py output file: /dev/null output file: /dev/null Foutput file: /dev/null Foutput file: /dev/null FWARN: Singularity detected in overlap matrix (condition number = 1.63e+05). SCF may be inaccurate and hard to converge. output file: /dev/null Foutput file: /dev/null Foutput file: /dev/null FFWARN: HOMO-LUMO gap 0.0 too small for KCCSD. May cause issues in convergence. FWARN: HOMO-LUMO gap 0.0 too small for KCCSD. May cause issues in convergence. FFF pyscf/pbc/cc/test/test_krccsd.py WARN: Even tempered Gaussians are generated as DF auxbasis for He output file: /dev/null .output file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null FFFFFFoutput file: /dev/null FWARN: Non-zero imaginary part of CCSD(T) energy was found -48.89126358639411 WARN: Non-zero imaginary part of CCSD(T) energy was found -48.89126358639411 .F pyscf/pbc/cc/test/test_krccsd_gamma.py output file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null F pyscf/pbc/cc/test/test_kuccsd.py ...WARN: Even tempered Gaussians are generated as DF auxbasis for H output file: /dev/null F...F pyscf/pbc/cc/test/test_kuccsd_openshell.py F pyscf/pbc/cc/test/test_rccsd_t_shift.py WARN: Even tempered Gaussians are generated as DF auxbasis for H O converged SCF energy = -16.8936587567774 F pyscf/pbc/ci/test/test_ci.py converged SCF energy = -3.78491506863179 kshift = 0 kshift = 1 ...WARN: Even tempered Gaussians are generated as DF auxbasis for He output file: /dev/null ******** ******** nkpts = 2 CIS nocc = 2, nmo = 4 max_memory 4000 MB (current use 787 MB) using incore ERI storage CPU time for CIS integral transformation 0.07 sec, wall time 0.05 sec kshift = 0 tol 1e-07 toloose 0.000316228 max_cycle 50 max_space 20 max_memory 4000 incore True davidson 0 1 |r|= 0.0872 e= [1.44542777] max|de|= 1.45 lindep= 1 davidson 1 2 |r|= 0.0103 e= [1.42497144] max|de|= -0.0205 lindep= 0.991 davidson 2 3 |r|= 0.000343 e= [1.42492904] max|de|= -4.24e-05 lindep= 0.985 Drop eigenvector 0, norm=9.66e-16 davidson 3 4 |r|= 9.66e-16 e= [1.4249289] max|de|= -1.35e-07 lindep= 1 Linear dependency in trial subspace. |r| for each state [0.] CIS root 0 E = 1.424928903273051 kshift = 1 tol 1e-07 toloose 0.000316228 max_cycle 50 max_space 20 max_memory 4000 incore True davidson 0 1 |r|= 0.0904 e= [1.5599655] max|de|= 1.56 lindep= 1 davidson 1 2 |r|= 0.0254 e= [1.51687869] max|de|= -0.0431 lindep= 0.94 davidson 2 3 |r|= 0.000246 e= [1.51642747] max|de|= -0.000451 lindep= 0.896 root 0 converged |r|= 1.72e-15 e= 1.5164274366463608 max|de|= -3.43e-08 converged 3 4 |r|= 1.72e-15 e= [1.51642744] max|de|= -3.43e-08 CIS root 0 E = 1.516427436646361 CPU time for CIS diagonalization 0.01 sec, wall time 0.01 sec CPU time for CIS 0.07 sec, wall time 0.06 sec . pyscf/pbc/ci/test/test_cisd.py converged SCF energy = -4.58399427889068 E(RCISD) = -4.594709793601475 E_corr = -0.01071551471079388 E(UCISD) = -4.594709793601057 E_corr = -0.01071551471037581 E(GCISD) = -4.594709793601063 E_corr = -0.01071551471038205 . pyscf/pbc/df/test/test_aft.py ..... does not have attributes time_reversal_symmetry ... WARN: Even tempered Gaussians are generated as DF auxbasis for He ... WARN: AFTDF integrals are found in all-electron calculation. It often causes huge error. Recommended methods are DF or MDF. In SCF calculation, they can be initialized as mf = mf.density_fit() or mf = mf.mix_density_fit() WARN: ke_cutoff/mesh (0.884407 / [3, 3, 3]) is not enough for AFTDF to get integral accuracy 1e-08. Coulomb integral error is ~ 3.1e+03 Eh. Recommended ke_cutoff/mesh are 111.839 / [25 3 3]. WARN: mesh [3, 3, 3] of AFTDF may not be enough to get integral accuracy 1e-08 for 1D PBC system. Coulomb integral error is ~ 0.054 Eh. Recommended mesh is [25 40 40]. . pyscf/pbc/df/test/test_aft_ao2mo.py .... pyscf/pbc/df/test/test_aft_jk.py .......converged SCF energy = -5.24728359001111 . pyscf/pbc/df/test/test_band.py ......... pyscf/pbc/df/test/test_df.py ............... WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Even tempered Gaussians are generated as DF auxbasis for H converged SCF energy = -0.687018457226162 WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. converged SCF energy = -0.674692142281995 WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. WARN: Function deprecated. Call pbc.df.rsdf_builder.estimate_ke_cutoff_for_omega instead. converged SCF energy = -0.678851816639722 . pyscf/pbc/df/test/test_df_ao2mo.py ....... pyscf/pbc/df/test/test_df_jk.py ....... pyscf/pbc/df/test/test_fft.py .............. pyscf/pbc/df/test/test_ft_ao.py ......... pyscf/pbc/df/test/test_gdf_builder.py ..........WARNING! Size of vacuum may not be enough. The recommended vacuum size is 16.583937014888004 AA (31.33909902517539 Bohr) .WARNING! Size of vacuum may not be enough. The recommended vacuum size is 16.583937014888004 AA (31.33909902517539 Bohr) ....WARNING! Size of vacuum may not be enough. The recommended vacuum size is 16.583937014888004 AA (31.33909902517539 Bohr) ............. pyscf/pbc/df/test/test_incore.py .. pyscf/pbc/df/test/test_mdf.py ....... pyscf/pbc/df/test/test_mdf_ao2mo.py .... pyscf/pbc/df/test/test_mdf_builder.py output file: /dev/null .........WARN: Overwritting j3c in /tmp/tmpk8lxbl9z. .WARN: Overwritting j3c in /tmp/tmp4nmhhn13. WARN: Overwritting j3c in /tmp/tmp4nmhhn13. .WARN: Overwritting j3c in /tmp/tmp1g8acjs7. WARN: Overwritting j3c in /tmp/tmp1g8acjs7. .WARN: Overwritting j3c in /tmp/tmpbkih20_z. WARN: Overwritting j3c in /tmp/tmpbkih20_z. .WARN: Overwritting j3c in /tmp/tmpi2zaukac. .WARN: Overwritting j3c in /tmp/tmplbjllb48. .WARN: Overwritting j3c in /tmp/tmptuqcjno9. .WARN: Overwritting j3c in /tmp/tmpz8l3xenw. .WARN: Overwritting j3c in /tmp/tmp7ydozraf. ..........WARN: Overwritting j3c in /tmp/tmpfov68b2a. .WARN: Overwritting j3c in /tmp/tmpehxdxbo4. WARN: Overwritting j3c in /tmp/tmpehxdxbo4. WARN: Overwritting j3c in /tmp/tmpehxdxbo4. WARN: Overwritting j3c in /tmp/tmpehxdxbo4. .WARN: Overwritting j3c in /tmp/tmp6j_tuq9i. WARN: Overwritting j3c in /tmp/tmp6j_tuq9i. WARN: Overwritting j3c in /tmp/tmp6j_tuq9i. WARN: Overwritting j3c in /tmp/tmp6j_tuq9i. .WARN: Overwritting j3c in /tmp/tmp3l_e8g36. .WARN: Overwritting j3c in /tmp/tmpixqmf253. .WARN: Overwritting j3c in /tmp/tmp87pn9ahe. . pyscf/pbc/df/test/test_mdf_jk.py ......WARNING! Size of vacuum may not be enough. The recommended vacuum size is 7.737429290400783 AA (14.621622267045268 Bohr) .. pyscf/pbc/df/test/test_outcore.py . pyscf/pbc/df/test/test_rsdf.py ....... pyscf/pbc/df/test/test_rsdf_1.py ....... pyscf/pbc/df/test/test_rsdf_ao2mo.py ....... pyscf/pbc/df/test/test_rsdf_builder.py output file: /dev/null .......WARNING! Size of vacuum may not be enough. The recommended vacuum size is 16.583937014888004 AA (31.33909902517539 Bohr) .WARNING! Size of vacuum may not be enough. The recommended vacuum size is 16.583937014888004 AA (31.33909902517539 Bohr) ..WARN: Overwritting j3c in /tmp/tmpdlro2crr. .WARN: Overwritting j3c in /tmp/tmpms3f9js3. WARN: Overwritting j3c in /tmp/tmpms3f9js3. WARN: Overwritting j3c in /tmp/tmpms3f9js3. WARN: Overwritting j3c in /tmp/tmpms3f9js3. .WARNING! Size of vacuum may not be enough. The recommended vacuum size is 16.583937014888004 AA (31.33909902517539 Bohr) . WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. ..WARN: Overwritting j3c in /tmp/tmpmgriakzp. WARN: Overwritting j3c in /tmp/tmpmgriakzp. WARN: Overwritting j3c in /tmp/tmpmgriakzp. WARN: Overwritting j3c in /tmp/tmpmgriakzp. .WARN: Overwritting j3c in /tmp/tmpuavqlebh. .WARN: Overwritting j3c in /tmp/tmpawgar_kc. .... pyscf/pbc/df/test/test_rsdf_jk.py ...... pyscf/pbc/df/test/test_rsdf_scf.py ...... pyscf/pbc/dft/test/test_gen_grid.py ..... pyscf/pbc/dft/test/test_gks.py converged SCF energy = -0.733593654493223 = 0.75007225 2S+1 = 2.0000722 .converged SCF energy = -0.609330965763093 = 0.75009378 2S+1 = 2.0000938 . pyscf/pbc/dft/test/test_kgks.py .converged SCF energy = -1.63734569225979 .converged SCF energy = -1.53380953164042 ... pyscf/pbc/dft/test/test_krks.py converged SCF energy = -0.38460752023198 .output file: /dev/null .output file: /dev/null .output file: /dev/null .output file: /dev/null .output file: /dev/null output file: /dev/null .WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. output file: /dev/null .... pyscf/pbc/dft/test/test_krks_ksym.py WARN: k-points have lower symmetry than lattice. output file: /dev/null FWARN: k-points have lower symmetry than lattice. FFFWARN: k-points have lower symmetry than lattice. FWARN: k-points have lower symmetry than lattice. FWARN: k-points have lower symmetry than lattice. FFWARN: k-points have lower symmetry than lattice. FWARN: k-points have lower symmetry than lattice. FWARN: k-points have lower symmetry than lattice. FFWARN: k-points have lower symmetry than lattice. FWARN: k-points have lower symmetry than lattice. FFFWARN: k-points have lower symmetry than lattice. FWARN: k-points have lower symmetry than lattice. F pyscf/pbc/dft/test/test_krkspu.py WARN: Input mesh [29 29 29] has lower symmetry than the lattice. Some of the symmetry operations will be removed. Recommended mesh is [32 32 32]. WARN: k-points have lower symmetry than lattice. output file: /dev/null Foutput file: /dev/null .WARN: Input mesh [29 29 29] has lower symmetry than the lattice. Some of the symmetry operations will be removed. Recommended mesh is [32 32 32]. . pyscf/pbc/dft/test/test_kuks.py converged SCF energy = -0.384607520231979 converged SCF energy = -0.384607520231979 .F... pyscf/pbc/dft/test/test_kukspu.py WARN: Input mesh [29 29 29] has lower symmetry than the lattice. Some of the symmetry operations will be removed. Recommended mesh is [32 32 32]. WARN: k-points have lower symmetry than lattice. output file: /dev/null Foutput file: /dev/null .WARN: Input mesh [29 29 29] has lower symmetry than the lattice. Some of the symmetry operations will be removed. Recommended mesh is [32 32 32]. . pyscf/pbc/dft/test/test_multigrid.py output file: /dev/null FFFFFFFFFFFFFFFFFFFFFFFFFF pyscf/pbc/dft/test/test_multigrid2.py converged SCF energy = -2.93775322308392 --------------- RKS gradients --------------- x y z 0 H -0.0000000000 -0.0000000000 -0.0031450933 1 H 0.0000000000 0.0000000000 0.0031450207 ---------------------------------------------- .converged SCF energy = -2.93775322308303 = 3.4461323e-13 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 H -0.0000001808 -0.0000001808 -0.0031452969 1 H 0.0000001808 0.0000001808 0.0031452243 ---------------------------------------------- ..converged SCF energy = -4.55799469715288 --------------- KRKS gradients --------------- x y z 0 He 0.0037621786 0.0000000046 0.0000000046 1 He -0.0036176159 -0.0000000047 -0.0000000047 ---------------------------------------------- converged SCF energy = -4.55799470621075 --------------- RKS gradients --------------- x y z 0 He 0.0037621814 0.0000000073 0.0000000073 1 He -0.0036176180 -0.0000000067 -0.0000000067 ---------------------------------------------- converged SCF energy = -4.55799470620958 = 5.5666582e-13 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 He 0.0037621928 0.0000000185 0.0000000185 1 He -0.0036176297 -0.0000000182 -0.0000000182 ---------------------------------------------- ..converged SCF energy = -2.44168568934371 --------------- KRKS gradients --------------- x y z 0 He 0.0036862933 -0.0000000001 -0.0000000001 1 He -0.0036862933 0.0000000001 0.0000000001 ---------------------------------------------- converged SCF energy = -2.441685693302 --------------- RKS gradients --------------- x y z 0 He 0.0036862951 0.0000000014 0.0000000014 1 He -0.0036862945 -0.0000000009 -0.0000000009 ---------------------------------------------- converged SCF energy = -2.441685693302 = 2.4424907e-15 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 He 0.0036862950 0.0000000012 0.0000000012 1 He -0.0036862944 -0.0000000008 -0.0000000008 ---------------------------------------------- .converged SCF energy = -4.48411660916899 --------------- KRKS gradients --------------- x y z 0 He 0.0036526808 0.0000000060 0.0000000060 1 He -0.0036526616 -0.0000000060 -0.0000000060 ---------------------------------------------- converged SCF energy = -4.48411661696041 --------------- RKS gradients --------------- x y z 0 He 0.0036526820 0.0000000071 0.0000000071 1 He -0.0036526621 -0.0000000064 -0.0000000064 ---------------------------------------------- converged SCF energy = -4.48411661695874 = 2.0428104e-13 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 He 0.0036526930 0.0000000186 0.0000000186 1 He -0.0036526730 -0.0000000178 -0.0000000178 ---------------------------------------------- ..converged SCF energy = -2.93775322308392 ...converged SCF energy = -4.67158844488045 --------------- KRKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.2523233888 1 He -0.0000000000 0.0000000000 -0.2523362440 ---------------------------------------------- converged SCF energy = -4.67158844084003 --------------- RKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.2523233865 1 He -0.0000000000 -0.0000000000 -0.2523362590 ---------------------------------------------- converged SCF energy = -4.67158844082007 = 2.1551649e-12 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.2523231315 1 He -0.0000000000 -0.0000000000 -0.2523360064 ---------------------------------------------- ..converged SCF energy = -2.67072142062722 --------------- KRKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.3233010095 1 He -0.0000000000 0.0000000000 -0.3233010095 ---------------------------------------------- converged SCF energy = -2.67072142172161 --------------- RKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.3233010109 1 He -0.0000000000 -0.0000000000 -0.3233010156 ---------------------------------------------- converged SCF energy = -2.67072142172162 = 1.110223e-15 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.3233010140 1 He -0.0000000000 -0.0000000000 -0.3233010186 ---------------------------------------------- .converged SCF energy = -4.58629177310795 --------------- KRKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.2492605646 1 He -0.0000000000 0.0000000000 -0.2492605543 ---------------------------------------------- converged SCF energy = -4.5862917754713 --------------- RKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.2492605652 1 He -0.0000000000 -0.0000000000 -0.2492605661 ---------------------------------------------- converged SCF energy = -4.58629177545762 = 4.3520743e-14 2S+1 = 1 --------------- UKS gradients --------------- x y z 0 He -0.0000000000 -0.0000000000 0.2492601165 1 He -0.0000000000 -0.0000000000 -0.2492601173 ---------------------------------------------- .. pyscf/pbc/dft/test/test_numint.py ...output file: /dev/null .output file: /dev/null .output file: /dev/null ....output file: /dev/null .output file: /dev/null . pyscf/pbc/dft/test/test_rks.py output file: /dev/null .. WARN: Even tempered Gaussians are generated as DF auxbasis for He converged SCF energy = -4.71769943875991 .converged SCF energy = -0.62526956972484 WARN: Even tempered Gaussians are generated as DF auxbasis for H converged SCF energy = -0.635068828433849 ..WARNING! Size of vacuum may not be enough. The recommended vacuum size is 7.737429290400783 AA (14.621622267045268 Bohr) ... pyscf/pbc/dft/test/test_sampling.py . pyscf/pbc/dft/test/test_uks.py output file: /dev/null ... pyscf/pbc/grad/test/test_krhf.py WARN: HOMO 1.62856504857 == LUMO 1.62856579948 output file: /dev/null . pyscf/pbc/grad/test/test_krks.py output file: /dev/null ... pyscf/pbc/grad/test/test_krks_stress.py ..........SCF not converged. SCF energy = -15.9975114226978 .... pyscf/pbc/grad/test/test_krkspu.py SCF not converged. SCF energy = -15.9975114226978 .converged SCF energy = -15.939464667887 --------------- KRKSpU_Scanner gradients --------------- x y z 0 C -0.3271693152 0.2249694409 0.0589441872 1 O 0.3271673745 -0.2249705139 -0.0589429173 ---------------------------------------------- converged SCF energy = -15.939888970092 converged SCF energy = -15.9390386916941 .. pyscf/pbc/grad/test/test_kuhf.py output file: /dev/null . pyscf/pbc/grad/test/test_kuks.py output file: /dev/null ... pyscf/pbc/grad/test/test_kuks_stress.py ....SCF not converged. SCF energy = -15.9975114226978 .. pyscf/pbc/grad/test/test_kukspu.py SCF not converged. SCF energy = -15.9744304628158 .converged SCF energy = -15.9394646678869 --------------- KUKSpU_Scanner gradients --------------- x y z 0 C -0.3271693152 0.2249694409 0.0589441872 1 O 0.3271673745 -0.2249705139 -0.0589429173 ---------------------------------------------- converged SCF energy = -15.939888970092 converged SCF energy = -15.9390386916941 . pyscf/pbc/grad/test/test_rks_stress.py .................. pyscf/pbc/grad/test/test_uks_stress.py ..... pyscf/pbc/gto/pseudo/test/test_pp.py .... pyscf/pbc/gto/test/test_cell.py WARNING! Lattice are not in right-handed coordinate system. This can cause wrong value for some integrals. It's recommended to resort the lattice vectors to a = [[0.78805738 0.57132576 0.35198079] [0.00021614 0.17449465 0.74978186] [1.36121601 0.27732844 0.65301513]] ..........output file: /dev/null output file: /dev/null .output file: /dev/null .output file: /dev/null .WARNING! Size of vacuum may not be enough. The recommended vacuum size is 3.8100759186240003 AA (7.2 Bohr) WARNING! Size of vacuum may not be enough. The recommended vacuum size is 17.478082236866125 AA (33.02878861030247 Bohr) output file: /dev/null .output file: /dev/null .... WARN: Mole.unit (angstrom) is changed to Angstrom . WARN: Mole.unit (angstrom) is changed to Angstrom ..converged SCF energy = -2.26197131934003 converged SCF energy = -2.26197131934002 converged SCF energy = -2.28740867221804 converged SCF energy = -2.28361416891689 converged SCF energy = -2.26197131934003 converged SCF energy = -2.26197131934003 converged SCF energy = -2.28740867221805 converged SCF energy = -1.88649138906637 = 0.75 2S+1 = 2 converged SCF energy = -1.88649138906637 = 0.75 2S+1 = 2 converged SCF energy = -1.87317900517165 = 0.75 2S+1 = 2 converged SCF energy = -1.8756882235292 = 0.75 2S+1 = 2 converged SCF energy = -1.88649138906637 Makov-Payne correction for charged 3D PBC systems Corrections (AU) Monopole Dipole Quadrupole total SC 0.18767915 -0.00000000 -0.12536368 0.06231546 BCC 0.24072493 -0.00000000 -0.12536368 0.11536124 FCC 0.30327557 -0.00000000 -0.12536368 0.17791188 converged SCF energy = -1.88649138906637 Makov-Payne correction for charged 3D PBC systems Corrections (AU) Monopole Dipole Quadrupole total SC 0.18767915 -0.00000000 -0.12536368 0.06231546 BCC 0.24072493 -0.00000000 -0.12536368 0.11536124 FCC 0.30327557 -0.00000000 -0.12536368 0.17791188 converged SCF energy = -1.87317900517165 Makov-Payne correction for charged 3D PBC systems Corrections (AU) Monopole Dipole Quadrupole total SC 0.18767915 -0.00000000 -0.12536368 0.06231546 BCC 0.24072493 -0.00000000 -0.12536368 0.11536124 FCC 0.30327557 -0.00000000 -0.12536368 0.17791188 WARN: k-points have lower symmetry than lattice. ....... WARN: Mole.unit (angstrom) is changed to Bohr WARN: Mole.unit (angstrom) is changed to Bohr WARN: Mole.unit (angstrom) is changed to Bohr WARN: Mole.unit (AU) is changed to Ang WARN: Mole.unit (Bohr) is changed to Ang WARN: Mole.unit (AU) is changed to Ang WARN: Mole.unit (1.5) is changed to Ang WARN: Mole.unit (1.5) is changed to Ang . pyscf/pbc/gto/test/test_rcut.py ..1e-12 error = 9.324609316056656e-15 3.774758283725532e-15 1.0000000000000001e-11 error = 5.2576472495443466e-14 1.8456374746891044e-14 1e-10 error = 1.47037063624519e-13 5.34934656525202e-14 1e-09 error = 9.050720398245679e-12 3.857220548707e-12 1e-08 error = 1.4113730824444315e-10 6.642922139396765e-11 1.0000000000000001e-07 error = 4.0797610266743917e-10 1.9664337439720546e-10 1e-06 error = 3.1154783234779107e-09 1.6830823438717744e-09 1e-05 error = 9.64539405202948e-08 6.276874331430589e-08 0.0001 error = 2.909945090615501e-07 1.9614669579273509e-07 . pyscf/pbc/gw/test/test_krgw.py WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: File /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscftmpdir/tmprjdder7z (specified by ._cderi) is overwritten by GDF initialization. WARN: GW QP energies may not be sorted from min to max output file: /dev/null output file: /dev/null F pyscf/pbc/gw/test/test_kugw.py WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: GW QP energies may not be sorted from min to max output file: /dev/null F pyscf/pbc/lib/test/test_kpts.py ....... pyscf/pbc/lib/test/test_kpts_ksymm.py SCF not converged. SCF energy = -7.84676511575938 WARN: k-points have lower symmetry than lattice. WARN: k-points have lower symmetry than lattice. ... pyscf/pbc/mp/test/test_dm.py WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. WARN: The coulG kernel for range-separated Coulomb potential for PBC 1 is inaccurate. output file: /dev/null . pyscf/pbc/mp/test/test_kpoint.py output file: /dev/null .WARN: Even tempered Gaussians are generated as DF auxbasis for Be . ******** ******** method = KRHF initial guess = minao damping factor = 0 level_shift factor = 0 DIIS = diis_start_cycle = 1 diis_space = 8 diis_damp = 0 SCF conv_tol = 1e-12 SCF conv_tol_grad = None SCF max_cycles = 50 direct_scf = True direct_scf_tol = 1e-13 max_memory 4000 MB (current use 1293 MB) ******** PBC SCF flags ******** N kpts = 2 Exchange divergence treatment (exxdiv) = ewald madelung (= occupied orbital energy shift) = 0.41483464269504156 Total energy shift due to Ewald probe charge = -1/2 * Nelec*madelung = -0.622251964043 DF object = Set gradient conv threshold to 1e-06 init E= -2.92107011113114 HOMO = 0.288176773721 LUMO = 0.654634512885 cycle= 1 E= -2.19665216744709 delta_E= 0.724 |g|= 0.0549 |ddm|= 3.37 HOMO = 0.0590582470643 LUMO = 0.690863174419 cycle= 2 E= -2.19827677284868 delta_E= -0.00162 |g|= 0.0298 |ddm|= 0.304 HOMO = 0.0576906137065 LUMO = 0.693153271344 cycle= 3 E= -2.19898602523908 delta_E= -0.000709 |g|= 0.005 |ddm|= 0.343 HOMO = 0.0588528045854 LUMO = 0.691391293014 cycle= 4 E= -2.19900462505027 delta_E= -1.86e-05 |g|= 0.00113 |ddm|= 0.0506 HOMO = 0.0582038345518 LUMO = 0.692429654339 cycle= 5 E= -2.1990056323949 delta_E= -1.01e-06 |g|= 9.91e-05 |ddm|= 0.0128 HOMO = 0.0584966256208 LUMO = 0.691966285661 cycle= 6 E= -2.19900563717585 delta_E= -4.78e-09 |g|= 2.03e-05 |ddm|= 0.00063 HOMO = 0.0584676223672 LUMO = 0.692012095961 cycle= 7 E= -2.19900563736488 delta_E= -1.89e-10 |g|= 1.19e-06 |ddm|= 0.000107 HOMO = 0.0584680209568 LUMO = 0.692011432193 cycle= 8 E= -2.19900563736542 delta_E= -5.32e-13 |g|= 5.81e-08 |ddm|= 5.93e-06 HOMO = 0.0584679853388 LUMO = 0.692011497729 Extra cycle E= -2.19900563736542 delta_E= -1.78e-15 |g|= 2.75e-08 |ddm|= 3.47e-07 converged SCF energy = -2.19900563736542 ******** ******** nkpts = 2 nocc = 2 nmo = 5 with_df_ints = False max_memory 4000 MB (current use 1293 MB) E(KMP2) = -2.20062621657753 E_corr = -0.00162057921211041 E(SCS-KMP2) = -2.20078176770685 E_corr = -0.00177613034143105 E_corr(same-spin) = -0.000194497745886286 E_corr(oppo-spin) = -0.00142608146622413 . pyscf/pbc/mp/test/test_kpoint_stagger.py WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Even tempered Gaussians are generated as DF auxbasis for H WARN: Even tempered Gaussians are generated as DF auxbasis for H output file: /dev/null . pyscf/pbc/mp/test/test_ksym.py EE pyscf/pbc/mp/test/test_mask.py ........ pyscf/pbc/mp/test/test_mask_uhf.py ......... pyscf/pbc/mp/test/test_padding.py output file: /dev/null . pyscf/pbc/mp/test/test_scs.py WARN: Even tempered Gaussians are generated as DF auxbasis for Be WARN: Even tempered Gaussians are generated as DF auxbasis for Be output file: /dev/null .WARN: Even tempered Gaussians are generated as DF auxbasis for Be output file: /dev/null FWARN: Even tempered Gaussians are generated as DF auxbasis for Be output file: /dev/null . pyscf/pbc/scf/test/test_addons.py WARN: WARNING! HOMO is greater than LUMO! This may lead to incorrect canonical occupation. WARN: WARNING! HOMO is greater than LUMO! This may lead to incorrect canonical occupation. output file: /dev/null .....FF WARN: Even tempered Gaussians are generated as DF auxbasis for He converged SCF energy = -5.567693501908 converged SCF energy = -5.56769351503205 converged SCF energy = -5.56785858136944 ..F.F pyscf/pbc/scf/test/test_band.py converged SCF energy = -4.57320061776639 .converged SCF energy = -3.33089753003818 . pyscf/pbc/scf/test/test_hf.py output file: /dev/null .output file: /dev/null .............converged SCF energy = -5.66197937620795 converged SCF energy = -5.66198034773817 ...WARNING! Size of vacuum may not be enough. The recommended vacuum size is 8.610449385543093 AA (16.27139114810597 Bohr) ....... pyscf/pbc/scf/test/test_khf.py output file: /dev/null F.WARN: Occupied band above Fermi level: k=1, mo_e=[2 3 4 5], mo_occ=[2. 2. 0. 0.] WARN: Occupied band above Fermi level: k=1, mo_e=[2 3 4 5], mo_occ=[2. 2. 0. 0.] .output file: /dev/null ........Warning: cell.build() is not called in input output file: /dev/null . pyscf/pbc/scf/test/test_khf_ksym.py WARN: k-points have lower symmetry than lattice. output file: /dev/null EEEEEEEEEEEEEEEEEEE pyscf/pbc/scf/test/test_mulliken_meta.py output file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null Foutput file: /dev/null F pyscf/pbc/scf/test/test_newton.py output file: /dev/null ................... pyscf/pbc/scf/test/test_rohf.py output file: /dev/null F.WARN: Problematic nelec (3, 1) and number of k-points 1 found in KRHF method. .WARN: Problematic nelec (3, 1) and number of k-points 1 found in KRHF method. .F.Warning: cell.build() is not called in input WARN: Problematic nelec (1, 0) and number of k-points 1 found in KRHF method. Warning: cell.build() is not called in input output file: /dev/null output file: /dev/null .. pyscf/pbc/scf/test/test_rsjk.py FFFF pyscf/pbc/scf/test/test_scfint.py .. pyscf/pbc/scf/test/test_stability.py output file: /dev/null ..... pyscf/pbc/scf/test/test_uhf.py WARN: system HOMO 2.63429280918515 >= system LUMO 0.153343377912651 WARN: system HOMO 3.34131318984706 >= system LUMO 0.408215936149253 WARN: system HOMO 3.30858464277637 >= system LUMO 0.468305596121155 WARN: system HOMO 3.29521895819993 >= system LUMO 0.455845687423706 WARN: system HOMO 3.29427528140414 >= system LUMO 0.457266018358502 WARN: system HOMO 3.29426084404913 >= system LUMO 0.457216787559793 WARN: system HOMO 3.29426169491203 >= system LUMO 0.457221339816749 WARN: system HOMO 3.29426176865997 >= system LUMO 0.457221297572424 output file: /dev/null .WARN: system HOMO 3.36070922822746 >= system LUMO 0.420162103931824 .FWARN: system HOMO 1.11042252659421 >= system LUMO -0.6672555393163 WARN: system HOMO 3.08543247056778 >= system LUMO 0.189547323119079 .Warning: cell.build() is not called in input Warning: cell.build() is not called in input output file: /dev/null output file: /dev/null ... pyscf/pbc/symm/test/test_basis.py ...... pyscf/pbc/symm/test/test_spg.py WARNING! Size of vacuum may not be enough. The recommended vacuum size is 24.463878104992176 AA (46.23002956317894 Bohr) .. pyscf/pbc/tdscf/test/test_krhf.py output file: /dev/null FFFFFoutput file: /dev/null FFFF pyscf/pbc/tdscf/test/test_krks.py output file: /dev/null FFFFoutput file: /dev/null FFFF pyscf/pbc/tdscf/test/test_kuhf.py WARN: system HOMO 0.427552128774932 >= system LUMO -0.392409139203598 output file: /dev/null output file: /dev/null FF pyscf/pbc/tdscf/test/test_kuks.py output file: /dev/null FFoutput file: /dev/null FF pyscf/pbc/tdscf/test/test_rhf.py output file: /dev/null FFFFoutput file: /dev/null FFFFoutput file: /dev/null output file: /dev/null FFFF pyscf/pbc/tdscf/test/test_rks.py output file: /dev/null FFFFFFFoutput file: /dev/null FFFFoutput file: /dev/null output file: /dev/null FFFFoutput file: /dev/null FFFFoutput file: /dev/null output file: /dev/null FFFF pyscf/pbc/tdscf/test/test_uhf.py output file: /dev/null FFWARN: system HOMO 0.594505807524159 >= system LUMO -0.119761480517414 WARN: system HOMO 0.427552128774933 >= system LUMO -0.392409139203598 output file: /dev/null output file: /dev/null FF pyscf/pbc/tdscf/test/test_uks.py output file: /dev/null FFFFFWARN: system HOMO 0.351086049512679 >= system LUMO -0.164942853521484 WARN: system HOMO 0.372224369917042 >= system LUMO -0.109398145082476 WARN: system HOMO 0.369788985313156 >= system LUMO -0.119864040275761 WARN: system HOMO 0.371281163613063 >= system LUMO -0.117223123560062 WARN: system HOMO 0.371421958814991 >= system LUMO -0.11723300096601 WARN: system HOMO 0.371422609067518 >= system LUMO -0.117231178820792 WARN: system HOMO 0.237008333008519 >= system LUMO -0.316466163790798 WARN: system HOMO 0.385331124060037 >= system LUMO -0.0783033012630696 WARN: system HOMO 0.370586778103576 >= system LUMO -0.11873573149721 WARN: system HOMO 0.370145454518539 >= system LUMO -0.118489586217734 WARN: system HOMO 0.370145883993405 >= system LUMO -0.118500873852523 WARN: system HOMO 0.370147407363317 >= system LUMO -0.118500055354112 output file: /dev/null output file: /dev/null FFoutput file: /dev/null FFWARN: system HOMO 0.401537400973323 >= system LUMO -0.167674079336167 WARN: system HOMO 0.437539778388623 >= system LUMO -0.0282605109697976 WARN: system HOMO 0.437070095840284 >= system LUMO -0.0372085070177085 WARN: system HOMO 0.439047499952029 >= system LUMO -0.0335878500451808 WARN: system HOMO 0.439142363904091 >= system LUMO -0.0339808473564027 WARN: system HOMO 0.439143560087996 >= system LUMO -0.0339786693013186 WARN: system HOMO 0.439143624292945 >= system LUMO -0.0339781906975345 WARN: system HOMO 0.275718151426506 >= system LUMO -0.347810183146953 WARN: system HOMO 0.448255108755831 >= system LUMO 0.000187108257607713 WARN: system HOMO 0.437265796382037 >= system LUMO -0.0355777686366815 WARN: system HOMO 0.437730027972803 >= system LUMO -0.0352559539014687 WARN: system HOMO 0.437836465438019 >= system LUMO -0.0352618010562597 WARN: system HOMO 0.437840285681184 >= system LUMO -0.0352584746575123 WARN: system HOMO 0.437840445140679 >= system LUMO -0.0352576925740627 output file: /dev/null output file: /dev/null FF pyscf/pbc/tools/test/test_k2gamma.py WARNING! Lattice are not in right-handed coordinate system. This can cause wrong value for some integrals. It's recommended to resort the lattice vectors to a = [[ 3.316469 3.316469 -3.316469] [-3.316469 3.316469 3.316469] [ 3.316469 -3.316469 3.316469]] output file: /dev/null .WARNING! Lattice are not in right-handed coordinate system. This can cause wrong value for some integrals. It's recommended to resort the lattice vectors to a = [[ 3.316469 3.316469 -3.316469] [-3.316469 3.316469 3.316469] [ 3.316469 -3.316469 3.316469]] output file: /dev/null F WARN: k-points have lower symmetry than lattice. F. pyscf/pbc/tools/test/test_pbc.py .output file: /dev/null ..output file: /dev/null ............ pyscf/pbc/x2c/test/test_x2c.py converged SCF energy = -4.7579614486112 .... WARN: Even tempered Gaussians are generated as DF auxbasis for He . pyscf/qmmm/pbc/test/test_qmmm.py F pyscf/qmmm/test/test_grad_mm.py output file: /dev/null ... pyscf/qmmm/test/test_itrf.py output file: /dev/null ..converged SCF energy = -76.1041683968315 --------------- QMMMRHF gradients --------------- x y z 0 O 0.0123367338 0.0044519147 -0.0967363076 1 H -0.0065903497 -0.0981918975 0.0578784211 2 H -0.1930064008 0.2046235340 -0.0479455541 ---------------------------------------------- converged SCF energy = -76.1043507936664 converged SCF energy = -76.1039851836305 E(CCSD) = -76.32749086071729 E_corr = -0.2233224638857711 F... pyscf/scf/test/test_addons.py WARN: system HOMO 0.123994959437268 >= system LUMO -0.474582388935664 WARN: alpha-A1 HOMO 0.123994959437267 > system LUMO -0.474582388935664 WARN: alpha-B1 HOMO -0.474582388935664 > system LUMO -0.474582388935664 WARN: beta-A1 LUMO 0.123994959437267 < system HOMO 0.123994959437267 output file: /dev/null .Overwritten attributes get_fock of Overwritten attributes get_fock of WARN: beta nocc = 5 HOMO 0.553920869506769 >= LUMO 0.55445254924954 .Overwritten attributes get_occ of WARN: set charge = 6 WARN: set charge = 6 output file: /dev/null .Overwritten attributes get_occ of WARN: system HOMO -0.0370208892610367 >= system LUMO -0.672294795662078 output file: /dev/null ..WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] WARN: fraction occ = 1 for orbitals [5 6] Overwritten attributes get_occ get_grad of WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: fraction occ = 0.5 for alpha orbitals [7 8] 1 for beta orbitals [5 6] WARN: Invalid number of electrons 13 for RHF method. WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] WARN: fraction occ = 1 for alpha orbitals [5 6] 0.5 for beta orbitals [5 6] output file: /dev/null ..Overwritten attributes get_occ of Overwritten attributes get_occ of .FFF....WARN: Invalid number of electrons 13 for RHF method. WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: fraction occ = 1.5 for orbitals [5 6] WARN: Invalid number of electrons 13 for RHF method. output file: /dev/null F WARN: Invalid number of electrons 15 for RHF method. converged SCF energy = -106.931080040137 .Overwritten attributes get_hcore get_ovlp of converged SCF energy = -2.93405853397115 = -7.1054274e-15 2S+1 = 1 .. pyscf/scf/test/test_dhf.py output file: /dev/null output file: /dev/null .......WARN: Variational collapse. PES mo_energy -37578.3 < -2c^2 ........... pyscf/scf/test/test_diis.py .converged SCF energy = -74.7874921601008 .output file: /dev/null ..output file: /dev/null .output file: /dev/null . pyscf/scf/test/test_ghf.py output file: /dev/null output file: /dev/null .....WARN: Molecule does not have irrep A1g ..WARN: A1 HOMO 0.185436673760549 > system LUMO -0.493132508003268 WARN: A1 LUMO 0.185436687149438 < system HOMO 0.185436673760549 WARN: B1 HOMO -0.493132512417356 > system LUMO -0.493132508003268 WARN: B1 LUMO -0.493132508003268 < system HOMO 0.185436673760549 WARN: A1 LUMO -0.566643139817743 < system HOMO 3.33789883391776 WARN: B1 HOMO -0.493132512417356 > system LUMO -0.69875414184994 WARN: B1 LUMO -0.493132508003268 < system HOMO 3.33789883391776 WARN: A1 HOMO 2.48888851265683 > system LUMO 0.185436659909893 WARN: B1 HOMO 3.28557598511698 > system LUMO 0.185436659909893 WARN: B2 HOMO 1.25344055578536 > system LUMO 0.185436659909893 .WARN: HOMO -0.827743760903045 == LUMO -0.932887064639662 WARN: HOMO -1.93174845013752 == LUMO -1.93174845013752 WARN: HOMO -1.93174845013752 == LUMO -1.93174845013752 output file: /dev/null ..Warning: must be initialized before calling SCF. Initialize in ....WARN: Fail in reading /tmp/tmpv7kvoj3t. Use MINAO initial guess ........ pyscf/scf/test/test_h2o.py output file: /dev/null .WARN: dual-basis SOSCF is an experimental feature. It is still in testing. ........................ pyscf/scf/test/test_h2o_vdz.py .............. pyscf/scf/test/test_he.py .... pyscf/scf/test/test_jk.py output file: /dev/null ..... pyscf/scf/test/test_response_function.py WARN: system HOMO -0.474582388935663 >= system LUMO -0.474582388935663 output file: /dev/null . pyscf/scf/test/test_rhf.py output file: /dev/null output file: /dev/null output file: /dev/null output file: /dev/null converged SCF energy = -0.466581849557275 .converged SCF energy = -23.8678185857788 ..WARN: SCF object must be initialized before calling post-SCF methods. Initialize for .converged SCF energy = -1.11639404819215 WARN: len(magmom) != natm. Set magmom to zero converged SCF energy = -1.1163913004438 .output file: /dev/null ..Overwritten attributes check_convergence of .......WARN: HOMO -0.880315412771353 == LUMO -0.880315412771353 WARN: HOMO -1.93174845013752 == LUMO -1.93174845013752 WARN: HOMO -1.93174845013752 == LUMO -1.93174845013752 output file: /dev/null .Warning: must be initialized before calling SCF. Initialize in ........WARN: A1 LUMO 0.100626554688218 < system HOMO 0.198508644776464 WARN: B2 HOMO 0.198508644776464 > system LUMO -0.476818251418642 WARN: B2 HOMO -0.11312133505852 > system LUMO -0.472959238444593 WARN: B2 HOMO -0.0790511410480298 > system LUMO -0.274498071320729 WARN: B2 HOMO -0.0779978985584412 > system LUMO -0.268571234655178 WARN: B2 HOMO -0.0782185850612112 > system LUMO -0.268388137950091 WARN: B2 HOMO -0.0782286609731169 > system LUMO -0.26838918752118 WARN: B2 HOMO -0.0782243431147116 > system LUMO -0.268371663507514 WARN: B2 HOMO -0.0782234452778216 > system LUMO -0.26837280517248 WARN: B2 HOMO -0.0782236408825977 > system LUMO -0.268373387005215 .WARN: System has nonzero charge 1; the dipole moment is origin-dependent. Location of origin: [0. 0. 0.] .WARN: System has nonzero charge 1; the dipole moment is origin-dependent. Location of origin: [0. 0. 0.] .Warning: Basis not found for atom 0 O output file: /dev/null ..WARN: Fail in reading /tmp/tmpt6rdl_x1. Use MINAO initial guess ..output file: /dev/null output file: /dev/null .ECP lanl2dz not found for O .output file: /dev/null ....F.WARN: A1g HOMO 0.790973840498403 > system LUMO -0.656109050488459 WARN: A1u LUMO -0.656109050488459 < system HOMO 0.790973840498403 WARN: E1uy HOMO -0.558413963720422 > system LUMO -0.656109050488459 WARN: E1ux HOMO -0.558413963720422 > system LUMO -0.656109050488459 WARN: A1g HOMO 0.375403321704211 > system LUMO -0.525104080372024 WARN: A1u LUMO -0.525104080372024 < system HOMO 0.375403321704211 WARN: A1g HOMO 0.401950751681825 > system LUMO -0.476138571983475 WARN: A1u LUMO -0.476138571983475 < system HOMO 0.401950751681825 WARN: A1g HOMO 0.401393990445035 > system LUMO -0.476334950130309 WARN: A1u LUMO -0.476334950130309 < system HOMO 0.401393990445035 WARN: A1g HOMO 0.401411382439573 > system LUMO -0.476246745051275 WARN: A1u LUMO -0.476246745051275 < system HOMO 0.401411382439573 WARN: A1g HOMO 0.401379501275205 > system LUMO -0.476284149317523 WARN: A1u LUMO -0.476284149317523 < system HOMO 0.401379501275205 WARN: A1g HOMO 0.401386210059678 > system LUMO -0.476280686080067 WARN: A1u LUMO -0.476280686080067 < system HOMO 0.401386210059678 WARN: A1g HOMO 0.401385909196368 > system LUMO -0.476280720764205 WARN: A1u LUMO -0.476280720764205 < system HOMO 0.401385909196368 ...Overwritten attributes get_hcore get_ovlp of converged SCF energy = 0.2 .....output file: /dev/null ....output file: /dev/null ......SCF not converged. SCF energy = -75.7236549363316 converged SCF energy = -75.5614333666719 .... pyscf/scf/test/test_stability.py output file: /dev/null .converged SCF energy = -149.524483960475 converged SCF energy = -108.888295356387 ...converged SCF energy = -149.609744335719 = 2.0354095 2S+1 = 3.0235142 converged SCF energy = -149.609744335719 = 2.0354095 2S+1 = 3.0235142 ... pyscf/scf/test/test_uhf.py WARN: system HOMO 0.100626554688217 >= system LUMO -0.476818251418644 output file: /dev/null output file: /dev/null output file: /dev/null converged SCF energy = -0.466581849557275 = 0.75 2S+1 = 2 converged SCF energy = -0.466581849557275 = 0.75 2S+1 = 2 ....Overwritten attributes get_hcore of WARN: alpha nocc = 7 HOMO -9.0621373864428 >= LUMO -9.0621373864428 WARN: beta nocc = 7 HOMO -9.0621373864428 >= LUMO -9.0621373864428 WARN: system HOMO -9.0621373864428 >= system LUMO -9.0621373864428 ........output file: /dev/null .Warning: must be initialized before calling SCF. Initialize in ............WARN: alpha-A1g HOMO -0.404459356383814 > system LUMO -0.404459356383814 WARN: beta-A1g LUMO -0.404459356383814 < system HOMO -0.404459356383814 .WARN: beta-A1u LUMO -0.656109050488459 < system HOMO -0.404459356383814 .Overwritten attributes get_hcore get_ovlp of converged SCF energy = 1 = 2 2S+1 = 3 ....converged SCF energy = -75.7263969090366 = 2.0038015 2S+1 = 3.0025333 converged SCF energy = -75.2245037720557 = 3.0019372 2S+1 = 3.6066257 ..output file: /dev/null ...WARN: alpha-A1 LUMO 0.100626554688217 < system HOMO 0.198508644776465 WARN: alpha-B2 HOMO 0.198508644776465 > system LUMO -0.476818251418645 WARN: beta-A1 LUMO 0.100626554688217 < system HOMO 0.198508644776465 WARN: beta-B2 LUMO 0.198508644776465 < system HOMO 0.198508644776465 WARN: alpha-B2 HOMO -0.444030706267463 > system LUMO -0.838745087395788 WARN: alpha-B2 HOMO -0.417313188723089 > system LUMO -0.604237958798907 WARN: alpha-B2 HOMO -0.420243713719429 > system LUMO -0.590716306950002 WARN: alpha-B2 HOMO -0.422142131595176 > system LUMO -0.586435350303594 WARN: alpha-B2 HOMO -0.422813147128579 > system LUMO -0.585344207583934 WARN: alpha-B2 HOMO -0.422833541001453 > system LUMO -0.5852413839014 WARN: alpha-B2 HOMO -0.422821043413013 > system LUMO -0.585276649173524 WARN: alpha-B2 HOMO -0.422821534893459 > system LUMO -0.585274419156934 WARN: alpha-B2 HOMO -0.422821159425841 > system LUMO -0.585273839864764 .. pyscf/scf/test/test_vhf.py output file: /dev/null ......... pyscf/sgx/test/test_sgx.py .converged SCF energy = -76.026797861897 .converged SCF energy = -76.0268642221971 converged SCF energy = -76.0267374703505 . pyscf/sgx/test/test_sgx_jk.py ... pyscf/solvent/test/test_cosmors.py .... pyscf/solvent/test/test_ddcosmo.py output file: /dev/null ..WARN: len(magmom) != natm. Set magmom to zero output file: /dev/null output file: /dev/null ..WARN: HOMO -0.466581849557275 == LUMO -0.466581849557275 WARN: HOMO -0.138370373941112 == LUMO -0.138370373941112 WARN: HOMO -0.138370373941112 == LUMO -0.138370373941112 output file: /dev/null output file: /dev/null ..converged SCF energy = -1.06933527174378 WARN: It is recommended to call density_fit() before applying a solvent model. Calling density_fit() after the solvent model may result in incorrect nuclear gradients, TDDFT and other methods. converged SCF energy = -1.06933527174378 .......F pyscf/solvent/test/test_ddcosmo_grad.py F.converged SCF energy = -1.18030499115103 WARN: The code for CASCI gradients was based on variational CASCI wavefunction. However, the ddCOSMO-CASCI energy was not computed variationally. Approximate gradients are evaluated here. A small error may be expected in the gradients which corresponds to the contribution of MCSCF_DM * V_solvent[d/dX MCSCF_DM] + V_solvent[MCSCF_DM] * d/dX MCSCF_DM converged SCF energy = -1.18030499115104 CASCI E = -1.16912342555180 E(CI) = -1.28466295743981 S^2 = 0.0000000 CASCI E = -1.16913854112823 E(CI) = -1.28464873960153 S^2 = 0.0000000 CASCI E = -1.16913902803667 E(CI) = -1.28464885205323 S^2 = 0.0000000 CASCI E = -1.16913903909721 E(CI) = -1.28464885468296 S^2 = 0.0000000 Total energy with solvent effects CASCI E = -1.18433669486790 E(CI) = -1.28464885468296 S^2 = 0.0000000 Fconverged SCF energy = -1.18030499115103 WARN: The code for CASSCF gradients was based on variational CASSCF wavefunction. However, the ddCOSMO-CASSCF energy was not computed variationally. Approximate gradients are evaluated here. A small error may be expected in the gradients which corresponds to the contribution of MCSCF_DM * V_solvent[d/dX MCSCF_DM] + V_solvent[MCSCF_DM] * d/dX MCSCF_DM converged SCF energy = -1.18030499115104 WARN: CASSCF+ddCOSMO may not be able to converge to conv_tol=1e-09 CASSCF energy = -1.19627533436529 CASCI E = -1.19627533436529 E(CI) = -1.99926267289313 S^2 = 0.0000000 Fconverged SCF energy = -1.18030499115103 WARN: Approximate gradients are evaluated here. A small error may be expected in the gradients which corresponds to the contribution of DM * V_solvent[d/dX DM] + V_solvent[DM] * d/dX DM converged SCF energy = -1.18030499115104 converged SCF energy = -1.18030499115364 E(CCSD_Scanner) = -1.20612069429831 E_corr = -0.02581570314467446 F.....converged SCF energy = -1.18030499115103 --------------- ddCOSMORHF (+ddCOSMO) gradients --------------- x y z 0 H 0.3175859136 0.3932221901 0.5722004535 1 H 0.8329455238 -1.0372977654 -0.7749267821 2 H -0.5535637804 0.3139138607 0.6023266411 3 H -0.5969676570 0.3301617146 -0.3996003124 ---------------------------------------------- converged SCF energy = -1.18036221023438 converged SCF energy = -1.18024777013542 converged SCF energy = -0.831524217916429 --------------- ddCOSMORHF_Scanner (+ddCOSMO) gradients --------------- x y z 0 H 1.2466891946 -1.2466891946 -0.0621243572 1 H 0.3573150882 -0.3573150882 -0.4725413878 2 H -1.2429188895 1.2429188895 0.3229641582 3 H -0.3610853933 0.3610853933 0.2117015868 ---------------------------------------------- converged SCF energy = -0.831524217916424 --------------- ddCOSMORHF (+ddCOSMO) gradients --------------- x y z 0 H 1.2466891509 -1.2466891509 -0.0621243097 1 H 0.3573150950 -0.3573150950 -0.4725414241 2 H -1.2429188656 1.2429188656 0.3229641858 3 H -0.3610853803 0.3610853803 0.2117015481 ---------------------------------------------- .Fconverged SCF energy = -0.877594776272974 Fconverged SCF energy = -1.18030499115103 --------------- ddCOSMORHF (+ddCOSMO) gradients --------------- x y z 0 H 0.3175859136 0.3932221901 0.5722004535 1 H 0.8329455238 -1.0372977654 -0.7749267821 2 H -0.5535637804 0.3139138607 0.6023266411 3 H -0.5969676570 0.3301617146 -0.3996003124 ---------------------------------------------- converged SCF energy = -1.18087709505125 converged SCF energy = -1.17973269402405 . pyscf/solvent/test/test_ddcosmo_tdscf_grad.py FFFFFFFFFF pyscf/solvent/test/test_ddpcm.py does not have attributes method WARN: ddPCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. output file: /dev/null output file: /dev/null .. pyscf/solvent/test/test_pcm.py Energy error in RHF with COSMO: 4.263256414560601e-14 .Energy error in RHF with C-PCM: 1.4210854715202004e-14 .Energy error in RHF with IEF-PCM: 7.105427357601002e-14 .Energy error in RHF with SS(V)PE: 7.105427357601002e-14 ...FEnergy error in DFRKS with IEF-PCM: 3.836930773104541e-13 .Energy error in DFUKS with IEF-PCM: 3.410605131648481e-13 ..Energy error in RKS with IEF-PCM: 7.105427357601002e-14 .Warning: must be initialized before calling SCF. Initialize in WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. output file: /dev/null FEnergy error in UHF with IEF-PCM: 9.947598300641403e-14 .Energy error in UKS with IEF-PCM: 8.526512829121202e-14 . pyscf/solvent/test/test_pcm_grad.py output file: /dev/null FFFWARN: Mole.unit (angstrom) is changed to B .Gradient error in RHF with COSMO: 6.3155267259393225e-09 .Gradient error in RHF with CPCM: 6.064433762532085e-09 .Gradient error in RHF with IEFPCM: 5.430152679360913e-09 .Gradient error in RHF with SS(V)PE: 4.082804060542772e-09 .Gradient error in UHF with IEFPCM: 5.430150116529732e-09 . pyscf/solvent/test/test_pcm_hessian.py WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. output file: /dev/null testing C-PCM dV_solv/dx .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing IEF-PCM dV_solv/dx .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing SS(V)PE dV_solv/dx .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing C-PCM Hessian with DF-RKS FWARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing IEF-PCM hessian with DF-RKS FWARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing IEF-PCM d2E_nuc/dx2 .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing IEF-PCM d2E_elec/dx2 .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing C-PCM d2E_KR/dx2 .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing IEF-PCM d2E_KR/dx2 .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing SS(V)PE d2E_KR/dx2 .WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. testing IEF-PCM hessian with DF-UKS F pyscf/solvent/test/test_pcm_tdscf.py WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. does not have attributes cphf_grids WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. does not have attributes cphf_grids WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. WARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. output file: /dev/null FWARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. FWARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. FWARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. FWARN: PCM is an experimental feature. It is still in testing. Features and APIs may be changed in the future. F pyscf/solvent/test/test_pol_embed.py output file: /dev/null output file: /dev/null sssssss pyscf/solvent/test/test_smd.py output file: /dev/null sssssssssssssssssss pyscf/solvent/test/test_smd_grad.py output file: /dev/null sssssssssssss pyscf/solvent/test/test_smd_hessian.py output file: /dev/null ssssssssssssss pyscf/soscf/test/test_newton_ah.py output file: /dev/null output file: /dev/null output file: /dev/null output file: /dev/null output file: /dev/null output file: /dev/null converged SCF energy = -2.80778395753997 ...........WARN: system HOMO -0.474582388935663 >= system LUMO -0.474582388935663 .WARN: system HOMO -0.474582388935663 >= system LUMO -0.474582388935663 .WARN: alpha-B1 HOMO -0.474582388935663 > system LUMO -0.474582388935663 .WARN: system HOMO -0.426968666148784 >= system LUMO -0.426968666148784 .WARN: alpha-B1 HOMO -0.188523345843501 > system LUMO -0.188523345843501 WARN: alpha-B2 HOMO -0.188523345843501 > system LUMO -0.188523345843501 WARN: alpha-B3 HOMO -0.188523345843501 > system LUMO -0.188523345843501 WARN: beta-B1 HOMO -0.188523345843501 > system LUMO -0.188523345843501 WARN: beta-B2 HOMO -0.188523345843501 > system LUMO -0.188523345843501 WARN: alpha-B1 HOMO -0.180429482784365 > system LUMO -0.180429482784364 WARN: alpha-B2 HOMO -0.180429482784364 > system LUMO -0.180429482784364 WARN: alpha-B3 HOMO -0.180429482784364 > system LUMO -0.180429482784364 WARN: beta-B1 HOMO -0.180429482784365 > system LUMO -0.180429482784364 WARN: beta-B2 HOMO -0.180429482784365 > system LUMO -0.180429482784364 WARN: beta-B1 HOMO -0.4306936285308 > system LUMO -0.4306936285308 WARN: beta-B3 HOMO -0.430960061334077 > system LUMO -0.4306936285308 .WARN: system HOMO -0.402204175673421 >= system LUMO -0.402204175673421 .WARN: system HOMO -0.460823893561094 >= system LUMO -0.460823893561094 ..converged SCF energy = -914.53936147065 WARN: Orbital degeneracy broken .converged SCF energy = -37.5906826042057 converged SCF energy = -54.3973578450836 ... pyscf/symm/test/test_Dmatrix.py ... pyscf/symm/test/test_addons.py .... pyscf/symm/test/test_basis.py ............ pyscf/symm/test/test_geom.py .......................................................... pyscf/symm/test/test_sph.py .. pyscf/tdscf/test/test_tddks.py WARN: Singularity detected in overlap matrix (condition number = 2.91e+06). SCF may be inaccurate and hard to converge. WARN: Singularity detected in overlap matrix (condition number = 2.91e+06). SCF may be inaccurate and hard to converge. WARN: HOMO -0.0535841219619609 == LUMO -0.0535841219395128 WARN: HOMO -0.0289425627481585 == LUMO -0.0289425627358248 output file: /dev/null FFFFWARN: Ground state SCF is not converged FWARN: Ground state SCF is not converged F pyscf/tdscf/test/test_tdgks.py WARN: HOMO -0.0572991040792039 == LUMO -0.0572991040792035 output file: /dev/null converged SCF energy = -76.3850439473609 = -1.3322676e-15 2S+1 = 1 converged SCF energy = -75.9839484981057 = 4.2144066e-13 2S+1 = 1 FFFF.FFFFconverged SCF energy = -75.9839484981053 = 1.577849e-12 2S+1 = 1 F pyscf/tdscf/test/test_tdrhf.py output file: /dev/null .converged SCF energy = -108.835774209929 FWARN: Not enough memory to store trial space in _lr_eig.eigh FFFF pyscf/tdscf/test/test_tdrks.py output file: /dev/null EEEEEEEEEEEEEEEEEEEEEEEEEEEEE pyscf/tdscf/test/test_tdrks_vv10.py Overwritten attributes exclude_nlc of output file: /dev/null output file: /dev/null FFOverwritten attributes exclude_nlc of F pyscf/tdscf/test/test_tduhf.py WARN: beta nocc = 4 HOMO -0.663592825229772 >= LUMO -0.663592825229764 WARN: system HOMO 0.138701849393292 >= system LUMO -0.663592825229764 output file: /dev/null .FFFFF pyscf/tdscf/test/test_tduks.py WARN: system HOMO 0.123994959437267 >= system LUMO -0.474582388935664 output file: /dev/null EEEEEEEEEEEEEEEEEEEE pyscf/tools/test/test_cubegen.py ...output file: /dev/null . pyscf/tools/test/test_fcidump.py ..Parsing /tmp/tmpv_9v1h_r Parsing /tmp/tmpqye97mp6 .Overwritten attributes get_hcore get_ovlp of Parsing /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscftmpdir/tmpdw89w7rs converged SCF energy = -107.495893307834 .converged SCF energy = -1.06610864931794 WARN: FCIDUMP does not support point group symmetry Dooh. Converting to its subgroup D2h. Parsing /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscftmpdir/tmpvxgp8qfo . pyscf/tools/test/test_finite_diff.py .. ******** ******** method = RHF initial guess = minao damping factor = 0 level_shift factor = 0 DIIS = diis_start_cycle = 1 diis_space = 8 diis_damp = 0 SCF conv_tol = 1e-09 SCF conv_tol_grad = None SCF max_cycles = 50 direct_scf = True direct_scf_tol = 1e-13 max_memory 4000 MB (current use 1655 MB) Set gradient conv threshold to 3.16228e-05 Initial guess from minao. init E= -0.691603264306376 HOMO = -0.402206600618452 LUMO = 0.361046123922442 cycle= 1 E= -1.06610864931794 delta_E= -0.375 |g|= 2.22e-16 |ddm|= 0.9 HOMO = -0.484441680354209 LUMO = 0.457501939047873 cycle= 2 E= -1.06610864931794 delta_E= 0 |g|= 0 |ddm|= 2.72e-16 HOMO = -0.484441680354209 LUMO = 0.457501939047873 Extra cycle E= -1.06610864931794 delta_E= 0 |g|= 0 |ddm|= 0 converged SCF energy = -1.06610864931794 ******** for ******** unit = Eh/Bohr max_memory 4000 MB (current use 1655 MB) --------------- RHF gradients --------------- x y z 0 H 0.0000000000 0.0000000000 -0.1485715746 1 H 0.0000000000 0.0000000000 0.1485715746 ---------------------------------------------- Computing finite-difference Gradients for {method} WARN: conv_tol 0.001 with displacement 0.005 might be insufficinet Apply {method}.scanner Create scanner for .AlwaysFailed'> WARN: Mole.unit (angstrom) is changed to Bohr New geometry 1 H 0.002645886055 0.000000000000 0.000000000000 AA 0.005000000000 0.000000000000 0.000000000000 Bohr 2 H 0.000000000000 0.000000000000 1.000000000000 AA 0.000000000000 0.000000000000 1.889726124565 Bohr ******** ******** method = AlwaysFailed_Scanner initial guess = minao damping factor = 0 level_shift factor = 0 DIIS = diis_start_cycle = 1 diis_space = 8 diis_damp = 0 SCF conv_tol = 0.001 SCF conv_tol_grad = None SCF max_cycles = 50 direct_scf = True direct_scf_tol = 1e-13 max_memory 4000 MB (current use 1655 MB) Set gradient conv threshold to 0.0316228 init E= -1.06610633131926 HOMO = -0.484441436457787 LUMO = 0.457498204190674 cycle= 1 E= -1.06610766655876 delta_E= -1.34e-06 |g|= 2.22e-16 |ddm|= 1.84e-06 HOMO = -0.484440573198357 LUMO = 0.457499646565075 Extra cycle E= -1.06610766655876 delta_E= -8.88e-16 |g|= 0 |ddm|= 4.71e-16 converged SCF energy = -1.06610766655876 New geometry 1 H 0.000000000000 0.000000000000 0.000000000000 AA 0.000000000000 0.000000000000 0.000000000000 Bohr 2 H 0.000000000000 0.000000000000 1.000000000000 AA 0.000000000000 0.000000000000 1.889726124565 Bohr ..... pyscf/tools/test/test_mo_mapping.py . WARN: Required orbitals are not found .. pyscf/tools/test/test_molden.py ..... pyscf/tools/test/test_qcschema.py ECP def2-svp not found for H ECP def2-svp not found for He Dipole moment(X, Y, Z, Debye): 0.00000, -0.00000, -1.08948 . pyscf/x2c/test/test_tdscf.py WARN: HOMO -0.0573070260614163 == LUMO -0.0573070260522868 WARN: HOMO -0.0330089758154641 == LUMO -0.0330089758062101 output file: /dev/null FFFWARN: HOMO -0.117750477500902 == LUMO -0.117750477492184 FFF pyscf/x2c/test/test_x2c.py output file: /dev/null . WARN: HOMO -0.0372356359662374 == LUMO -0.0369693195803584 converged SCF energy = -37.6494036946543 converged SCF energy = -37.6494036946435 = 1.3333333 2S+1 = 2.5166115 F WARN: HOMO -0.129969371950545 == LUMO -0.129643913423562 converged SCF energy = -37.8217455761948 converged SCF energy = -37.821745576184 = 1.3333333 2S+1 = 2.5166115 F..F..F.. pyscf/x2c/test/test_x2c_grad.py FFF pyscf/x2c/test/test_x2c_hess.py .F... ==================================== ERRORS ==================================== ______________ ERROR at setup of KnownValues.test_dfragf2_h2o_ea _______________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol).density_fit(auxbasis='cc-pv5z-ri') self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_dfragf2_h2o.py:34: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513375, -0. , 0.00916651, 0. , -0.00076132, 0.00924567, -0. , 0. ...312, -0.18219072, -0.18045252, -0.17905901, -0.17103061, -0.16357411, -0.16188682, -0.16024456, -0.07330668]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________ ERROR at setup of KnownValues.test_dfragf2_h2o_ground_state __________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol).density_fit(auxbasis='cc-pv5z-ri') self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_dfragf2_h2o.py:34: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513375, -0. , 0.00916651, 0. , -0.00076132, 0.00924567, -0. , 0. ...312, -0.18219072, -0.18045252, -0.17905901, -0.17103061, -0.16357411, -0.16188682, -0.16024456, -0.07330668]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_dfragf2_h2o_ip _______________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol).density_fit(auxbasis='cc-pv5z-ri') self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_dfragf2_h2o.py:34: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513375, -0. , 0.00916651, 0. , -0.00076132, 0.00924567, -0. , 0. ...312, -0.18219072, -0.18045252, -0.17905901, -0.17103061, -0.16357411, -0.16188682, -0.16024456, -0.07330668]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_dfuagf2_beh_ea _______________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol).density_fit(auxbasis='cc-pv5z-ri') self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_dfuagf2_beh.py:34: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0.00547361, -0. , 0. , -0.00189166, 0. , -0. , 0. , 0. , 0.02...-0.4291627 , -0.4291627 , -0.35291695, -0.31932475, -0.28769478, -0.28769478, -0.27700794, -0.25094674, -0.15468159]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________ ERROR at setup of KnownValues.test_dfuagf2_beh_ground_state __________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol).density_fit(auxbasis='cc-pv5z-ri') self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_dfuagf2_beh.py:34: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0.00547361, -0. , 0. , -0.00189166, 0. , -0. , 0. , 0. , 0.02...-0.4291627 , -0.4291627 , -0.35291695, -0.31932475, -0.28769478, -0.28769478, -0.27700794, -0.25094674, -0.15468159]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_dfuagf2_beh_ip _______________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol).density_fit(auxbasis='cc-pv5z-ri') self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_dfuagf2_beh.py:34: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0.00547361, -0. , 0. , -0.00189166, 0. , -0. , 0. , 0. , 0.02...-0.4291627 , -0.4291627 , -0.35291695, -0.31932475, -0.28769478, -0.28769478, -0.27700794, -0.25094674, -0.15468159]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_ragf2_frozen ________________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_ragf2_frozen_fully_outcore _________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_ragf2_frozen_outcore ____________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_ragf2_h2o_ea ________________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________ ERROR at setup of KnownValues.test_ragf2_h2o_ground_state ___________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_ragf2_h2o_ip ________________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_ragf2_outcore _______________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='cc-pvdz', verbose=0) self.mf = scf.RHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.RAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_ragf2_h2o.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:620: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[ 0. , -0.01513294, 0. , 0.00916688, 0. , -0.00076178, -0.00924629, -0. , -0. ...302, -0.18219056, -0.18045254, -0.17905956, -0.17103027, -0.16357417, -0.16188727, -0.16024594, -0.07330538]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_uagf2_beh_ea ________________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_uagf2_beh.py:36: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[-0.00547518, -0. , 0. , -0.00188868, -0. , 0. , 0. , 0. , -0.02...-0.4291645 , -0.4291645 , -0.35291527, -0.31932451, -0.28769511, -0.28769511, -0.27700893, -0.25094685, -0.15468174]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________ ERROR at setup of KnownValues.test_uagf2_beh_ground_state ___________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_uagf2_beh.py:36: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[-0.00547518, -0. , 0. , -0.00188868, -0. , 0. , 0. , 0. , -0.02...-0.4291645 , -0.4291645 , -0.35291527, -0.31932451, -0.28769511, -0.28769511, -0.27700893, -0.25094685, -0.15468174]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_uagf2_beh_ip ________________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_uagf2_beh.py:36: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[-0.00547518, -0. , 0. , -0.00188868, -0. , 0. , 0. , 0. , -0.02...-0.4291645 , -0.4291645 , -0.35291527, -0.31932451, -0.28769511, -0.28769511, -0.27700893, -0.25094685, -0.15468174]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_uagf2_frozen_fully_outcore _________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_uagf2_beh.py:36: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[-0.00547518, -0. , 0. , -0.00188868, -0. , 0. , 0. , 0. , -0.02...-0.4291645 , -0.4291645 , -0.35291527, -0.31932451, -0.28769511, -0.28769511, -0.27700893, -0.25094685, -0.15468174]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_uagf2_frozen_outcore ____________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_uagf2_beh.py:36: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[-0.00547518, -0. , 0. , -0.00188868, -0. , 0. , 0. , 0. , -0.02...-0.4291645 , -0.4291645 , -0.35291527, -0.31932451, -0.28769511, -0.28769511, -0.27700893, -0.25094685, -0.15468174]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_uagf2_outcore _______________ self = @classmethod def setUpClass(self): self.mol = gto.M(atom='Be 0 0 0; H 0 0 1', basis='cc-pvdz', spin=1, verbose=0) self.mf = scf.UHF(self.mol) self.mf.chkfile = tempfile.NamedTemporaryFile().name self.mf.conv_tol = 1e-12 self.mf.run() self.gf2 = agf2.UAGF2(self.mf) self.gf2.conv_tol = 1e-7 > self.gf2.run() pyscf/agf2/test/test_uagf2_beh.py:36: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/agf2/ragf2.py:832: in kernel kernel(self, eri=eri, gf=gf, se=se, verbose=self.verbose, dump_chk=dump_chk) pyscf/agf2/ragf2.py:71: in kernel e_init = agf2.energy_mp2(agf2.mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:467: in energy_mp2 self.e_init = energy_mp2(self, mo_energy, se) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/uagf2.py:334: in energy_mp2 emp2_a = ragf2.energy_mp2(agf2, gf[0], se[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/agf2/ragf2.py:433: in energy_mp2 emp2 = lib.einsum('xk,xk,xk->', vxk, vxk.conj(), 1./dxk) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xk,xk,xk->' tensors = [array([[-0.00547518, -0. , 0. , -0.00188868, -0. , 0. , 0. , 0. , -0.02...-0.4291645 , -0.4291645 , -0.35291527, -0.31932451, -0.28769511, -0.28769511, -0.27700893, -0.25094685, -0.15468174]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xk,xk->xk', ['xk', 'xk']), ((1, 0), 'xk,xk->', [''])] contraction = ((1, 0), 'xk,xk->xk', ['xk', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ao2mo ___________________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_df_eaccsd _________________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_df_eaccsd_koopmans _____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_df_eomee_ccsd_diag _____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_df_eomee_ccsd_matvec ____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_df_eomee_init_guess ____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_df_eomsf_ccsd_matvec ____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_df_ipccsd _________________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_df_ipccsd_koopmans _____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_eomee ___________________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_eomee_ccsd_spin_keep ____________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_with_df __________________ def setUpModule(): global mol, rhf, mf, ucc, ucc1, nocca, nvira, noccb, nvirb mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > ucc = dfuccsd.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfuccsd.py:40: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1095: in ccsd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:43: in ao2mo return _make_df_eris(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/dfuccsd.py:137: in _make_df_eris Lpq = lib.einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, -1.38533144, 0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ea_matvec _________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eaccsd ___________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_eaccsd_koopmans ______________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_eomee_diag _________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_eomee_matvec ________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_h2o_star __________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ip_matvec _________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ipccsd ___________________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_ipccsd_koopmans ______________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_t3p2_intermediates_complex _________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________ ERROR at setup of KnownValues.test_t3p2_intermediates_real __________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_vector_to_amplitudes ____________ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____ ERROR at setup of KnownValues.test_vector_to_amplitudes_overwritten ______ def setUpModule(): global mol, mf, mycc, eris1, mycc1, nocc, nvir mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '6-31g' mol.verbose = 7 mol.output = '/dev/null' mol.build() mf = scf.RHF(mol).run() > mycc = cc.GCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_gccsd.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[ 0. , -0. , 0. , -0. , 0. , -0. , -0. , -0. , -0. ... , 0. , -0. , 0. , -0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ea_matvec _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_ea_matvec1 _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_ea_matvec2 _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eaccsd ___________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eaccsd2 __________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_eaccsd_koopmans ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_eaccsd_koopmans2 ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_eaccsd_partition ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_eaccsd_partition2 _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eeccsd ___________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eeccsd2 __________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eeccsd3 __________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_eeccsd_koopmans ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_eeccsd_koopmans2 ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_eeccsd_koopmans3 ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________ ERROR at setup of KnownValues.test_eomee_ccsd_matvec_singlet _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_eomee_ccsd_matvec_singlet2 _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_eomee_ccsd_matvec_singlet3 _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________ ERROR at setup of KnownValues.test_eomee_ccsd_matvec_triplet _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_eomee_ccsd_matvec_triplet2 _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_eomee_ccsd_matvec_triplet3 _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_eomee_ccsd_singlet _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_eomee_ccsd_triplet _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_eomee_diag _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_eomee_diag2 ________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_eomee_diag3 ________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_eomsf_ccsd _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_eomsf_ccsd_matvec _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_eomsf_ccsd_matvec2 _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_eomsf_ccsd_matvec3 _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_h2o_star __________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ip_matvec _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_ip_matvec1 _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_ip_matvec2 _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_ip_matvec3 _________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ipccsd ___________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ipccsd2 __________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ipccsd3 __________________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_ipccsd_koopmans ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ipccsd_koopmans2 ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ipccsd_koopmans3 ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ipccsd_partition ______________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ipccsd_partition2 _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ipccsd_partition3 _____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_sort_left_right_eigensystem ________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______ ERROR at setup of KnownValues.test_t3p2_intermediates_against_so _______ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_t3p2_intermediates_complex _________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________ ERROR at setup of KnownValues.test_t3p2_intermediates_real __________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_vector_to_amplitudes ____________ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____ ERROR at setup of KnownValues.test_vector_to_amplitudes_overwritten ______ def setUpModule(): global mol, mf, mycc, mf1, eris1, mycc1, mycci, erisi, mycc2, mycc21, eris21, mycc3, mycc31, eris31, no, nv mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.verbose = 0 mol.spin = 0 mol.build() mf = scf.RHF(mol).run() > mycc = rccsd.RCCSD(mf).run() ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_eom_rccsd.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01008377, -0. , -0. , -0.01110746, -0.00413918, 0. , -0. , 0.00689724, -0....-0. , -0. , 0. , 0. , -0.00000001, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eaccsd ___________________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_eaccsd_koopmans ______________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_eomee ___________________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_eomee1 ___________________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_eomee_ccsd_spin_keep ____________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_eomsf_ccsd _________________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ipccsd ___________________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_ipccsd_koopmans ______________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_spatial2spin_eomsf _____________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ucc_eomea_matvec ______________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_ucc_eomee_ccsd_diag ____________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_ucc_eomee_ccsd_matvec ___________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_ucc_eomee_init_guess ____________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_ucc_eomip_matvec ______________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_ucc_eomsf_ccsd_matvec ___________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_ucc_update_amps ______________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____ ERROR at setup of KnownValues.test_vector_to_amplitudes_eom_spin_keep _____ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________ ERROR at setup of KnownValues.test_vector_to_amplitudes_eomsf _________ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____ ERROR at setup of KnownValues.test_vector_to_amplitudes_overwritten ______ def setUpModule(): global mol, mf, mol1, mf0, mf1, gmf, ucc, ucc0, ucc1 global orbspin, nocca, noccb, nvira, nvirb, r1, r2 mol = gto.Mole() mol.verbose = 0 mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mol1 = mol.copy() mol1.spin = 2 mol1.build() mf0 = scf.UHF(mol1).run(conv_tol=1e-12) mf1 = mf0.copy() nocca, noccb = mol1.nelec nmo = mol1.nao_nr() nvira, nvirb = nmo-nocca, nmo-noccb numpy.random.seed(12) mf1.mo_coeff = numpy.random.random((2,nmo,nmo)) - .5 gmf = scf.addons.convert_to_ghf(mf1) orbspin = gmf.mo_coeff.orbspin ucc1 = cc.UCCSD(mf1) numpy.random.seed(11) no = nocca + noccb nv = nvira + nvirb r1 = numpy.random.random((no,nv)) - .9 r2 = numpy.random.random((no,no,nv,nv)) - .9 r2 = r2 - r2.transpose(1,0,2,3) r2 = r2 - r2.transpose(0,1,3,2) r1 = cc.addons.spin2spatial(r1, orbspin) r2 = cc.addons.spin2spatial(r2, orbspin) r1,r2 = eom_uccsd.vector_to_amplitudes_ee( eom_uccsd.amplitudes_to_vector_ee(r1,r2), ucc1.nmo, ucc1.nocc) ucc1.t1 = r1 ucc1.t2 = r2 ucc = cc.UCCSD(mf) ucc.max_space = 0 ucc.conv_tol = 1e-8 > ucc.kernel()[0] ^^^^^^^^^^^^ pyscf/cc/test/test_eom_uccsd.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0. , -0. , 0. , -0. , 0. , 0. , 0. , 0. ], ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ERIS ____________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______ ERROR at setup of KnownValues.test_amplitudes_from_rccsd_or_uccsd _______ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_frozen ___________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_gccsd ___________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_mbpt2 ___________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_rdm_complex ________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_rdm_real __________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_rdm_real1 _________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_rdm_vs_rccsd ________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_rdm_vs_uccsd ________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_spin2spatial ________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_update_amps ________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_vector_size ________________ def setUpModule(): global mol, mf, gcc1 mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.verbose = 5 mol.output = '/dev/null' mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).run(conv_tol=1e-12) mf = scf.addons.convert_to_ghf(mf) > gcc1 = gccsd.GCCSD(mf).run(conv_tol=1e-9) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd.py:45: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:161: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gccsd.py:51: in update_amps Wovvo = imd.cc_Wovvo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/gintermediates.py:81: in cc_Wovvo Wmbej -= einsum('jf,nb,mnef->mbej', t1, t1, eris.oovv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'jf,nb,mnef->mbej' tensors = [array([[-0. , -0. , -0. , -0. , -0. , -0. , -0. , 0. , -0. ... , 0. , 0. , 0. , 0. , 0. , 0. ]]]], shape=(10, 10, 16, 16))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']), ((1, 0), 'jmne,nb->mbej', ['mbej'])] contraction = ((2, 0), 'mnef,jf->jmne', ['nb', 'jmne']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_gccsd_t __________________ def setUpModule(): global mol, mol1, mf, myucc, mygcc mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.757 , .587)], [1 , (0. , .757 , .587)]] mol.spin = 2 mol.basis = '3-21g' mol.symmetry = 'C2v' mol.build() mol1 = mol.copy() mol1.symmetry = False mf = scf.UHF(mol1).run(conv_tol=1e-14) > myucc = cc.UCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd_t.py:41: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., -0., 0., 0., 0., 0., -0.], [ 0., 0., 0., 0., 0., 0., 0.], [-0., -0., -0., -0., -... [ 0. , -0. , 0.02176894, 0. , 0.01802969, 0. , 0.04003886]]]], shape=(6, 7, 6, 7))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________ ERROR at setup of KnownValues.test_gccsd_t_compare_uccsd_t __________ def setUpModule(): global mol, mol1, mf, myucc, mygcc mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.757 , .587)], [1 , (0. , .757 , .587)]] mol.spin = 2 mol.basis = '3-21g' mol.symmetry = 'C2v' mol.build() mol1 = mol.copy() mol1.symmetry = False mf = scf.UHF(mol1).run(conv_tol=1e-14) > myucc = cc.UCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd_t.py:41: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., -0., 0., 0., 0., 0., -0.], [ 0., 0., 0., 0., 0., 0., 0.], [-0., -0., -0., -0., -... [ 0. , -0. , 0.02176894, 0. , 0.01802969, 0. , 0.04003886]]]], shape=(6, 7, 6, 7))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_gccsd_t_complex ______________ def setUpModule(): global mol, mol1, mf, myucc, mygcc mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.757 , .587)], [1 , (0. , .757 , .587)]] mol.spin = 2 mol.basis = '3-21g' mol.symmetry = 'C2v' mol.build() mol1 = mol.copy() mol1.symmetry = False mf = scf.UHF(mol1).run(conv_tol=1e-14) > myucc = cc.UCCSD(mf).run() ^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd_t.py:41: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., -0., 0., 0., 0., 0., -0.], [ 0., 0., 0., 0., 0., 0., 0.], [-0., -0., -0., -0., -... [ 0. , -0. , 0.02176894, 0. , 0.01802969, 0. , 0.04003886]]]], shape=(6, 7, 6, 7))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ ERROR at setup of KnownValues.test_0 _____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ ERROR at setup of KnownValues.test_1 _____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ ERROR at setup of KnownValues.test_2 _____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ ERROR at setup of KnownValues.test_3 _____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ ERROR at setup of KnownValues.test_4 _____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ ERROR at setup of KnownValues.test_5 _____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_amp_input _________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_chkfile __________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_density_fitting ______________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_hermi_moments _______________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_lambda_assertion ______________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_misc ____________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_mom_input _________________ cls = @classmethod def setUpClass(cls): cls.mol = gto.Mole() cls.mol.atom = "O 0 0 0; H 0 -0.757 0.587; H 0 0.757 0.587" cls.mol.basis = "6-31g" cls.mol.verbose = 0 cls.mol.build() cls.mf = scf.RHF(cls.mol) cls.mf.conv_tol_grad = 1e-8 cls.mf.kernel() cls.mycc = cc.ccsd.CCSD(cls.mf) cls.mycc.conv_tol = 1e-10 cls.mycc.kernel() > cls.mycc.solve_lambda() pyscf/cc/test/test_momgfccsd.py:24: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., 0., -0., -0., 0., 0.], [ 0., -0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ERIS ____________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_add_vvvv __________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_amplitudes_to_vector ____________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ao2mo ___________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ao_direct _________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ccsd_t ___________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_density_fit_interface ___________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_diagnostic _________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_dump_chk __________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_eris_contract_vvvv_t2 ___________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_incore_complete ______________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_iterative_dampling _____________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_mbpt2 ___________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_no_diis __________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_rccsd_frozen ________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_restart __________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_roccsd ___________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_update_amps ________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_vector_size ________________ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____ ERROR at setup of KnownValues.test_vector_to_amplitudes_overwritten ______ def setUpModule(): global mol, mf, eris, mycc mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.chkfile = tempfile.NamedTemporaryFile().name mf.conv_tol_grad = 1e-8 mf.kernel() mycc = rccsd.RCCSD(mf) mycc.conv_tol = 1e-10 eris = mycc.ao2mo() > mycc.kernel(eris=eris) pyscf/cc/test/test_rccsd.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01169288, -0. , -0. , -0. , -0.01612109, 0.00022651, -0. , -0.02080587], ...0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0., 0., 0.], [-0., 0., -0., 0., -0., -0., -0., -0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ERIS ____________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_add_vvVV __________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_add_vvvv __________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_amplitudes_from_rccsd ___________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ao2mo ___________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_damping __________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_eris_contract_vvvv_t2 ___________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_h2o_rdm __________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_h4_rdm ___________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_mbpt2 ___________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ ERROR at setup of KnownValues.test_rdm ____________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_reset ___________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_uccsd_frozen ________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_uintermediats _______________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_update_amps1 ________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_update_amps2 ________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_vector_size ________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_vector_to_amplitudes ____________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____ ERROR at setup of KnownValues.test_vector_to_amplitudes_overwritten ______ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_with_df_s0 _________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_with_df_s2 _________________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_zero_beta_electrons ____________ def setUpModule(): global mol, rhf, mf, myucc, mol_s2, mf_s2, eris mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol) rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) > myucc = cc.UCCSD(mf).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0., 0., 0., -0., -0., -0., -0., -0.], [-0., -0., -0., 0., 0., 0., -0., -0.], [ 0., -0., ...19, 0. , 0. , -0. , -0.0033399 , -0.00457009, 0. , 0.04515319]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_uccsd_t __________________ def setUpModule(): global mol, mol1, mf, mcc mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.757 , .587)], [1 , (0. , .757 , .587)]] mol.spin = 2 mol.basis = '3-21g' mol.symmetry = 'C2v' mol.build() mol1 = mol.copy() mol1.symmetry = False mf = scf.UHF(mol1).run(conv_tol=1e-14) mcc = cc.UCCSD(mf) mcc.conv_tol = 1e-14 > mcc.kernel() pyscf/cc/test/test_uccsd_t.py:50: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0., -0., 0., -0., 0., 0., 0.], [-0., 0., 0., -0., 0., -0., -0.], [ 0., -0., -0., -0., ... [ 0. , 0. , 0.02176894, 0. , 0.01802969, 0. , 0.04003886]]]], shape=(6, 7, 6, 7))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_uccsd_t_complex ______________ def setUpModule(): global mol, mol1, mf, mcc mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.757 , .587)], [1 , (0. , .757 , .587)]] mol.spin = 2 mol.basis = '3-21g' mol.symmetry = 'C2v' mol.build() mol1 = mol.copy() mol1.symmetry = False mf = scf.UHF(mol1).run(conv_tol=1e-14) mcc = cc.UCCSD(mf) mcc.conv_tol = 1e-14 > mcc.kernel() pyscf/cc/test/test_uccsd_t.py:50: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0., -0., 0., -0., 0., 0., 0.], [-0., 0., 0., -0., 0., -0., -0.], [ 0., -0., -0., -0., ... [ 0. , 0. , 0.02176894, 0. , 0.01802969, 0. , 0.04003886]]]], shape=(6, 7, 6, 7))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_uccsd_t_rdm ________________ def setUpModule(): global mol, mol1, mf, mcc mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.757 , .587)], [1 , (0. , .757 , .587)]] mol.spin = 2 mol.basis = '3-21g' mol.symmetry = 'C2v' mol.build() mol1 = mol.copy() mol1.symmetry = False mf = scf.UHF(mol1).run(conv_tol=1e-14) mcc = cc.UCCSD(mf) mcc.conv_tol = 1e-14 > mcc.kernel() pyscf/cc/test/test_uccsd_t.py:50: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0., -0., 0., -0., 0., 0., 0.], [-0., 0., 0., -0., 0., -0., -0.], [ 0., -0., -0., -0., ... [ 0. , 0. , 0.02176894, 0. , 0.01802969, 0. , 0.04003886]]]], shape=(6, 7, 6, 7))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_diabatize _________________ def setUpModule(): global mol, mf, mc > mol, mf, mc = get_lih (1.5) ^^^^^^^^^^^^^ pyscf/mcpdft/test/test_mspdft.py:33: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_mspdft.py:28: in get_lih mc = mc.multi_state ([0.5,0.5], 'cms').run (conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_final_adiabats _______________ def setUpModule(): global mol, mf, mc > mol, mf, mc = get_lih (1.5) ^^^^^^^^^^^^^ pyscf/mcpdft/test/test_mspdft.py:33: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_mspdft.py:28: in get_lih mc = mc.multi_state ([0.5,0.5], 'cms').run (conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_intermediate_diabats ____________ def setUpModule(): global mol, mf, mc > mol, mf, mc = get_lih (1.5) ^^^^^^^^^^^^^ pyscf/mcpdft/test/test_mspdft.py:33: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_mspdft.py:28: in get_lih mc = mc.multi_state ([0.5,0.5], 'cms').run (conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_reference_adiabats _____________ def setUpModule(): global mol, mf, mc > mol, mf, mc = get_lih (1.5) ^^^^^^^^^^^^^ pyscf/mcpdft/test/test_mspdft.py:33: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_mspdft.py:28: in get_lih mc = mc.multi_state ([0.5,0.5], 'cms').run (conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_n3_diffuse _________________ def setUpModule(): global cell, kmf, mycc, eris cell = make_test_cell.test_cell_n3_diffuse() kmf = scf.KRHF(cell, kpts=cell.make_kpts([1,1,2], with_gamma_point=True), exxdiv=None) kmf.conv_tol = 1e-10 kmf.conv_tol_grad = 1e-6 kmf.scf() mycc = cc.KGCCSD(kmf) mycc.conv_tol = 1e-7 mycc.conv_tol_normt = 1e-7 > mycc.run() pyscf/pbc/cc/test/test_eom_kgccsd.py:20: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... , -0.00000021-0.j , -0. -0.j , 0.01298529+0.j ]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_n3_diffuse_Ta _______________ def setUpModule(): global cell, kmf, mycc, eris cell = make_test_cell.test_cell_n3_diffuse() kmf = scf.KRHF(cell, kpts=cell.make_kpts([1,1,2], with_gamma_point=True), exxdiv=None) kmf.conv_tol = 1e-10 kmf.conv_tol_grad = 1e-6 kmf.scf() mycc = cc.KGCCSD(kmf) mycc.conv_tol = 1e-7 mycc.conv_tol_normt = 1e-7 > mycc.run() pyscf/pbc/cc/test/test_eom_kgccsd.py:20: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... , -0.00000021-0.j , -0. -0.j , 0.01298529+0.j ]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_n3_diffuse_frozen _____________ def setUpModule(): global cell, kmf, mycc, eris cell = make_test_cell.test_cell_n3_diffuse() kmf = scf.KRHF(cell, kpts=cell.make_kpts([1,1,2], with_gamma_point=True), exxdiv=None) kmf.conv_tol = 1e-10 kmf.conv_tol_grad = 1e-6 kmf.scf() mycc = cc.KGCCSD(kmf) mycc.conv_tol = 1e-7 mycc.conv_tol_normt = 1e-7 > mycc.run() pyscf/pbc/cc/test/test_eom_kgccsd.py:20: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... , -0.00000021-0.j , -0. -0.j , 0.01298529+0.j ]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_n3_diffuse_star ______________ def setUpModule(): global cell, kmf, mycc, eris cell = make_test_cell.test_cell_n3_diffuse() kmf = scf.KRHF(cell, kpts=cell.make_kpts([1,1,2], with_gamma_point=True), exxdiv=None) kmf.conv_tol = 1e-10 kmf.conv_tol_grad = 1e-6 kmf.scf() mycc = cc.KGCCSD(kmf) mycc.conv_tol = 1e-7 mycc.conv_tol_normt = 1e-7 > mycc.run() pyscf/pbc/cc/test/test_eom_kgccsd.py:20: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... , -0.00000021-0.j , -0. -0.j , 0.01298529+0.j ]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_krccsd_ksym ________________ def setUpModule(): global kmf, kcc L = 2. He = gto.Cell() He.verbose = 5 He.output = '/dev/null' He.a = np.eye(3)*L He.atom =[['He' , ( L/2+0., L/2+0., L/2+0.)],] He.basis = {'He': [[0, (4.0, 1.0)], [0, (1.0, 1.0)]]} He.space_group_symmetry = True He.build() nk = [2,2,2] kpts = He.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = scf.KRHF(He, kpts, exxdiv=None).density_fit() > kmf.kernel() pyscf/pbc/cc/test/test_kccsd_ksymm.py:38: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.125, 0.375, 0.375, 0.125]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821...71552616+0.j, 0.99841537-0.j]], [[1. -0.j, 0.71549499+0.j], [0.71549499+0.j, 0.99526111-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_vs_krccsd _________________ def setUpModule(): global kmf, kcc L = 2. He = gto.Cell() He.verbose = 5 He.output = '/dev/null' He.a = np.eye(3)*L He.atom =[['He' , ( L/2+0., L/2+0., L/2+0.)],] He.basis = {'He': [[0, (4.0, 1.0)], [0, (1.0, 1.0)]]} He.space_group_symmetry = True He.build() nk = [2,2,2] kpts = He.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = scf.KRHF(He, kpts, exxdiv=None).density_fit() > kmf.kernel() pyscf/pbc/cc/test/test_kccsd_ksymm.py:38: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.125, 0.375, 0.375, 0.125]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821...71552616+0.j, 0.99841537-0.j]], [[1. -0.j, 0.71549499+0.j], [0.71549499+0.j, 0.99526111-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_kmp2 ____________________ def setUpModule(): global He, nk, kpts0, kpts, kmf0, kmf, kmp2ref L = 2. He = gto.Cell() He.verbose = 0 He.a = np.eye(3)*L He.atom =[['He' , ( L/2+0., L/2+0., L/2+0.)],] He.basis = {'He': [[0, (4.0, 1.0)], [0, (1.0, 1.0)]]} He.space_group_symmetry=True He.output = '/dev/null' He.build() nk = [2,2,2] kpts0 = He.make_kpts(nk) kmf0 = scf.KRHF(He, kpts0, exxdiv=None).density_fit() kmf0.kernel() kmp2ref = mp.KMP2(kmf0) kmp2ref.kernel() kpts = He.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = scf.KRHF(He, kpts, exxdiv=None).density_fit() > kmf.kernel() pyscf/pbc/mp/test/test_ksym.py:44: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.125, 0.375, 0.375, 0.125]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821...71552616+0.j, 0.99841537-0.j]], [[1. -0.j, 0.71549499+0.j], [0.71549499+0.j, 0.99526111-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_rdm1 ____________________ def setUpModule(): global He, nk, kpts0, kpts, kmf0, kmf, kmp2ref L = 2. He = gto.Cell() He.verbose = 0 He.a = np.eye(3)*L He.atom =[['He' , ( L/2+0., L/2+0., L/2+0.)],] He.basis = {'He': [[0, (4.0, 1.0)], [0, (1.0, 1.0)]]} He.space_group_symmetry=True He.output = '/dev/null' He.build() nk = [2,2,2] kpts0 = He.make_kpts(nk) kmf0 = scf.KRHF(He, kpts0, exxdiv=None).density_fit() kmf0.kernel() kmp2ref = mp.KMP2(kmf0) kmp2ref.kernel() kpts = He.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = scf.KRHF(He, kpts, exxdiv=None).density_fit() > kmf.kernel() pyscf/pbc/mp/test/test_ksym.py:44: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.125, 0.375, 0.375, 0.125]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821...71552616+0.j, 0.99841537-0.j]], [[1. -0.j, 0.71549499+0.j], [0.71549499+0.j, 0.99526111-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_convert_from ________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_get_rho __________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________ ERROR at setup of KnownValues.test_init_guess_from_chkfile __________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_kghf ____________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_khf_newton _________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_krhf_df __________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_krhf_gamma_center _____________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_krhf_monkhorst _______________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_krhf_symorb ________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_kuhf_df __________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_kuhf_gamma_center _____________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_kuhf_monkhorst _______________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_kuhf_newton ________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_kuhf_smearing _______________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_to_khf ___________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ ERROR at setup of KnownValues.test_to_khf_with_chkfile ____________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_to_rhf ___________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_to_uhf ___________________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_transform_fock _______________ def setUpModule(): global cell, He, nk, kmf0, kumf0, kmf_ksymm, kumf_ksymm cell = make_primitive_cell([16]*3) nk = [1,2,2] kmf0 = pscf.KRHF(cell, cell.make_kpts(nk)).run() kumf0 = pscf.KUHF(cell, cell.make_kpts(nk)).run() kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kmf_ksymm = pscf.KRHF(cell, kpts) kmf_ksymm.chkfile='kmf_ksymm.chk' > kmf_ksymm.kernel() pyscf/pbc/scf/test/test_khf_ksym.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0. ... -0.j, -0. -0.j, -0.549031+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.712682-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ab_b3lyp __________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ab_hf ___________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ab_lda ___________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ab_mgga __________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_analyze __________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_dRPA ____________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_dTDA ____________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_init ____________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_nohbrid_b88p86 _______________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_nohbrid_lda ________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ ERROR at setup of KnownValues.test_nto ____________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_reset ___________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_scanner __________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_tda_b3lyp_triplet _____________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_tda_b3lypg _________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_tda_lda __________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_tda_lda_triplet ______________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_tda_m06l_singlet ______________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_tda_rsh __________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_tda_with_wfnsym ______________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_tddft_b3lyp ________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_tddft_b88p86 ________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_tddft_b88p86_triplet ____________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_tddft_camb3lyp _______________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_tddft_hse06 ________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_tddft_lda _________________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_tddft_with_wfnsym _____________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_tdhf_with_wfnsym ______________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ ERROR at setup of KnownValues.test_transition_multipoles ___________ def setUpModule(): global mol, mf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = [ ['H' , (0. , 0. , .917)], ['F' , (0. , 0. , 0.)], ] mol.basis = '631g' mol.build() mf = scf.RHF(mol).run() > td_hf = tdscf.TDHF(mf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , -0. , 0. , 0.978924, -0.053791], [-0.0028 , 0.094185, 0.699376, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_ab_b3lyp __________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_ab_hf ___________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ab_lda ___________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_ab_mgga __________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_analyze __________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ ERROR at setup of KnownValues.test_init ____________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_nohybrid_b88p86 ______________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_nohybrid_lda ________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ ERROR at setup of KnownValues.test_nto ____________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_tda_b3lyp _________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_tda_lda __________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_tda_m06l __________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ ERROR at setup of KnownValues.test_tda_rsh __________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_tda_with_wfnsym ______________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ ERROR at setup of KnownValues.test_tddft_b3lyp ________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ ERROR at setup of KnownValues.test_tddft_b88p86 ________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ ERROR at setup of KnownValues.test_tddft_camb3lyp _______________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ ERROR at setup of KnownValues.test_tddft_lda _________________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_tddft_with_wfnsym _____________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ ERROR at setup of KnownValues.test_tdhf_with_wfnsym ______________ def setUpModule(): global mol, mol1, mf_uhf, td_hf, mf_lda, mf_bp86, mf_b3lyp, mf_m06l mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.spin = 2 mol.basis = '631g' mol.build() mol1 = gto.Mole() mol1.verbose = 0 mol1.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol1.basis = '631g' mol1.build() mf_uhf = scf.UHF(mol).run() > td_hf = tdscf.TDHF(mf_uhf).run(conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduks.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0.], ....226884, 0. , 0.119948, -0.131276], [ 0.001965, -0.029157, 0.090045, -0. , 0.033009, -0.911087]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError =================================== FAILURES =================================== ___________________________ KnownValues.test_ea_adc2 ___________________________ self = def test_ea_adc2(self): e, t_amp1, t_amp2 = myadc.kernel_gs() self.assertAlmostEqual(e, -0.2218560609876961, 6) dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 20.3557963972156, 6) myadcea = adc.radc_ea.RADCEA(myadc) e,v,p,x = myadcea.kernel(nroots=3) self.assertAlmostEqual(e[0], 0.0287675413010661, 6) self.assertAlmostEqual(e[1], 0.0553475511361251, 6) self.assertAlmostEqual(e[2], 0.1643553780332306, 6) self.assertAlmostEqual(p[0], 1.9868196915945326, 6) self.assertAlmostEqual(p[1], 1.9941128865405613, 6) self.assertAlmostEqual(p[2], 1.9760420333383126, 6) > dm1_exc = np.array(myadcea.make_rdm1()) ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ea_H2O.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ea.py:914: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ea.py:955: in make_rdm1_eigenvectors rdm1[:nocc, :nocc] += 2 * einsum('a,a,IJ->IJ', L1, R1, kd_oc, optimize = einsum_type) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'a,a,IJ->IJ' tensors = [array([ 9.95443938e-01, -1.71280603e-13, -3.20252379e-02, 5.54048454e-17, -4.53205570e-02, 1.48304937e-13, ..., [0., 1., 0., 0., 0.], [0., 0., 1., 0., 0.], [0., 0., 0., 1., 0.], [0., 0., 0., 0., 1.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'a,a->', ['IJ', '']), ((1, 0), ',IJ->IJ', ['IJ'])] contraction = ((1, 0), 'a,a->', ['IJ', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ea_adc2x ___________________________ self = def test_ea_adc2x(self): myadc.method = "adc(2)-x" e, t_amp1, t_amp2 = myadc.kernel_gs() self.assertAlmostEqual(e, -0.2218560609876961, 6) dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 20.3557963972156, 6) myadcea = adc.radc_ea.RADCEA(myadc) e,v,p,x = myadcea.kernel(nroots=3) self.assertAlmostEqual(e[0], 0.0270276135717527, 6) self.assertAlmostEqual(e[1], 0.0546446308721235, 6) self.assertAlmostEqual(e[2], 0.1614552196278816, 6) self.assertAlmostEqual(p[0], 1.9782643804856972, 6) self.assertAlmostEqual(p[1], 1.9905409664546319, 6) self.assertAlmostEqual(p[2], 1.9593142553574816, 6) > dm1_exc = myadcea.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ea_H2O.py:104: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ea.py:914: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ea.py:955: in make_rdm1_eigenvectors rdm1[:nocc, :nocc] += 2 * einsum('a,a,IJ->IJ', L1, R1, kd_oc, optimize = einsum_type) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'a,a,IJ->IJ' tensors = [array([-9.92489518e-01, 2.05470142e-13, 3.98253476e-02, -6.11488018e-17, 5.51499360e-02, -1.81342638e-13, -..., [0., 1., 0., 0., 0.], [0., 0., 1., 0., 0.], [0., 0., 0., 1., 0.], [0., 0., 0., 0., 1.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'a,a->', ['IJ', '']), ((1, 0), ',IJ->IJ', ['IJ'])] contraction = ((1, 0), 'a,a->', ['IJ', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ea_adc3 ___________________________ self = def test_ea_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ea_H2O.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.03542985, 0.05793028, 0.17397411, 0.19669173, 0.2226423 , 0.23145509, 0.29071277, 0.33149575, 0.38581... -8.68924073e-19, -2.13267016e-04, 1.33174061e-18, 2.39304666e-17, 7.56687197e-19, 8.59315356e-19]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ea_adc2 ___________________________ self = def test_ea_adc2(self): e, t_amp1, t_amp2 = myadc.kernel_gs() self.assertAlmostEqual(e, -0.32201692499346535, 6) dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 39.23226380360857, 6) myadcea = adc.radc_ea.RADCEA(myadc) e,v,p,x = myadcea.kernel(nroots=3) self.assertAlmostEqual(e[0], 0.0961781923822576, 6) self.assertAlmostEqual(e[1], 0.1258326916409743, 6) self.assertAlmostEqual(e[2], 0.1380779405750178, 6) self.assertAlmostEqual(p[0], 1.9832854445007961, 6) self.assertAlmostEqual(p[1], 1.9634368668786559, 6) self.assertAlmostEqual(p[2], 1.9783719593912672, 6) > dm1_exc = myadcea.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ea_N2.py:74: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ea.py:914: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ea.py:955: in make_rdm1_eigenvectors rdm1[:nocc, :nocc] += 2 * einsum('a,a,IJ->IJ', L1, R1, kd_oc, optimize = einsum_type) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'a,a,IJ->IJ' tensors = [array([-9.95382886e-01, -6.18036566e-15, 1.40434590e-16, -4.84124405e-14, -7.24127983e-17, 5.21955931e-16, -..., 0.], [0., 0., 0., 0., 1., 0., 0.], [0., 0., 0., 0., 0., 1., 0.], [0., 0., 0., 0., 0., 0., 1.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'a,a->', ['IJ', '']), ((1, 0), ',IJ->IJ', ['IJ'])] contraction = ((1, 0), 'a,a->', ['IJ', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ea_adc2x ___________________________ self = def test_ea_adc2x(self): myadc.method = "adc(2)-x" myadc.method_type = "ea" myadc.kernel_gs() dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 39.23226380360857, 6) myadcea = adc.radc_ea.RADCEA(myadc) e,v,p,x = myadcea.kernel(nroots=4) e_corr = myadc.e_corr self.assertAlmostEqual(e_corr, -0.32201692499346535, 6) self.assertAlmostEqual(e[0], 0.0953065329895602, 6) self.assertAlmostEqual(e[1], 0.1238833071439568, 6) self.assertAlmostEqual(e[2], 0.1365693813556231, 6) self.assertAlmostEqual(e[3], 0.1365693813556253, 6) self.assertAlmostEqual(p[0],1.9781770712894666, 6) self.assertAlmostEqual(p[1],1.9515196916710356, 6) self.assertAlmostEqual(p[2],1.9689940350592570, 6) self.assertAlmostEqual(p[3],1.9689940350592559, 6) > dm1_exc = myadcea.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ea_N2.py:114: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ea.py:914: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ea.py:955: in make_rdm1_eigenvectors rdm1[:nocc, :nocc] += 2 * einsum('a,a,IJ->IJ', L1, R1, kd_oc, optimize = einsum_type) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'a,a,IJ->IJ' tensors = [array([-9.93973598e-01, 5.79434735e-13, -2.50605700e-14, -3.98052496e-14, 2.68367926e-16, 5.93753388e-16, -..., 0.], [0., 0., 0., 0., 1., 0., 0.], [0., 0., 0., 0., 0., 1., 0.], [0., 0., 0., 0., 0., 0., 1.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'a,a->', ['IJ', '']), ((1, 0), ',IJ->IJ', ['IJ'])] contraction = ((1, 0), 'a,a->', ['IJ', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ea_adc3 ___________________________ self = def test_ea_adc3(self): myadc.method = "adc(3)" myadc.method_type = "ea" > myadc.kernel_gs() pyscf/adc/test/test_radc/test_ea_N2.py:125: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.1038212 , 0.12440987, 0.12440987, 0.14018851, 0.15039055, 0.15039055, 0.19616822, 0.25300864, 0.25300... -5.06972160e-18, 3.91752490e-17, -9.30673732e-19, 9.46671232e-18, -1.31185699e-17, 1.81213866e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ee_H2O.py:96: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355904, 1.20037149, 1.25336256, 1.44422514, 1.47634...7.21163337e-18, -2.58274411e-04, 6.21162328e-18, -3.75315213e-19, -1.44369249e-18, 9.29642677e-19]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ee_N2.py:75: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.1038212 , 0.12440987, 0.12440987, 0.14018851, 0.15039055, 0.15039055, 0.19616822, 0.25300864, 0.25300... -4.16229972e-18, -4.56394270e-18, 1.46196613e-18, -3.56883192e-17, 8.76441826e-17, -1.72826245e-19]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ee_df_H2O.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355904, 1.20037149, 1.25336256, 1.44422514, 1.47634...7.52839767e-18, -2.33315451e-04, -1.78577468e-18, -3.57358544e-19, 3.30671324e-20, 3.14751240e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ee_df_N2.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.1038212 , 0.12440987, 0.12440987, 0.14018851, 0.15039055, 0.15039055, 0.19616822, 0.25300864, 0.25300... -1.24101741e-17, -1.07295412e-17, -4.72573280e-18, 2.67301130e-17, 1.94760534e-17, -4.52782234e-19]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" myadc.max_memory = 20 myadc.incore_complete = False > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ee_outcore_H2O.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355904, 1.20037149, 1.25336256, 1.44422514, 1.47634...1.60894937e-17, -2.58274411e-04, -4.77853109e-19, -3.34715342e-20, 2.03667965e-18, -2.71384221e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc2 ___________________________ self = def test_ip_adc2(self): e, t_amp1, t_amp2 = myadc.kernel_gs() self.assertAlmostEqual(e, -0.2039852016968376, 6) dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 19.073700043115412, 6) myadcip = adc.radc_ip.RADCIP(myadc) e,v,p,x = myadcip.kernel(nroots=3) self.assertAlmostEqual(e[0], 0.4034634878946100, 6) self.assertAlmostEqual(e[1], 0.4908881395275673, 6) self.assertAlmostEqual(e[2], 0.6573303400764507, 6) self.assertAlmostEqual(p[0], 1.8162558898737797, 6) self.assertAlmostEqual(p[1], 1.8274312312239454, 6) self.assertAlmostEqual(p[2], 1.8582314560275948, 6) > dm1_exc = myadcip.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_H2O.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ip.py:791: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ip.py:832: in make_rdm1_eigenvectors rdm1[:nocc,:nocc] = 2*einsum('ij,m,m->ij',kd_oc,L1,R1,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ij,m,m->ij' tensors = [array([[1., 0., 0., 0., 0.], [0., 1., 0., 0., 0.], [0., 0., 1., 0., 0.], [0., 0., 0., 1., 0.], ...-9.58770042e-01]), array([ 6.90939920e-17, 9.09523352e-18, -2.40883120e-16, 6.91925034e-16, -9.58770042e-01])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'm,m->', ['ij', '']), ((1, 0), ',ij->ij', ['ij'])] contraction = ((2, 1), 'm,m->', ['ij', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ip_adc2x ___________________________ self = def test_ip_adc2x(self): myadc.method = "adc(2)-x" e, t_amp1, t_amp2 = myadc.kernel_gs() self.assertAlmostEqual(e, -0.2039852016968376, 6) dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 19.073700043115412, 6) myadcip = adc.radc_ip.RADCIP(myadc) e,v,p,x = myadcip.kernel(nroots=3) self.assertAlmostEqual(e[0], 0.4085610789192171, 6) self.assertAlmostEqual(e[1], 0.4949784593692911, 6) self.assertAlmostEqual(e[2], 0.6602619900185128, 6) self.assertAlmostEqual(p[0], 1.8296221555740104, 6) self.assertAlmostEqual(p[1], 1.8381884804163264, 6) self.assertAlmostEqual(p[2], 1.8669268953278064, 6) > dm1_exc = myadcip.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_H2O.py:104: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ip.py:791: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ip.py:832: in make_rdm1_eigenvectors rdm1[:nocc,:nocc] = 2*einsum('ij,m,m->ij',kd_oc,L1,R1,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ij,m,m->ij' tensors = [array([[1., 0., 0., 0., 0.], [0., 1., 0., 0., 0.], [0., 0., 1., 0., 0.], [0., 0., 0., 1., 0.], ...-9.62348371e-01]), array([-3.80108049e-19, 4.34959366e-17, -2.79270784e-16, 3.42140193e-18, -9.62348371e-01])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'm,m->', ['ij', '']), ((1, 0), ',ij->ij', ['ij'])] contraction = ((2, 1), 'm,m->', ['ij', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_H2O.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355904, 1.20037149, 1.25336256, 1.44422514, 1.47634...6.06569029e-18, -2.58274411e-04, -6.34129677e-18, -8.04674353e-19, -5.56069973e-19, -2.65420983e-19]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc2 ___________________________ self = def test_ip_adc2(self): e, t_amp1, t_amp2 = myadc.kernel_gs() self.assertAlmostEqual(e, -0.32201692499346535, 6) dm1_gs = myadc.make_ref_rdm1() r2_gs = rdms_test(dm1_gs) self.assertAlmostEqual(r2_gs, 39.23226380360857, 6) myadcip = adc.radc_ip.RADCIP(myadc) e,v,p,x = myadcip.kernel(nroots=3) self.assertAlmostEqual(e[0], 0.5434389910483670, 6) self.assertAlmostEqual(e[1], 0.6240296243595950, 6) self.assertAlmostEqual(e[2], 0.6240296243595956, 6) self.assertAlmostEqual(p[0], 1.7688097076459075, 6) self.assertAlmostEqual(p[1], 1.8192921131700284, 6) self.assertAlmostEqual(p[2], 1.8192921131700293, 6) > dm1_exc = myadcip.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_N2.py:75: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ip.py:791: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ip.py:832: in make_rdm1_eigenvectors rdm1[:nocc,:nocc] = 2*einsum('ij,m,m->ij',kd_oc,L1,R1,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ij,m,m->ij' tensors = [array([[1., 0., 0., 0., 0., 0., 0.], [0., 1., 0., 0., 0., 0., 0.], [0., 0., 1., 0., 0., 0., 0.], ...317e-04, 1.50091196e-15, -3.28268068e-02, 5.84395159e-16, 9.47099200e-01, -8.46362268e-16, -2.51099427e-14])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'm,m->', ['ij', '']), ((1, 0), ',ij->ij', ['ij'])] contraction = ((2, 1), 'm,m->', ['ij', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ip_adc2x ___________________________ self = def test_ip_adc2x(self): myadc.method = "adc(2)-x" e, t_amp1, t_amp2 = myadc.kernel_gs() myadcip = adc.radc_ip.RADCIP(myadc) e,v,p,x = myadcip.kernel(nroots=3) e_corr = myadc.e_corr self.assertAlmostEqual(e_corr, -0.32201692499346535, 6) self.assertAlmostEqual(e[0], 0.5405255360673243, 6) self.assertAlmostEqual(e[1], 0.6208026698756092, 6) self.assertAlmostEqual(e[2], 0.6208026698756107, 6) self.assertAlmostEqual(p[0], 1.7513284912002309, 6) self.assertAlmostEqual(p[1], 1.8152869633769022, 6) self.assertAlmostEqual(p[2], 1.8152869633769015, 6) > dm1_exc = myadcip.make_rdm1() ^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_N2.py:107: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc_ip.py:791: in make_rdm1 rdm1 = make_rdm1_eigenvectors(adc, U[:,i], U[:,i]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ip.py:832: in make_rdm1_eigenvectors rdm1[:nocc,:nocc] = 2*einsum('ij,m,m->ij',kd_oc,L1,R1,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ij,m,m->ij' tensors = [array([[1., 0., 0., 0., 0., 0., 0.], [0., 1., 0., 0., 0., 0., 0.], [0., 0., 1., 0., 0., 0., 0.], ...188e-04, 9.79583013e-16, -4.38376237e-02, 3.05146877e-15, 9.41949214e-01, -1.81603958e-15, -2.19358369e-14])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'm,m->', ['ij', '']), ((1, 0), ',ij->ij', ['ij'])] contraction = ((2, 1), 'm,m->', ['ij', '']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.method = "adc(3)" myadc.method_type = "ip" > myadc.kernel_gs() pyscf/adc/test/test_radc/test_ip_N2.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.1038212 , 0.12440987, 0.12440987, 0.14018851, 0.15039055, 0.15039055, 0.19616822, 0.25300864, 0.25300... -1.09039310e-18, -6.58341691e-17, 4.73765297e-19, -3.97120561e-17, -3.59153827e-17, 3.20282685e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_cvs_H2O.py:90: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355904, 1.20037149, 1.25336256, 1.44422514, 1.47634...8.89099330e-18, -2.58274411e-04, 8.41624576e-18, 6.81331614e-19, 1.63156103e-18, -1.05327167e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.ncvs = 2 myadc.method = "adc(3)" myadc.method_type = "ip" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_cvs_N2.py:89: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.1038212 , 0.12440987, 0.12440987, 0.14018851, 0.15039055, 0.15039055, 0.19616822, 0.25300864, 0.25300... -3.31059149e-18, -2.81562510e-17, 1.59442848e-18, 4.83081084e-17, -2.70361319e-17, 3.68937420e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_dfadc3_ip __________________________ self = def test_dfadc3_ip(self): myadc = adc.ADC(mf).density_fit(auxbasis='cc-pvdz-ri') myadc.conv_tol = 1e-12 myadc.tol_residual = 1e-6 myadc.max_memory = 1 myadc.method = "adc(3)" myadc.method_type = "ip" > e,v,p,x = myadc.kernel(nroots=3) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_ea_df_N2.py:68: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:384: in kernel self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.17542205, 0.17542205, 0.59444205, 0.82047386, 0.87257422, 0.87257422, 0.99238047, 1.051108 , 1.05110... -1.70303953e-17, -7.21331447e-18, -5.83764374e-18, -1.74025881e-17, -1.17147125e-17, 2.52829134e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.max_memory = 20 myadc.incore_complete = False myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_radc/test_ip_outcore_H2O.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:342: in kernel_gs self.e_corr, self.t1, self.t2 = radc_amplitudes.compute_amplitudes_energy( pyscf/adc/radc_amplitudes.py:36: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_amplitudes.py:166: in compute_amplitudes t1_3 = lib.einsum('d,ilad,ld->ia',e[nocc:],t2_1[:],t1_2,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355904, 1.20037149, 1.25336256, 1.44422514, 1.47634...1.22111959e-18, -2.58274411e-04, -6.12909680e-18, 6.07542000e-19, 2.64530958e-18, 1.43531365e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" myadc.approx_trans_moments = True myadc.compute_spin_square = True > e,v,p,x = myadc.kernel(nroots=5) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_approx_trans_moments_CN.py:60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 8.37401867e-06, 1.19051531e-04, -3.30357608e-19, -6.78225378e-07, -9.64217696e-06, 3.67869860e-19,...00, 8.76162033e-18, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ea_adc3 ___________________________ self = def test_ea_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ea_N2.py:92: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:351: in kernel_gs self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.1038212 , 0.12440987, 0.12440987, 0.14018851, 0.15039055, 0.15039055, 0.19616822, 0.25300864, 0.25300... 5.26433205e-19, 5.55055521e-17, 7.17335480e-19, 1.08447374e-16, 6.54520278e-17, 9.56475117e-19]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ea_adc3 ___________________________ self = def test_ea_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ea_OH.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:351: in kernel_gs self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.03572255, 0.17825976, 0.18513538, 0.19802999, 0.22577484, 0.31678394, 0.38649732, 0.39685198, 0.62621... 4.51701661e-19, 2.90314762e-19, -5.83462240e-19, 4.66092369e-18, -3.02844045e-04, -1.03326422e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ea_adc3 ___________________________ self = def test_ea_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ea_P.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:351: in kernel_gs self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.08816404, 0.101011 , 0.101011 , 0.101011 , 0.25828265, 0.25828265, 0.25828265, 0.25828265, 0.25828... 2.27057420e-17, -2.46850653e-16, 2.23513864e-16, 2.40450094e-16, -3.87330660e-17, -1.44577392e-16]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_CN.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 8.11165343e-06, 1.19069695e-04, -7.37495778e-20, -6.56975992e-07, -9.64364810e-06, 2.69866646e-20,...00, -6.28916309e-17, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_CN.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 1.68084166e-05, 9.27365707e-05, 2.50710202e-20, -1.38525357e-06, -7.64281781e-06, -2.60121753e-20,...00, -6.28916309e-17, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_CN.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18653855, 0.18653855, 0.37141653, 0.61849421, 0.61849421, 0.64743078, 0.87480923, 1.02434277, 1.06878... -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, 1.38289228e-03, -0.00000000e+00]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_F2.py:60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 4.37013804e-18, -2.19030365e-18, 1.99866357e-04, 4.76784434e-05, -2.21882190e-18, 4.93896103e-15,...18, -2.29266460e-33, ..., -2.67669302e-34, -6.42406325e-33, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_F2.py:75: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 5.07635391e-18, -2.12602418e-18, -3.65301717e-05, 1.93476302e-04, -2.49612259e-18, 3.94860197e-15,...18, -2.29266460e-33, ..., -2.67669302e-34, -6.42406325e-33, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_F2.py:90: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.48348447, 1.31337867, 1.35127956, 1.35127956, 1.46235713, 1.49107716, 1.49107716, 1.72328568, 2.50640...6.07851977e-18, 2.33743582e-18, 2.94469277e-19, 7.76438013e-05, -1.99475665e-04, 2.78533986e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_H2O.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-1.48362450e-19, 3.41729073e-20, -2.16792247e-19, 9.14793082e-20, -4.67286991e-18, -3.37907377e-04,...19, -1.60174260e-18, ..., -1.24704205e-18, -4.29795821e-18, -0.00000000e+00]]]], shape=(5, 5, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_H2O.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-2.25631681e-19, 4.96362240e-20, -2.02143752e-19, 2.32210680e-19, -4.50148848e-18, -3.22559984e-04,...19, -1.60174260e-18, ..., -1.24704205e-18, -4.29795821e-18, -0.00000000e+00]]]], shape=(5, 5, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_H2O.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355905, 1.20037151, 1.25336256, 1.44422514, 1.47634...4.35621668e-19, -2.58274468e-04, -6.36756376e-19, -3.24055905e-18, 3.18405744e-18, 2.86049625e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_O2.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 6.16447413e-19, 0.00000000e+00, 0.00000000e+00, 3.00757211e-19, -5.98449520e-23, 0.00000000e+00,...00, -0.00000000e+00, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_O2.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-3.74162151e-18, 0.00000000e+00, 0.00000000e+00, -2.97727587e-18, -2.05921549e-20, 0.00000000e+00,...00, -0.00000000e+00, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_O2.py:103: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.41743463, 1.05419707, 1.05419707, 1.06347941, 1.14910175, 1.16428322, 1.16428322, 1.3171613 , 1.94356...0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -1.36032455e-03, -0.00000000e+00]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_OH.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0.00000000e+00, 0.00000000e+00, -2.30332674e-19, 0.00000000e+00, 1.29343435e-19, -1.63717330e-20,...19, -0.00000000e+00, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_OH.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0.00000000e+00, 0.00000000e+00, -4.41135136e-19, 0.00000000e+00, -2.67136077e-19, -2.33075725e-20,...19, -0.00000000e+00, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_OH.py:103: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18481584, 0.79337126, 1.10173917, 1.1478373 , 1.16345632, 1.51463357, 1.5361072 , 1.63993348, 2.38073...0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -3.56017399e-04, -0.00000000e+00]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_CN.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 1.13067231e-04, 3.82999970e-05, 2.19114817e-19, -9.11706510e-06, -3.08828263e-06, -1.71597295e-19,...00, -3.60066589e-18, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_CN.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 9.38563924e-05, 8.43785426e-06, 2.72701841e-19, -7.71061703e-06, -6.93197992e-07, -1.51892740e-19,...00, -3.60066589e-18, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_CN.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18653855, 0.18653855, 0.37141653, 0.61849421, 0.61849421, 0.64743078, 0.87480923, 1.02434277, 1.06878... -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, 1.37643384e-03, -0.00000000e+00]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_F2.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 1.60608220e-18, 9.90969455e-20, -1.09790405e-04, -1.73715734e-04, -5.30934701e-19, -4.15967546e-15,...19, 3.05688613e-33, ..., 4.28270883e-33, -0.00000000e+00, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_F2.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 6.22319148e-19, 1.70651200e-18, -1.95363214e-04, 2.46789533e-05, 5.97410186e-19, 1.13578327e-15,...19, 3.05688613e-33, ..., 4.28270883e-33, -0.00000000e+00, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_F2.py:91: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.48348447, 1.31337867, 1.35127956, 1.35127956, 1.46235713, 1.49107716, 1.49107716, 1.72328568, 2.50640...2.85706520e-17, -3.05890318e-20, 1.47570653e-17, 1.84341513e-04, 7.66411563e-05, 3.47971117e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_H2O.py:65: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 3.69033004e-19, -2.19354802e-19, 7.11807597e-20, -1.06011376e-18, 7.62599675e-19, -3.38390274e-04,...20, -9.15281488e-20, ..., -2.89100319e-19, -5.86152942e-19, -0.00000000e+00]]]], shape=(5, 5, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_H2O.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 6.80106119e-19, -1.80349203e-19, 5.98689132e-20, -1.49329651e-18, 7.49108292e-19, -3.23062040e-04,...20, -9.15281488e-20, ..., -2.89100319e-19, -5.86152942e-19, -0.00000000e+00]]]], shape=(5, 5, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_H2O.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355905, 1.20037151, 1.25336256, 1.44422514, 1.47634...3.38949872e-18, -2.33315507e-04, 8.56240241e-18, 1.85591085e-19, -2.15045097e-18, -1.12828589e-18]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_O2.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 6.53859316e-20, 0.00000000e+00, 0.00000000e+00, 4.62368806e-19, -2.26777817e-23, 0.00000000e+00,...00, -0.00000000e+00, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_O2.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-3.79614172e-19, 0.00000000e+00, 0.00000000e+00, -9.65411739e-20, -1.24237449e-20, 0.00000000e+00,...00, -0.00000000e+00, ..., -0.00000000e+00, -0.00000000e+00, -0.00000000e+00]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_O2.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.41743463, 1.05419707, 1.05419707, 1.06347941, 1.14910175, 1.16428322, 1.16428322, 1.3171613 , 1.94356...0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -1.35208675e-03, -0.00000000e+00]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_OH.py:62: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0. , 0. , 0. , 0. , 0. , 0. , -0. , 0. , 0. ... , 0. , -0. , 0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_OH.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0. , 0. , 0. , 0. , 0. , 0. , -0. , 0. , 0. ... , 0. , -0. , 0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_OH.py:104: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18481584, 0.79337126, 1.10173917, 1.1478373 , 1.16345632, 1.51463357, 1.5361072 , 1.63993348, 2.38073749, 2.... , 0.00222695, -0. , -0. , -0. , -0. , -0. , -0.00033478, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.42081668, 1.06124929, 1.06124929, 1.06301253, 1.14760047, 1.17060333, 1.17060333, 1.31330548, 1.9441965 , 2.... , 0. , 0. , -0. , -0. , 0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.42081668, 1.06124929, 1.06124929, 1.06301253, 1.14760047, 1.17060333, 1.17060333, 1.31330548, 1.9441965 , 2.... , 0. , 0. , -0. , -0. , 0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.42081668, 1.06124929, 1.06124929, 1.06301253, 1.14760047, 1.17060333, 1.17060333, 1.31330548, 1.9441965 , 2.... , 0. , 0. , -0. , -0. , 0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , -0. , -0. , -0. , 0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , -0. , -0. , -0. , 0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py:103: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , -0. , -0. , -0. , 0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_F2.py:63: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0. , -0. , 0.0001653 , 0.00012204, -0. , -0. , -0. , -0. , 0. ... , 0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" myadc.max_memory = 20 myadc.incore_complete = False myadcee = adc.uadc_ee.UADCEE(myadc) > e,v,p,x = myadcee.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_F2.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-0. , -0. , 0.00004544, -0.00019158, 0. , 0. , 0. , -0. , -0. ... , 0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" myadc.max_memory = 20 myadc.incore_complete = False myadcee = adc.uadc_ee.UADCEE(myadc) > e,v,p,x = myadcee.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_F2.py:99: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:70: in kernel imds = adc.get_imds(eris) ^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:743: in get_imds a:a + k] += -lib.einsum('AaDb,Ia,Lb->IDLA', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'AaDb,Ia,Lb->IDLA' tensors = [array([[[[ 0. , -0. , -0. , -0. , 0. , 0. , 0. , -0. , -0....0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'Ia,AaDb->AIDb', ['Lb', 'AIDb']), ((1, 0), 'AIDb,Lb->IDLA', ['IDLA'])] contraction = ((1, 0), 'Ia,AaDb->AIDb', ['Lb', 'AIDb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.max_memory = 20 myadc.incore_complete = False myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py:66: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-0. , -0. , -0. , 0. , 0. , -0.00033791, -0. , -0. , -0. ... , 0. , -0. , -0. , 0. , 0. , -0. ]]]], shape=(5, 5, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-0. , -0. , -0. , 0. , 0. , -0.00032256, -0. , -0. , -0. ... , 0. , -0. , -0. , 0. , 0. , -0. ]]]], shape=(5, 5, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py:100: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18551955, 0.25622245, 0.78898811, 0.8543069 , 1.16355905, 1.20037151, 1.25336256, 1.44422514, 1.47634541, 1.... 0. , 0. , -0. , -0. , -0.00025827, -0. , -0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_O2.py:62: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[-0. , 0. , 0. , -0. , 0. , 0. , 0. , -0. , 0. ... , -0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_O2.py:85: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , -0. , -0. ... , -0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_O2.py:108: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.41743463, 1.05419707, 1.05419707, 1.06347941, 1.14910175, 1.16428322, 1.16428322, 1.3171613 , 1.94356068, 2....-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0.00136032, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_OH.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ... , -0. , -0. , -0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_OH.py:87: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:402: in kernel e_exc, v_exc, spec_fac, X, adc_es = self.ee_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:433: in ee_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc.py:83: in kernel adc.P,adc.X = adc.get_properties(nroots) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:22987: in get_properties X = adc.get_trans_moments() ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_ee.py:20485: in get_trans_moments :nocc_a] += lib.einsum('xg,ph,qxgh->pq', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xg,ph,qxgh->pq' tensors = [array([[ 0. , 0. , 0. , 0. , -0. , 0. , -0. , 0. , 0. ... , -0. , -0. , -0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qxgh,xg->qh', ['ph', 'qh']), ((1, 0), 'qh,ph->pq', ['pq'])] contraction = ((2, 0), 'qxgh,xg->qh', ['ph', 'qh']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_OH.py:110: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18481584, 0.79337126, 1.10173917, 1.1478373 , 1.16345632, 1.51463357, 1.5361072 , 1.63993348, 2.38073749, 2.... , 0.00221214, -0. , -0. , -0. , -0. , -0. , -0.00035602, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py:63: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , -0. , 0. , 0. , 0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py:86: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , -0. , 0. , 0. , 0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" myadc.max_memory = 20 myadc.incore_complete = False > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py:109: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , -0. , 0. , 0. , 0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_CN.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.15783317, 0.15783317, 0.37264976, 0.64619524, 0.64619524, 0.6506721 , 0.86524533, 1.02287537, 1.03266908, 1.... , -0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_CN.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.15783317, 0.15783317, 0.37264976, 0.64619524, 0.64619524, 0.6506721 , 0.86524533, 1.02287537, 1.03266908, 1.... , -0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_CN.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.15783317, 0.15783317, 0.37264976, 0.64619524, 0.64619524, 0.6506721 , 0.86524533, 1.02287537, 1.03266908, 1.... , -0. , 0. , 0. , -0. , -0. , -0. ]]]], shape=(7, 7, 21, 21))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_O2.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.42081668, 1.06124929, 1.06124929, 1.06301253, 1.14760047, 1.17060333, 1.17060333, 1.31330548, 1.9441965 , 2.... , 0. , -0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_O2.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.42081668, 1.06124929, 1.06124929, 1.06301253, 1.14760047, 1.17060333, 1.17060333, 1.31330548, 1.9441965 , 2.... , 0. , -0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_O2.py:103: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.42081668, 1.06124929, 1.06124929, 1.06301253, 1.14760047, 1.17060333, 1.17060333, 1.31330548, 1.9441965 , 2.... , 0. , -0. , 0. , -0. , -0. , -0. ]]]], shape=(9, 9, 19, 19))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc2 ___________________________ self = def test_ee_adc2(self): myadc.method = "adc(2)" myadc.method_type = "ee" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_OH.py:60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , 0. , 0. , -0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ee_adc2x ___________________________ self = def test_ee_adc2x(self): myadc.method = "adc(2)-x" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_OH.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , 0. , 0. , -0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ee_adc3 ___________________________ self = def test_ee_adc3(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ee_rohf_OH.py:102: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:171: in compute_amplitudes t1_2_a += lib.einsum('d,ld,ilad->ia',e_a[nocc_a:],t1_1_a,t2_1_a[:], optimize = True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ld,ilad->ia' tensors = [array([0.18536192, 0.78926901, 1.10434428, 1.14952402, 1.16624281, 1.51194642, 1.53244472, 1.64178251, 2.38089199, 2.... , 0. , 0. , -0. , -0. , -0. , -0. ]]]], shape=(5, 5, 14, 14))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ilad,ld->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ilad,ld->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_OH.py:85: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:351: in kernel_gs self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.03572255, 0.17825976, 0.18513538, 0.19802999, 0.22577484, 0.31678394, 0.38649732, 0.39685198, 0.62621292, 0.... , 0.00088499, -0. , 0. , -0. , -0. , -0. , -0.00030284, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_ip_adc3_oneroot _______________________ self = def test_ip_adc3_oneroot(self): myadc.method = "adc(3)" > e,v,p,x = myadc.kernel() ^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_OH.py:103: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.03572255, 0.17825976, 0.18513538, 0.19802999, 0.22577484, 0.31678394, 0.38649732, 0.39685198, 0.62621292, 0.... , 0.00088499, -0. , 0. , -0. , -0. , -0. , -0.00030284, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.method = "adc(3)" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_P.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:351: in kernel_gs self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.08816404, 0.101011 , 0.101011 , 0.101011 , 0.25828265, 0.25828265, 0.25828265, 0.25828265, 0.25828265, 0....981, -0.00021255, 0.0002875 , 0. , -0. , 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ip_adc3 ___________________________ self = def test_ip_adc3(self): myadc.ncvs = 1 myadc.method = "adc(3)" myadc.method_type = "ip" > e, t_amp1, t_amp2 = myadc.kernel_gs() ^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_cvs_OH.py:90: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:351: in kernel_gs self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.03572255, 0.17825976, 0.18513538, 0.19802999, 0.22577484, 0.31678394, 0.38649732, 0.39685198, 0.62621292, 0.... , 0.00088499, 0. , -0. , 0. , -0. , 0. , -0.00030284, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ea_dfadc3 __________________________ self = def test_ea_dfadc3(self): mf = scf.UHF(mol).density_fit(auxbasis='cc-pvdz-jkfit') mf.kernel() myadc.with_df = df.DF(mol, auxbasis='cc-pvdz-ri') myadc.max_memory = 1 myadc.method = "adc(3)" myadc.method_type = "ea" > e,v,p,x = myadc.kernel(nroots=4) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18492883, 0.79396516, 1.10183799, 1.14778667, 1.16354738, 1.51546357, 1.53690947, 1.64010687, 2.38257865, 2.... , 0.0022246 , -0. , -0. , 0. , -0. , 0. , -0.00033448, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_hf_dfadc3_ip _________________________ self = def test_hf_dfadc3_ip(self): mf = scf.UHF(mol).run() myadc = adc.ADC(mf) myadc.conv_tol = 1e-12 myadc.tol_residual = 1e-6 myadc.with_df = df.DF(mol, auxbasis='aug-cc-pvdz-ri') myadc.method = "adc(3)" > e,v,p,x = myadc.kernel(nroots=3) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py:124: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18492844, 0.79395941, 1.10175372, 1.14766941, 1.16347429, 1.51472695, 1.53622436, 1.63996627, 2.38233663, 2.... , 0.00222455, 0. , -0. , 0. , 0. , 0. , -0.00033897, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_ip_dfadc3_dif_aux_basis ___________________ self = def test_ip_dfadc3_dif_aux_basis(self): mf = scf.UHF(mol).density_fit(auxbasis='cc-pvdz-jkfit') mf.kernel() myadc.with_df = df.DF(mol, auxbasis='aug-cc-pvdz-ri') myadc.max_memory = 1 myadc.method = "adc(3)" myadc.method_type = "ip" > e,v,p,x = myadc.kernel(nroots=3) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/uadc.py:393: in kernel self.e_corr, self.t1, self.t2 = uadc_amplitudes.compute_amplitudes_energy( pyscf/adc/uadc_amplitudes.py:37: in compute_amplitudes_energy t1, t2, myadc.imds.t2_1_vvvv = myadc.compute_amplitudes(eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/uadc_amplitudes.py:496: in compute_amplitudes t1_3_a = lib.einsum('d,ilad,ld->ia',e_a[nocc_a:],t2_1_a[:],t1_2_a,optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'd,ilad,ld->ia' tensors = [array([0.18492883, 0.79396516, 1.10183799, 1.14778667, 1.16354738, 1.51546357, 1.53690947, 1.64010687, 2.38257865, 2.... , 0.00222305, -0. , -0. , 0. , -0. , 0. , -0.0003387 , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'ld,ilad->iad', ['d', 'iad']), ((1, 0), 'iad,d->ia', ['ia'])] contraction = ((2, 1), 'ld,ilad->iad', ['d', 'iad']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_incore ____________________________ self = def test_incore(self): numpy.random.seed(15) nmo = 12 mo = numpy.random.random((nao,nmo)) eriref = trans(eri, [mo]*4) eri1 = ao2mo.incore.full(ao2mo.restore(8,eri,nao), mo) self.assertTrue(numpy.allclose(ao2mo.restore(1,eri1,nmo), eriref)) eri1 = ao2mo.incore.full(ao2mo.restore(4,eri,nao), mo, compact=False) self.assertTrue(numpy.allclose(eri1.reshape((nmo,)*4), eriref)) eri1 = ao2mo.incore.general(eri, (mo[:,:2], mo[:,1:3], mo[:,:3], mo[:,2:5])) eri1 = eri1.reshape(2,2,3,3) self.assertTrue(numpy.allclose(eri1, eriref[:2,1:3,:3,2:5])) # eri_ao = ao2mo.restore('s2ij', eri, nao) # eri1 = ao2mo.incore.general(eri_ao, (mo[:,:3], mo[:,1:3], mo[:,:3], mo[:,2:5])) # eri1 = eri1.reshape(3,2,3,3) # self.assertTrue(numpy.allclose(eri1, eriref[:3,1:3,:3,2:5])) eri_ao = ao2mo.restore(1, eri, nao) > eri1 = ao2mo.incore.general(eri_ao, (mo[:,:3], mo[:,1:3], mo[:,:3], mo[:,2:5])) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/test/test_incore.py:73: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 4.73826792, -1.60036294, 0.59611165, 0. , 0. , 0. , 0. , 0. , 0....6, 0.31172871, 0.65006592], [0.92836599, 0.31155852, 0.25064276], [0.3927244 , 0.89143354, 0.47387735]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,pqrs->jprs', ['pi', 'rk', 'sl', 'jprs']), ((3, 0), 'jprs,pi->jirs', ['rk', 'sl', 'jirs']), ((2, 0), 'jirs,rk->jiks', ['sl', 'jiks']), ((1, 0), 'jiks,sl->ijkl', ['ijkl'])] contraction = ((2, 0), 'qj,pqrs->jprs', ['pi', 'rk', 'sl', 'jprs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_nrr_ghf ___________________________ self = def test_nrr_ghf(self): mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.basis = '631g' mol.build() mf = mol.GHF().run() nao = mol.nao nmo = mf.mo_coeff.shape[1] mo_a = mf.mo_coeff[:nao] mo_b = mf.mo_coeff[nao:] eri0 = mol.intor('int2e_sph') > eri1 = lib.einsum('pqrs,pi,qj->ijrs', eri0, mo_a.conj(), mo_a) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/test/test_nrr_outcore.py:41: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj->ijrs' tensors = [array([[[[ 4.78044571, 0.59837845, 0.53797322, 0. , 0. , 0. , 0. , 0. , 0.... , -0.38337104, -0.38337139, 0.0663796 , 0.06637687, 0.64368145, -0.64368142, 0.43336608, -0.43336612]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->qrsi', ['qj', 'qrsi']), ((1, 0), 'qrsi,qj->ijrs', ['ijrs'])] contraction = ((1, 0), 'pi,pqrs->qrsi', ['qj', 'qrsi']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_nrr_spinor __________________________ self = def test_nrr_spinor(self): mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' O 0. 0. 0. H 0. -0.757 0.587 H 0. 0.757 0.587''' mol.basis = '631g' mol.build() mf = mol.GHF().x2c().run() mo = mf.mo_coeff nao = mol.nao nmo = mf.mo_coeff.shape[1] mo_a = mf.mo_coeff[:nao] mo_b = mf.mo_coeff[nao:] eri0 = mol.intor('int2e_spinor') > ref = lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri0, mo.conj(), mo, mo.conj(), mo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/test/test_nrr_outcore.py:68: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 4.78044571+0.j , 0. +0.j , 0.59837845+0.j , 0. +0.j , 0.5379...227384j, -0.00068694-0.64375965j, 0.00068692-0.64375159j, -0.43328346-0.00025331j, -0.43327263+0.00023073j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_ao2mo_r_e2 __________________________ self = def test_ao2mo_r_e2(self): n2c = mol.nao_2c() numpy.random.seed(1) mo = numpy.random.random((n2c,n2c)) + numpy.random.random((n2c,n2c))*1j tao = numpy.asarray(mol.tmap(), dtype=numpy.int32) buf = ao2mo._ao2mo.r_e1('int2e_spinor', mo, (0,4,0,3), (0, 2, 8), mol._atm, mol._bas, mol._env, tao, 's1') buf = buf.reshape(8,12).T > ref = lib.einsum('pqkl,pi,qj->ijkl', eri0, mo[:,:4].conj(), mo[:,:3]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/test/test_r_outcore.py:97: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqkl,pi,qj->ijkl' tensors = [array([[[[ 4.78044571+0.j , 0. +0.j , 0.59837845+0.j , 0. +0.j , 0.5379....36598335j, 0.60095425+0.60430684j], [0.35706161+0.97867281j, 0.10806533+0.2363841j , 0.78755184+0.66059836j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,pqkl->jklp', ['pi', 'jklp']), ((1, 0), 'jklp,pi->ijkl', ['ijkl'])] contraction = ((2, 0), 'qj,pqkl->jklp', ['pi', 'jklp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnowValues.test_general ____________________________ self = def test_general(self): numpy.random.seed(15) nmo = 12 mo = numpy.random.random((nao,nmo)) eriref = ao2mo.incore.full(eri, mo) tmpfile = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR) io_size = nao**2*4e-5 > semi_incore.general(eri, [mo]*4, tmpfile.name, ioblk_size=io_size) pyscf/ao2mo/test/test_semi_incore.py:51: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/ao2mo/semi_incore.py:241: in general lo = lib.einsum('xpq,pi,qj->xij', lo, Cklam, mo_coeffs[3]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,pi,qj->xij' tensors = [array([[[ 8.36278444, 5.53159902, 2.85777204, 0.22412728, 0.21851484, 1.63115596, 2.81304869, 0.04519161, 0.0... 0.19843054, 0.45226602, 0.25276903, 0.81725646, 0.9508608 , 0.2622476 , 0.13324375, 0.16787213, 0.41039868]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,xpq->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'pi,xpq->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnowValues.test_general_complex ________________________ self = def test_general_complex(self): numpy.random.seed(15) nmo = 12 mo = numpy.random.random((nao,nmo)) + numpy.random.random((nao,nmo))*1j > eriref = lib.einsum('pqrs,pi,qj,rk,sl->ijkl', ao2mo.restore(1, eri, nao), mo.conj(), mo, mo.conj(), mo) pyscf/ao2mo/test/test_semi_incore.py:65: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[1.39303459, 0.82297073, 0.41125567, 0.01015586, 0.0085913 , 0.15510837, 0.36138886, 0. , 0. ,...0.07247963j, 0.2622476 +0.80802032j, 0.13324375+0.93649484j, 0.16787213+0.09295845j, 0.41039868+0.99115705j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ccsd _____________________________ self = def test_ccsd(self): mycc = cc.CCSD(mf) ecc = mycc.kernel()[0] norb = mf.mo_coeff.shape[1] nelec = mol.nelec h2e = ao2mo.restore(1, ao2mo.kernel(mf._eri, mf.mo_coeff), norb) h1e = reduce(numpy.dot, (mf.mo_coeff.T, mf.get_hcore(), mf.mo_coeff)) eci, civec = fci.direct_spin0.kernel(h1e, h2e, norb, nelec) dm1ref = fci.direct_spin0.make_rdm1(civec, norb, nelec) eci = eci + mol.energy_nuc() - mf.e_tot self.assertAlmostEqual(eci, ecc, 7) > l1, l2 = mycc.solve_lambda() ^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_2e.py:60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0. , -0.00000002, 0.00000003, 0.00000001, -0.00000002, -0. , 0.00000001]]), array([[ 0. ..., 0.0007304 ]]), array([[ 0. , 0.01814676, -0.00081904, -0.00206114, 0.00293629, 0. , 0.0007304 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_bccd_kernel_ _________________________ self = def test_bccd_kernel_(self): mybcc = addons.bccd_kernel_(myrcc) self.assertAlmostEqual(abs(mybcc.t1).max(), 0, 4) e_r = mybcc.e_tot myucc = addons.convert_to_uccsd(myrcc) > mybcc = addons.bccd_kernel_(myucc) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_addons.py:87: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/bccd.py:244: in bccd_kernel_ mycc.kernel(t1=t1, t2=t2) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0.00000003, -0. , 0. , -0. , -0.00000004, 0.00000001, 0. , -0.00000003], ...77, -0. , 0. , 0. , -0.00398328, -0.00414098, -0. , 0.04537292]]]], shape=(5, 8, 5, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_rdm _____________________________ self = def test_rdm(self): > dm1 = mycc.make_rdm1() ^^^^^^^^^^^^^^^^ pyscf/cc/test/test_ccd.py:50: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccd.py:62: in make_rdm1 if l2 is None: l2 = self.solve_lambda(t2) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccd.py:52: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0.00000001, 0. , -0. , 0. , 0. , -0.00000002, 0. , 0.00000002], ... [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ccsd _____________________________ self = def test_ccsd(self): mol = gto.M() mf = scf.RHF(mol) mcc = cc.CCSD(mf) numpy.random.seed(12) mcc.nocc = nocc = 5 mcc.nmo = nmo = 12 nvir = nmo - nocc eri0 = numpy.random.random((nmo,nmo,nmo,nmo)) eri0 = ao2mo.restore(1, ao2mo.restore(8, eri0, nmo), nmo) fock0 = numpy.random.random((nmo,nmo)) fock0 = fock0 + fock0.T + numpy.diag(range(nmo))*2 t1 = numpy.random.random((nocc,nvir)) t2 = numpy.random.random((nocc,nocc,nvir,nvir)) t2 = t2 + t2.transpose(1,0,3,2) l1 = numpy.random.random((nocc,nvir)) l2 = numpy.random.random((nocc,nocc,nvir,nvir)) l2 = l2 + l2.transpose(1,0,3,2) eris = cc.ccsd._ChemistsERIs() eris.oooo = eri0[:nocc,:nocc,:nocc,:nocc].copy() eris.ovoo = eri0[:nocc,nocc:,:nocc,:nocc].copy() eris.oovv = eri0[:nocc,:nocc,nocc:,nocc:].copy() eris.ovvo = eri0[:nocc,nocc:,nocc:,:nocc].copy() idx = numpy.tril_indices(nvir) eris.ovvv = eri0[:nocc,nocc:,nocc:,nocc:][:,:,idx[0],idx[1]].copy() eris.vvvv = ao2mo.restore(4,eri0[nocc:,nocc:,nocc:,nocc:],nvir) eris.fock = fock0 eris.mo_energy = fock0.diagonal() > saved = ccsd_lambda.make_intermediates(mcc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_ccsd_lambda.py:86: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[0.56583249, 0.8436779 , 1.48788121, 0.79782585, 0.49504429, 1.06631093, 1.22541398], [1.05912234, 0.22...0.62897697, 0.87648706], [0.48386851, 0.44236453, 0.37061368, 0.1690263 , 0.773672 , 0.77156898, 0.35141294]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_restart ___________________________ self = def test_restart(self): ftmp = tempfile.NamedTemporaryFile() cc1 = mycc.copy() cc1.max_cycle = 5 > cc1.solve_lambda() pyscf/cc/test/test_ccsd_lambda.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0., 0., 0., 0., 0., -0., 0.], [ 0., 0., -0., -0., -0., -0., -0., 0.], [ 0., -0., -...93], [ 0. , 0. , -0. , 0.0059843 , 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_ccsd_t_rdm __________________________ self = def test_ccsd_t_rdm(self): mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -.957 , .587)], [1 , (0.2, .757 , .487)]] mol.basis = '631g' mol.build() mf = scf.RHF(mol) mf.conv_tol = 1e-1 mf.scf() mcc = mf.CCSD() ecc, t1, t2 = mcc.kernel() eris = mcc.ao2mo() e3ref = ccsd_t.kernel(mcc, eris, t1, t2) > l1, l2 = ccsd_t_lambda.kernel(mcc, eris, t1, t2)[1:] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_ccsd_t.py:212: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_t_lambda_slow.py:35: in kernel return ccsd_lambda.kernel(mycc, eris, t1, t2, l1, l2, max_cycle, tol, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_t_lambda_slow.py:39: in make_intermediates imds = ccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0.00403889, 0.00135115, 0.00215778, 0. , 0.00296071, -0.00174766, 0.00074062, 0.00926526], ...77], [-0. , -0. , 0. , 0.02045946, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_df_eaccsd __________________________ self = def test_df_eaccsd(self): self.assertAlmostEqual(mycc.e_tot, -76.118403942938741, 6) > e,v = mycc.eaccsd(nroots=1) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfccsd.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1300: in eaccsd return eom_rccsd.EOMEA(self).kernel(nroots, left, koopmans, guess, pyscf/cc/eom_rccsd.py:615: in eaccsd return ipccsd(eom, nroots, left, koopmans, guess, partition, eris, imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:255: in ipccsd = kernel(eom, nroots, koopmans, guess, left, eris=eris, imds=imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:40: in kernel imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:958: in make_imds imds.make_ea(self.partition) pyscf/cc/eom_rccsd.py:1875: in make_ea self._make_shared_1e() pyscf/cc/eom_rccsd.py:1816: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:65: in Loo Lki = cc_Foo(t1, t2, eris) + np.einsum('kc,ic->ki',fov, t1) ^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01167438, -0. , -0. , 0. , -0.01608749, 0.00012266, 0. , -0.0208568 ], ...03], [ 0. , 0. , -0. , 0.00596681, 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_df_eaccsd_koopmans ______________________ self = def test_df_eaccsd_koopmans(self): > e,v = mycc.eaccsd(nroots=3, koopmans=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfccsd.py:147: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1300: in eaccsd return eom_rccsd.EOMEA(self).kernel(nroots, left, koopmans, guess, pyscf/cc/eom_rccsd.py:615: in eaccsd return ipccsd(eom, nroots, left, koopmans, guess, partition, eris, imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:255: in ipccsd = kernel(eom, nroots, koopmans, guess, left, eris=eris, imds=imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:40: in kernel imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:958: in make_imds imds.make_ea(self.partition) pyscf/cc/eom_rccsd.py:1875: in make_ea self._make_shared_1e() pyscf/cc/eom_rccsd.py:1816: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:65: in Loo Lki = cc_Foo(t1, t2, eris) + np.einsum('kc,ic->ki',fov, t1) ^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01167438, -0. , -0. , 0. , -0.01608749, 0.00012266, 0. , -0.0208568 ], ...03], [ 0. , 0. , -0. , 0.00596681, 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_df_eaccsd_partition _____________________ self = def test_df_eaccsd_partition(self): > e,v = mycc.eaccsd(nroots=3, partition='mp') ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfccsd.py:158: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1300: in eaccsd return eom_rccsd.EOMEA(self).kernel(nroots, left, koopmans, guess, pyscf/cc/eom_rccsd.py:615: in eaccsd return ipccsd(eom, nroots, left, koopmans, guess, partition, eris, imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:255: in ipccsd = kernel(eom, nroots, koopmans, guess, left, eris=eris, imds=imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:40: in kernel imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:958: in make_imds imds.make_ea(self.partition) pyscf/cc/eom_rccsd.py:1875: in make_ea self._make_shared_1e() pyscf/cc/eom_rccsd.py:1816: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:65: in Loo Lki = cc_Foo(t1, t2, eris) + np.einsum('kc,ic->ki',fov, t1) ^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01167438, -0. , -0. , 0. , -0.01608749, 0.00012266, 0. , -0.0208568 ], ...03], [ 0. , 0. , -0. , 0.00596681, 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_df_ipccsd __________________________ self = def test_df_ipccsd(self): > e,v = mycc.ipccsd(nroots=1) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfccsd.py:91: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1294: in ipccsd return eom_rccsd.EOMIP(self).kernel(nroots, left, koopmans, guess, pyscf/cc/eom_rccsd.py:255: in ipccsd = kernel(eom, nroots, koopmans, guess, left, eris=eris, imds=imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:40: in kernel imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:589: in make_imds imds.make_ip(self.partition) pyscf/cc/eom_rccsd.py:1839: in make_ip self._make_shared_1e() pyscf/cc/eom_rccsd.py:1816: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:65: in Loo Lki = cc_Foo(t1, t2, eris) + np.einsum('kc,ic->ki',fov, t1) ^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01167438, -0. , -0. , 0. , -0.01608749, 0.00012266, 0. , -0.0208568 ], ...03], [ 0. , 0. , -0. , 0.00596681, 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_df_ipccsd_koopmans ______________________ self = def test_df_ipccsd_koopmans(self): > e,v = mycc.ipccsd(nroots=3, koopmans=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfccsd.py:107: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1294: in ipccsd return eom_rccsd.EOMIP(self).kernel(nroots, left, koopmans, guess, pyscf/cc/eom_rccsd.py:255: in ipccsd = kernel(eom, nroots, koopmans, guess, left, eris=eris, imds=imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:40: in kernel imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:589: in make_imds imds.make_ip(self.partition) pyscf/cc/eom_rccsd.py:1839: in make_ip self._make_shared_1e() pyscf/cc/eom_rccsd.py:1816: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:65: in Loo Lki = cc_Foo(t1, t2, eris) + np.einsum('kc,ic->ki',fov, t1) ^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01167438, -0. , -0. , 0. , -0.01608749, 0.00012266, 0. , -0.0208568 ], ...03], [ 0. , 0. , -0. , 0.00596681, 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_df_ipccsd_partition _____________________ self = def test_df_ipccsd_partition(self): > e,v = mycc.ipccsd(nroots=3, partition='mp') ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_dfccsd.py:118: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1294: in ipccsd return eom_rccsd.EOMIP(self).kernel(nroots, left, koopmans, guess, pyscf/cc/eom_rccsd.py:255: in ipccsd = kernel(eom, nroots, koopmans, guess, left, eris=eris, imds=imds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:40: in kernel imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/cc/eom_rccsd.py:589: in make_imds imds.make_ip(self.partition) pyscf/cc/eom_rccsd.py:1839: in make_ip self._make_shared_1e() pyscf/cc/eom_rccsd.py:1816: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:65: in Loo Lki = cc_Foo(t1, t2, eris) + np.einsum('kc,ic->ki',fov, t1) ^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.01167438, -0. , -0. , 0. , -0.01608749, 0.00012266, 0. , -0.0208568 ], ...03], [ 0. , 0. , -0. , 0.00596681, 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Water.test_fno_by_thresh ___________________________ self = def test_fno_by_thresh(self): threshs = [1e-2,1e-3,1e-4] refs = [ [-0.1200179470,-0.0001506723], [-0.1925851371,-0.0006428496], [-0.2149635715,-0.0030270215], ] for thresh,ref in zip(threshs,refs): > eccsd, et = self.kernel(cc.FNOCCSD, thresh=thresh) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_fno_uhf.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/test/test_fno_uhf.py:49: in kernel mcc.kernel(eris=eris) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[ 0. , -0.00000006, 0. , 0.00000004], [-0.00000016, -0. , 0. , 0. ... 0. , -0. , 0.0231641 , 0. ], [-0. , 0.01783045, 0. , 0.03382715]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->bj', ['jb', 'bj']), ((1, 0), 'bj,jb->', [''])] contraction = ((2, 0), 'iajb,ia->bj', ['jb', 'bj']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ Water.test_fno_by_thresh_frozen ________________________ self = def test_fno_by_thresh_frozen(self): threshs = [1e-2,1e-3,1e-4] refs = [ [-0.0777291294,-0.0000381574], [-0.1409238993,-0.0004851219], [-0.1500184791,-0.0021645217], ] for thresh,ref in zip(threshs,refs): > eccsd, et = self.kernel(cc.FNOCCSD, thresh=thresh, frozen=1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_fno_uhf.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/test/test_fno_uhf.py:49: in kernel mcc.kernel(eris=eris) pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0.00000016, 0. , -0. ], [ 0. , -0.00000018, -0. ], [ 0. , ..., -0. ], [-0. , -0.120231 , -0. ], [ 0. , -0. , 0.15940881]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->bj', ['jb', 'bj']), ((1, 0), 'bj,jb->', [''])] contraction = ((2, 0), 'iajb,ia->bj', ['jb', 'bj']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_gccsd_t_lambda ________________________ self = def test_gccsd_t_lambda(self): mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 0 mol.build() mf0 = mf = scf.RHF(mol).run(conv_tol=1.) mf = scf.addons.convert_to_ghf(mf) mycc0 = cc.CCSD(mf0) eris0 = mycc0.ao2mo() mycc0.kernel(eris=eris0) t1 = mycc0.t1 t2 = mycc0.t2 > imds = ccsd_t_lambda.make_intermediates(mycc0, t1, t2, eris0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_gccsd_lambda.py:264: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_t_lambda_slow.py:39: in make_intermediates imds = ccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0.00635036, -0. , 0. , -0.00726232, 0. , 0.00223913, 0. , -0.01422887], ...14], [ 0. , -0. , 0. , -0. , -0.02725762, 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_ccsd_lambda _________________________ self = def test_ccsd_lambda(self): mcc = cc.ccsd.CC(mf) mcc.conv_tol = 1e-9 mcc.conv_tol_normt = 1e-7 mcc.kernel() > mcc.solve_lambda() pyscf/cc/test/test_h2o.py:135: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0., 0., 0., -0., 0., -0., -0., -0., -0., 0., 0., -0., -0., -0., 0., -0., -0., 0.], [-0., ... 0. , -0. , -0. , 0. , -0.00018019, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ccsd_rdm ___________________________ self = def test_ccsd_rdm(self): mcc = cc.ccsd.CC(mf) mcc.max_memory = 0 mcc.conv_tol = 1e-9 mcc.conv_tol_normt = 1e-7 mcc.kernel() > mcc.solve_lambda() pyscf/cc/test/test_h2o.py:145: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0., -0., 0., -0., 0., -0., -0., -0., -0., 0., 0., -0., -0., -0., 0., -0., -0., -0.], [-0., ... 0. , -0. , -0. , 0. , -0.00018019, -0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_rdm _____________________________ self = def test_rdm(self): mycc = rccsd.RCCSD(mf) mycc.frozen = 1 > mycc.kernel() pyscf/cc/test/test_rccsd_lambda.py:159: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.0448917 , -0. , -0. , -0. , -0.04175596, 0.00629927, -0. , -0.03986915], ...03], [ 0. , 0. , -0. , 0.00000012, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rdm_trace __________________________ self = def test_rdm_trace(self): mycc = rccsd.RCCSD(mf) numpy.random.seed(2) nocc = 5 nmo = 12 nvir = nmo - nocc eri0 = numpy.random.random((nmo,nmo,nmo,nmo)) eri0 = ao2mo.restore(1, ao2mo.restore(8, eri0, nmo), nmo) fock0 = numpy.random.random((nmo,nmo)) fock0 = fock0 + fock0.T + numpy.diag(range(nmo))*2 t1 = numpy.random.random((nocc,nvir)) t2 = numpy.random.random((nocc,nocc,nvir,nvir)) t2 = t2 + t2.transpose(1,0,3,2) l1 = numpy.random.random((nocc,nvir)) l2 = numpy.random.random((nocc,nocc,nvir,nvir)) l2 = l2 + l2.transpose(1,0,3,2) h1 = fock0 - (numpy.einsum('kkpq->pq', eri0[:nocc,:nocc])*2 - numpy.einsum('pkkq->pq', eri0[:,:nocc,:nocc])) eris = lambda:None eris.oooo = eri0[:nocc,:nocc,:nocc,:nocc].copy() eris.ooov = eri0[:nocc,:nocc,:nocc,nocc:].copy() eris.ovoo = eri0[:nocc,nocc:,:nocc,:nocc].copy() eris.oovv = eri0[:nocc,:nocc,nocc:,nocc:].copy() eris.ovov = eri0[:nocc,nocc:,:nocc,nocc:].copy() eris.ovvo = eri0[:nocc,nocc:,nocc:,:nocc].copy() eris.ovvv = eri0[:nocc,nocc:,nocc:,nocc:].copy() eris.vvvv = eri0[nocc:,nocc:,nocc:,nocc:].copy() eris.fock = fock0 doo, dov, dvo, dvv = ccsd_rdm._gamma1_intermediates(mycc, t1, t2, l1, l2) self.assertAlmostEqual((numpy.einsum('ij,ij', doo, fock0[:nocc,:nocc]))*2, -20166.329861034799, 8) self.assertAlmostEqual((numpy.einsum('ab,ab', dvv, fock0[nocc:,nocc:]))*2, 58078.964019246778, 8) self.assertAlmostEqual((numpy.einsum('ai,ia', dvo, fock0[:nocc,nocc:]))*2, -74994.356886784764, 8) self.assertAlmostEqual((numpy.einsum('ia,ai', dov, fock0[nocc:,:nocc]))*2, 34.010188025702391, 9) fdm2 = lib.H5TmpFile() dovov, dvvvv, doooo, doovv, dovvo, dvvov, dovvv, dooov = \ > ccsd_rdm._gamma2_outcore(mycc, t1, t2, l1, l2, fdm2, True) pyscf/cc/test/test_rccsd_lambda.py:218: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_rdm.py:128: in _gamma2_outcore gOvvO = lib.einsum('kiac,jc,kb->iabj', l2[:,:,p0:p1], t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kiac,jc,kb->iabj' tensors = [array([[[[1.51768281, 1.14236678, 1.41807856, 1.22250612, 0.6983057 , 0.56553588, 0.53168045], [1.14236678, ...0.85716458, 0.42390885], [0.64812822, 0.27289589, 0.64708204, 0.52437773, 0.91045365, 0.97605539, 0.35783095]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'jc,kiac->aijk', ['kb', 'aijk']), ((1, 0), 'aijk,kb->iabj', ['iabj'])] contraction = ((1, 0), 'jc,kiac->aijk', ['kb', 'aijk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_update_lambda_complex ____________________ self = def test_update_lambda_complex(self): mo_coeff = mf.mo_coeff + np.sin(mf.mo_coeff) * .01j nao = mo_coeff.shape[0] eri = ao2mo.restore(1, mf._eri, nao) > eri0 = lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri, mo_coeff.conj(), mo_coeff, mo_coeff.conj(), mo_coeff) pyscf/cc/test/test_rccsd_lambda.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 4.78044571, 0.59837845, 0.53797322, 0. , 0. , 0. , 0. , 0. , 0.... , -0.54216863-0.00515995j, 0.09387402+0.00093736j, -0.91030312-0.0078969j , -0.61287221-0.00575219j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_update_lambda_real ______________________ self = def test_update_lambda_real(self): mycc = rccsd.RCCSD(mf) np.random.seed(12) nocc = 5 nmo = 12 nvir = nmo - nocc eri0 = np.random.random((nmo,nmo,nmo,nmo)) eri0 = ao2mo.restore(1, ao2mo.restore(8, eri0, nmo), nmo) fock0 = np.random.random((nmo,nmo)) fock0 = fock0 + fock0.T + np.diag(range(nmo))*2 t1 = np.random.random((nocc,nvir)) t2 = np.random.random((nocc,nocc,nvir,nvir)) t2 = t2 + t2.transpose(1,0,3,2) l1 = np.random.random((nocc,nvir)) l2 = np.random.random((nocc,nocc,nvir,nvir)) l2 = l2 + l2.transpose(1,0,3,2) eris = rccsd._ChemistsERIs(mol) eris.oooo = eri0[:nocc,:nocc,:nocc,:nocc].copy() eris.ovoo = eri0[:nocc,nocc:,:nocc,:nocc].copy() eris.oovv = eri0[:nocc,:nocc,nocc:,nocc:].copy() eris.ovvo = eri0[:nocc,nocc:,nocc:,:nocc].copy() eris.ovov = eri0[:nocc,nocc:,:nocc,nocc:].copy() idx = np.tril_indices(nvir) eris.ovvv = eri0[:nocc,nocc:,nocc:,nocc:].copy() eris.vvvv = eri0[nocc:,nocc:,nocc:,nocc:].copy() eris.fock = fock0 > imds = rccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_rccsd_lambda.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/rccsd_lambda.py:65: in make_intermediates v5 += lib.einsum('kc,kb,jc->bj', v4, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 8.56652427, 8.0864907 , 8.74830729, 8.87673259, 7.3868184 , 6.0877245 , 7.47261231], [ 9.943529...0.62897697, 0.87648706], [0.48386851, 0.44236453, 0.37061368, 0.1690263 , 0.773672 , 0.77156898, 0.35141294]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_lambda_intermediates_real __________________ self = def test_lambda_intermediates_real(self): mycc = rccsd.RCCSD(mf) np.random.seed(12) nocc = 5 nmo = 12 nvir = nmo - nocc eri0 = np.random.random((nmo,nmo,nmo,nmo)) eri0 = ao2mo.restore(1, ao2mo.restore(8, eri0, nmo), nmo) fock0 = np.random.random((nmo,nmo)) fock0 = fock0 + fock0.T + np.diag(range(nmo))*2 t1 = np.random.random((nocc,nvir)) t2 = np.random.random((nocc,nocc,nvir,nvir)) t2 = t2 + t2.transpose(1,0,3,2) eris = rccsd._ChemistsERIs(mol) eris.oooo = eri0[:nocc,:nocc,:nocc,:nocc].copy() eris.ovoo = eri0[:nocc,nocc:,:nocc,:nocc].copy() eris.oovv = eri0[:nocc,:nocc,nocc:,nocc:].copy() eris.ovvo = eri0[:nocc,nocc:,nocc:,:nocc].copy() eris.ovov = eri0[:nocc,nocc:,:nocc,nocc:].copy() idx = np.tril_indices(nvir) eris.ovvv = eri0[:nocc,nocc:,nocc:,nocc:].copy() eris.vvvv = eri0[nocc:,nocc:,nocc:,nocc:].copy() eris.fock = fock0 eris.mo_energy = fock0.diagonal() > imds_ref = ccsd_t_lambda_slow.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_rccsd_t_lambda.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_t_lambda_slow.py:39: in make_intermediates imds = ccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[0.56583249, 0.8436779 , 1.48788121, 0.79782585, 0.49504429, 1.06631093, 1.22541398], [1.05912234, 0.22...0.62897697, 0.87648706], [0.48386851, 0.44236453, 0.37061368, 0.1690263 , 0.773672 , 0.77156898, 0.35141294]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_rdm_intermediates_real ____________________ self = def test_rdm_intermediates_real(self): mycc = rccsd.RCCSD(mf) np.random.seed(12) nocc = 5 nmo = 12 nvir = nmo - nocc eri0 = np.random.random((nmo,nmo,nmo,nmo)) eri0 = ao2mo.restore(1, ao2mo.restore(8, eri0, nmo), nmo) fock0 = np.random.random((nmo,nmo)) fock0 = fock0 + fock0.T + np.diag(range(nmo))*2 t1 = np.random.random((nocc,nvir)) t2 = np.random.random((nocc,nocc,nvir,nvir)) t2 = t2 + t2.transpose(1,0,3,2) l1 = np.random.random((nocc,nvir)) l2 = np.random.random((nocc,nocc,nvir,nvir)) l2 = l2 + l2.transpose(1,0,3,2) eris = rccsd._ChemistsERIs(mol) eris.oooo = eri0[:nocc,:nocc,:nocc,:nocc].copy() eris.ovoo = eri0[:nocc,nocc:,:nocc,:nocc].copy() eris.oovv = eri0[:nocc,:nocc,nocc:,nocc:].copy() eris.ovvo = eri0[:nocc,nocc:,nocc:,:nocc].copy() eris.ovov = eri0[:nocc,nocc:,:nocc,nocc:].copy() idx = np.tril_indices(nvir) eris.ovvv = eri0[:nocc,nocc:,nocc:,nocc:].copy() eris.vvvv = eri0[nocc:,nocc:,nocc:,nocc:].copy() eris.fock = fock0 eris.mo_energy = fock0.diagonal() d1_ref = ccsd_t_rdm_slow._gamma1_intermediates(mycc, t1, t2, l1, l2, eris, for_grad=False) d1_ref = np.concatenate([d.ravel() for d in d1_ref]) d1_g_ref = ccsd_t_rdm_slow._gamma1_intermediates(mycc, t1, t2, l1, l2, eris, for_grad=True) d1_g_ref = np.concatenate([d.ravel() for d in d1_g_ref]) > d2_ref = ccsd_t_rdm_slow._gamma2_intermediates(mycc, t1, t2, l1, l2, eris, compress_vvvv=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_rccsd_t_lambda.py:136: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_t_rdm_slow.py:68: in _gamma2_intermediates ccsd_rdm._gamma2_intermediates(mycc, t1, t2, l1, l2) pyscf/cc/ccsd_rdm.py:50: in _gamma2_intermediates _gamma2_outcore(mycc, t1, t2, l1, l2, f, compress_vvvv) pyscf/cc/ccsd_rdm.py:128: in _gamma2_outcore gOvvO = lib.einsum('kiac,jc,kb->iabj', l2[:,:,p0:p1], t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kiac,jc,kb->iabj' tensors = [array([[[[0.48970924, 1.30899123, 0.32955166, 0.44844013, 0.71494997, 0.43839417, 1.33172116], [1.30899123, ...0.62897697, 0.87648706], [0.48386851, 0.44236453, 0.37061368, 0.1690263 , 0.773672 , 0.77156898, 0.35141294]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'jc,kiac->aijk', ['kb', 'aijk']), ((1, 0), 'aijk,kb->iabj', ['iabj'])] contraction = ((1, 0), 'jc,kiac->aijk', ['kb', 'aijk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_update_lambda_complex ____________________ self = def test_update_lambda_complex(self): nocca, noccb = mol.nelec nmo = mol.nao_nr() nvira,nvirb = nmo-nocca, nmo-noccb numpy.random.seed(9) t1 = [numpy.random.random((nocca,nvira))-.9, numpy.random.random((noccb,nvirb))-.9] l1 = [numpy.random.random((nocca,nvira))-.9, numpy.random.random((noccb,nvirb))-.9] t2 = [numpy.random.random((nocca,nocca,nvira,nvira))-.9, numpy.random.random((nocca,noccb,nvira,nvirb))-.9, numpy.random.random((noccb,noccb,nvirb,nvirb))-.9] t2[0] = t2[0] - t2[0].transpose(1,0,2,3) t2[0] = t2[0] - t2[0].transpose(0,1,3,2) t2[2] = t2[2] - t2[2].transpose(1,0,2,3) t2[2] = t2[2] - t2[2].transpose(0,1,3,2) l2 = [numpy.random.random((nocca,nocca,nvira,nvira))-.9, numpy.random.random((nocca,noccb,nvira,nvirb))-.9, numpy.random.random((noccb,noccb,nvirb,nvirb))-.9] l2[0] = l2[0] - l2[0].transpose(1,0,2,3) l2[0] = l2[0] - l2[0].transpose(0,1,3,2) l2[2] = l2[2] - l2[2].transpose(1,0,2,3) l2[2] = l2[2] - l2[2].transpose(0,1,3,2) # eris = mycc.ao2mo() # imds = make_intermediates(mycc, t1, t2, eris) # l1new, l2new = update_lambda(mycc, t1, t2, l1, l2, eris, imds) # print(lib.fp(l1new[0]) --104.55975252585894) # print(lib.fp(l1new[1]) --241.12677819375281) # print(lib.fp(l2new[0]) --0.4957533529669417) # print(lib.fp(l2new[1]) - 15.46423057451851 ) # print(lib.fp(l2new[2]) - 5.8430776663704407) nocca, noccb = mol.nelec mo_a = mf.mo_coeff[0] + numpy.sin(mf.mo_coeff[0]) * .01j mo_b = mf.mo_coeff[1] + numpy.sin(mf.mo_coeff[1]) * .01j nao = mo_a.shape[0] eri = ao2mo.restore(1, mf._eri, nao) > eri0aa = lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri, mo_a.conj(), mo_a, mo_a.conj(), mo_a) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd_lambda.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 4.78044571, 0.59837845, 0.53797322, 0. , 0. , 0. , 0. , 0. , 0....460675j, -0.4505775 -0.00435485j, -0.51141953-0.00489416j, -1.00821767-0.00845883j, -0.61084956-0.00573564j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_update_lambda_real ______________________ self = def test_update_lambda_real(self): numpy.random.seed(21) eris = mycc.ao2mo() gcc1 = gccsd.GCCSD(scf.addons.convert_to_ghf(mf)) eri1 = gcc1.ao2mo() orbspin = eri1.orbspin nocc = mol.nelectron nvir = mol.nao_nr()*2 - nocc t1r = numpy.random.random((nocc,nvir))*.1 t2r = numpy.random.random((nocc,nocc,nvir,nvir))*.1 t2r = t2r - t2r.transpose(1,0,2,3) t2r = t2r - t2r.transpose(0,1,3,2) l1r = numpy.random.random((nocc,nvir))*.1 l2r = numpy.random.random((nocc,nocc,nvir,nvir))*.1 l2r = l2r - l2r.transpose(1,0,2,3) l2r = l2r - l2r.transpose(0,1,3,2) t1r = addons.spin2spatial(t1r, orbspin) t2r = addons.spin2spatial(t2r, orbspin) t1r = addons.spatial2spin(t1r, orbspin) t2r = addons.spatial2spin(t2r, orbspin) l1r = addons.spin2spatial(l1r, orbspin) l2r = addons.spin2spatial(l2r, orbspin) l1r = addons.spatial2spin(l1r, orbspin) l2r = addons.spatial2spin(l2r, orbspin) imds = gccsd_lambda.make_intermediates(gcc1, t1r, t2r, eri1) l1ref, l2ref = gccsd_lambda.update_lambda(gcc1, t1r, t2r, l1r, l2r, eri1, imds) t1 = addons.spin2spatial(t1r, orbspin) t2 = addons.spin2spatial(t2r, orbspin) l1 = addons.spin2spatial(l1r, orbspin) l2 = addons.spin2spatial(l2r, orbspin) > imds = uccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/test/test_uccsd_lambda.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd_lambda.py:90: in make_intermediates v5a += einsum('kc,kb,jc->bj', tmp, t1a, t1a) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0.0021558 , -0.00479139, 0.00100601, 0.00736064, -0.00466649, 0.00567794, -0.0042061 ], [-0.000434...0.07158187, 0.07607078], [0.03119592, 0.00883349, 0.00882858, 0.02182589, 0.07777771, 0.08098333, 0.01956104]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_overlap ___________________________ self = def test_overlap(self): numpy.random.seed(1) nmo = 6 nocc = 3 nvir = nmo - nocc c2 = numpy.random.rand(nocc,nocc,nvir,nvir) cibra = cisd.amplitudes_to_cisdvec(numpy.random.rand(1), numpy.random.rand(nocc,nvir), c2+c2.transpose(1,0,3,2)) c2 = numpy.random.rand(nocc,nocc,nvir,nvir) ciket = cisd.amplitudes_to_cisdvec(numpy.random.rand(1), numpy.random.rand(nocc,nvir), c2+c2.transpose(1,0,3,2)) fcibra = cisd.to_fcivec(cibra, nmo, nocc*2) fciket = cisd.to_fcivec(ciket, nmo, nocc*2) s_mo = numpy.random.random((nmo,nmo)) s0 = fci.addons.overlap(fcibra, fciket, nmo, nocc*2, s_mo) > s1 = cisd.overlap(cibra, ciket, nmo, nocc, s_mo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ci/test/test_cisd.py:390: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/ci/cisd.py:485: in overlap ovlp = lib.einsum('ab,ap,bq,pq->', bra_mat, trans, trans, ket_mat) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ab,ap,bq,pq->' tensors = [array([[ 0.62367221, 0.75094243, 0.34889834, 0.26992789, 0.89588622, 0.42809119, 0.96484005, 0.6634415 , 0.62... 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,ab->bp', ['bq', 'pq', 'bp']), ((1, 0), 'pq,bq->bp', ['bp', 'bp']), ((1, 0), 'bp,bp->', [''])] contraction = ((1, 0), 'ap,ab->bp', ['bq', 'pq', 'bp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_overlap ___________________________ self = def test_overlap(self): nmo = 8 nocc = nocca, noccb = (4,3) numpy.random.seed(2) nvira, nvirb = nmo-nocca, nmo-noccb cibra = ucisd.amplitudes_to_cisdvec(numpy.random.rand(1)[0], (numpy.random.rand(nocca,nvira), numpy.random.rand(noccb,nvirb)), (numpy.random.rand(nocca,nocca,nvira,nvira), numpy.random.rand(nocca,noccb,nvira,nvirb), numpy.random.rand(noccb,noccb,nvirb,nvirb))) ciket = ucisd.amplitudes_to_cisdvec(numpy.random.rand(1)[0], (numpy.random.rand(nocca,nvira), numpy.random.rand(noccb,nvirb)), (numpy.random.rand(nocca,nocca,nvira,nvira), numpy.random.rand(nocca,noccb,nvira,nvirb), numpy.random.rand(noccb,noccb,nvirb,nvirb))) fcibra = ucisd.to_fcivec(cibra, nmo, nocc) fciket = ucisd.to_fcivec(ciket, nmo, nocc) s_mo = numpy.random.random((nmo,nmo)) s0 = fci.addons.overlap(fcibra, fciket, nmo, nocc, s_mo) > s1 = ucisd.overlap(cibra, ciket, nmo, nocc, (s_mo, s_mo)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ci/test/test_ucisd.py:325: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/ci/ucisd.py:593: in overlap c_s = lib.einsum('ab,ap,bq->pq', bra_mat, trans_a, trans_b) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ab,ap,bq->pq' tensors = [array([[0.4359949 , 0.49423684, 0.84656149, 0.07964548, 0.50524609, 0.0652865 , 0.42812233, 0.09653092, 0.12715997, 0...99, -0.0825945 , -0.07745024, -0.09181332, -0.05314351, -0.01496372, -0.14426636, 0.13831275]], shape=(46, 46))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,ab->bp', ['bq', 'bp']), ((1, 0), 'bp,bq->pq', ['pq'])] contraction = ((1, 0), 'ap,ab->bp', ['bq', 'bp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_with_df_s0 __________________________ self = def test_with_df_s0(self): mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.build() rhf = scf.RHF(mol).density_fit(auxbasis='weigend') rhf.conv_tol_grad = 1e-8 rhf.kernel() mf = scf.addons.convert_to_uhf(rhf) myci = ci.UCISD(mf) > myci.kernel() pyscf/ci/test/test_ucisd.py:361: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/ci/cisd.py:965: in kernel return self.cisd(ci0, eris) ^^^^^^^^^^^^^^^^^^^^ pyscf/ci/cisd.py:969: in cisd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ci/ucisd.py:946: in ao2mo return uccsd._make_df_eris_outcore(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:988: in _make_df_eris_outcore Lpq = einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ... , -0.99238945, 1.38533144, -0.48588491, 0. , -0.54183037, 0.09036684, -0.91008414, -0.61366478]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_with_df_s2 __________________________ self = def test_with_df_s2(self): mol = gto.Mole() mol.atom = [ [8 , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)]] mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).density_fit(auxbasis='weigend') mf.conv_tol_grad = 1e-8 mf.kernel() myci = ci.UCISD(mf) > myci.kernel() pyscf/ci/test/test_ucisd.py:377: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/ci/cisd.py:965: in kernel return self.cisd(ci0, eris) ^^^^^^^^^^^^^^^^^^^^ pyscf/ci/cisd.py:969: in cisd eris = self.ao2mo(self.mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ci/ucisd.py:946: in ao2mo return uccsd._make_df_eris_outcore(self, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:988: in _make_df_eris_outcore Lpq = einsum('Lab,ap,bq->Lpq', eri1, moa, moa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'Lab,ap,bq->Lpq' tensors = [array([[[ 2.18498097, 0.26658448, 0.24233725, 0. , 0. , 0. , 0. , 0. , 0. ...678, -0.91139924, -1.32075378, 0. , -0.47874843, -0.45168617, -0.50742628, -1.00854356, -0.61288189]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']), ((1, 0), 'bpL,bq->Lpq', ['Lpq'])] contraction = ((1, 0), 'ap,Lab->bpL', ['bq', 'bpL']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casscf_grad _________________________ self = def test_casscf_grad(self): > gref = mcscf.CASSCF (mol.RHF.run (), 8, 6).run ().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:169: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.008852 , -0.03815532, 0.04362963, 0.01051954, -0.01894301, 0.00609745, 0. , -0. , -0. ...7 ], [ 0.13279544, 0.07453633, 0. , -0.16729823, -0.33261575, 0.10727509, 0. , 0.11305205]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rhf_grad ___________________________ self = def test_rhf_grad(self): gref = scf.RHF(mol).run().nuc_grad_method().kernel() > g1 = scf.RHF(mol).density_fit().run().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:543: in get_veff vj, vk = self.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...671, 0.00078095, 0. , -0.00647602, -0. , -0.00251434, -0.00076189, -0. , 0.00144139]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_gga_grad _________________________ self = def test_rks_gga_grad(self): gref = mol.RKS(xc='b3lyp').run().nuc_grad_method().kernel() > g1 = mol.RKS(xc='b3lyp').density_fit().run().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rks.py:81: in get_veff vj, vk = ks_grad.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...452, 0.00070668, 0. , -0.00681898, 0. , -0.00327828, -0.00095381, 0. , 0.00184336]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_lda_grad _________________________ self = def test_rks_lda_grad(self): gref = mol.RKS(xc='lda,').run().nuc_grad_method().kernel() > g1 = mol.RKS(xc='lda,').density_fit().run().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rks.py:75: in get_veff vj = ks_grad.get_j(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:534: in get_j return get_j(self, mol, dm, hermi) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:293: in get_j vjaux[:,:,:,p0:p1] = lib.einsum('xwp,mw,np->mnxp', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xwp,mw,np->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...176, 0.00071651, -0. , -0.00658905, 0. , -0.00343895, -0.00094359, 0. , 0.00201178]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mw,xwp->mxp', ['np', 'mxp']), ((1, 0), 'mxp,np->mnxp', ['mnxp'])] contraction = ((1, 0), 'mw,xwp->mxp', ['np', 'mxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_mgga_grad ________________________ self = def test_rks_mgga_grad(self): gref = mol.RKS(xc='m06').run().nuc_grad_method().kernel() > g1 = mol.RKS(xc='m06').density_fit().run().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rks.py:81: in get_veff vj, vk = ks_grad.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...283, 0.00073107, 0. , -0.00679221, 0. , -0.00307167, -0.00092561, 0. , 0.00169665]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_rsh_grad _________________________ self = def test_rks_rsh_grad(self): gref = mol.RKS(xc='wb97').run().nuc_grad_method().kernel() > g1 = mol.RKS(xc='wb97').density_fit().run().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:89: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rks.py:81: in get_veff vj, vk = ks_grad.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...575, 0.00075868, 0. , -0.00679609, 0. , -0.00303917, -0.00091082, 0. , 0.00171378]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_sacasscf_grad ________________________ self = def test_sacasscf_grad(self): mf = mol.RHF.run () mc = mcscf.CASSCF (mf,8,6).state_average_([.5,.5]).run() > gref = mc.nuc_grad_method ().kernel (state=1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:176: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:643: in get_ham_response return fcasscf_grad.kernel (mo_coeff=mo, ci=ci[state], atmlst=atmlst, verbose=verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.03059944, -0.13969778, 0.16338311, -0.3718117 , 0.82176929, 2.09293518, 0. , -0. , -0. ...61], [ 0.11839095, 0.06181947, 0. , -0.97344131, 0.31439504, -0.01976078, 0. , -0.63255798]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_uhf_grad ___________________________ self = def test_uhf_grad(self): mol = gto.Mole() mol.atom = [ ['O' , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)] ] mol.symmetry = True mol.verbose = 0 mol.basis = '631g' mol.spin = 2 mol.build() mf = scf.UHF(mol).density_fit().run(conv_tol=1e-12) > g1 = mf.nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:109: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uhf.py:48: in get_veff vj, vk = self.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...67 , 0.00051602, -0. , -0.00325755, 0. , -0.00048594, -0.00031893, 0. , 0.00005853]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_uks_gga_grad _________________________ self = def test_uks_gga_grad(self): gref = mol.UKS.run(xc='b3lyp').nuc_grad_method().kernel() > g1 = mol.UKS.density_fit().run(xc='b3lyp').nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:150: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uks.py:83: in get_veff vj, vk = ks_grad.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...726, 0.00035334, 0. , -0.00340949, 0. , -0.00163914, -0.0004769 , 0. , 0.00092168]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_uks_lda_grad _________________________ self = def test_uks_lda_grad(self): mol = gto.Mole() mol.atom = [ ['O' , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)] ] mol.basis = '631g' mol.charge = 1 mol.spin = 1 mol.build() mf = mol.UKS().density_fit().run(conv_tol=1e-12) gref = mol.UKS.run().nuc_grad_method().kernel() > g1 = mf.nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:138: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uks.py:77: in get_veff vj = ks_grad.get_j(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:534: in get_j return get_j(self, mol, dm, hermi) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:293: in get_j vjaux[:,:,:,p0:p1] = lib.einsum('xwp,mw,np->mnxp', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xwp,mw,np->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...312, 0.00049827, -0. , -0.00354548, -0. , -0.0009129 , -0.00043953, -0. , 0.0002734 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mw,xwp->mxp', ['np', 'mxp']), ((1, 0), 'mxp,np->mnxp', ['mnxp'])] contraction = ((1, 0), 'mw,xwp->mxp', ['np', 'mxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_uks_rsh_grad _________________________ self = def test_uks_rsh_grad(self): mol = gto.Mole() mol.atom = [ ['O' , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)] ] mol.basis = '631g' mol.charge = 1 mol.spin = 1 mol.verbose = 0 mol.build() gref = mol.UKS(xc='camb3lyp').run().nuc_grad_method().kernel() > g1 = mol.UKS(xc='camb3lyp').density_fit().run().nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_grad.py:165: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uks.py:83: in get_veff vj, vk = ks_grad.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...881, 0.0005222 , -0. , -0.0035888 , 0. , -0.00089639, -0.00042522, 0. , 0.00027291]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rhf_hess ___________________________ self = def test_rhf_hess(self): href = scf.RHF(mol).run().Hessian().kernel() > h1 = scf.RHF(mol).density_fit().run().Hessian().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:48: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rhf.py:55: in partial_hess_elec e1, ej, ek = _partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:257: in _partial_hess_ejk _ej -= lib.einsum('yqp,q,px->xy', int2c_ip1[:,q0:q1], rhoj0_P[q0:q1], rhoj1_P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yqp,q,px->xy' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ... 0.00059031], [ 0.00134601, -0. , -0. ], [ -0. , 0.03413229, 0.02027776]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'q,yqp->yp', ['px', 'yp']), ((1, 0), 'yp,px->xy', ['xy'])] contraction = ((1, 0), 'q,yqp->yp', ['px', 'yp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_gga_hess _________________________ self = def test_rks_gga_hess(self): href = mol.RKS.run(xc='b3lyp').Hessian().kernel() df_h = mol.RKS.density_fit().run(xc='b3lyp').Hessian() df_h.auxbasis_response = 2 > h1 = df_h.kernel() ^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:62: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:180: in _partial_hess_ejk wk_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocc_2, mocc_2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0....45, 0.37844824, 0.20086825, 0. ], [ 0.00436809, 0.00006853, 0.21142618, 0.14641878, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_lda_hess _________________________ self = def test_rks_lda_hess(self): href = mol.RKS.run(xc='lda,vwn').Hessian().kernel() df_h = mol.RKS.density_fit().run(xc='lda,vwn').Hessian() df_h.auxbasis_response = 2 > h1 = df_h.kernel() ^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:55: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:189: in _partial_hess_ejk int2c_ip_ip = lib.einsum('xpq,qr,ysr->xyps', int2c_ip1, int2c_inv, int2c_ip1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,qr,ysr->xyps' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. .... , 0. , 0. , 0. , 0. , 0. , 0. ]]], shape=(3, 116, 116))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'qr,xpq->xpr', ['ysr', 'xpr']), ((1, 0), 'xpr,ysr->xyps', ['xyps'])] contraction = ((1, 0), 'qr,xpq->xpr', ['ysr', 'xpr']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_mgga_hess ________________________ self = def test_rks_mgga_hess(self): href = mol.RKS.run(xc='m06').Hessian().kernel() df_h = mol.RKS.density_fit().run(xc='m06').Hessian() df_h.auxbasis_response = 2 > h1 = df_h.kernel() ^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:69: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:180: in _partial_hess_ejk wk_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocc_2, mocc_2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0....9 , 0.378042 , 0.20107541, 0. ], [ 0.00468398, -0.00842 , 0.19328086, 0.13724835, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_rks_rsh_hess _________________________ self = def test_rks_rsh_hess(self): href = mol.RKS.run(xc='camb3lyp').Hessian().kernel() df_h = mol.RKS.density_fit().run(xc='camb3lyp').Hessian() df_h.auxbasis_response = 2 > h1 = df_h.kernel() ^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:180: in _partial_hess_ejk wk_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocc_2, mocc_2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0....2 , 0.3754687 , 0.19773145, -0. ], [ 0.00439206, 0.0051357 , 0.21164048, 0.1405475 , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_uhf_hess ___________________________ self = def test_uhf_hess(self): href = scf.UHF(mol).run().Hessian().kernel() df_h = scf.UHF(mol).density_fit().run().Hessian() df_h.auxbasis_response = 2 > h1 = df_h.kernel() ^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/uhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/uhf.py:45: in partial_hess_elec e1, ej, ek = _partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/uhf.py:193: in _partial_hess_ejk wka_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocca, mocca) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0....79, 0.26316255, 0.14402504, -0. ], [ 0.00198102, -0.00830414, 0.12389938, 0.08054158, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_uks_hess ___________________________ self = def test_uks_hess(self): href = mol.UKS.run(xc='camb3lyp').Hessian().kernel() df_h = mol.UKS.density_fit().run(xc='camb3lyp').Hessian() df_h.auxbasis_response = 2 > h1 = df_h.kernel() ^^^^^^^^^^^^^ pyscf/df/test/test_df_hessian.py:90: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/uhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/uks.py:60: in partial_hess_elec de2, ej, ek = df_uhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/uhf.py:193: in _partial_hess_ejk wka_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocca, mocca) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0....32, 0.26549731, 0.13981819, -0. ], [ 0.00310565, 0.0036318 , 0.14965338, 0.09938483, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rsh_omega __________________________ self = def test_rsh_omega(self): rho0 = numpy.array([1., 1., 0.1, 0.1]).reshape(-1,1) ni = dft.numint.NumInt() ni.omega = 0.4 omega = 0.2 exc, vxc, fxc, kxc = ni.eval_xc('ITYH,', rho0, 0, 0, 1, omega) > self.assertAlmostEqual(float(exc), -0.6359945579326314, 7) ^^^^^^^^^^ E TypeError: only 0-dimensional arrays can be converted to Python scalars pyscf/dft/test/test_numint.py:554: TypeError _________________________ KnownValues.test_contract_2e _________________________ self = def test_contract_2e(self): mol = gto.M( atom = 'Li 0 0 0; Li 0 0 2.', basis = {'Li': [[0, [4.5, 1]], [2, [0.5, 1]]]}, spin=0, symmetry = True, ) mf = mol.RHF().run() norb = mf.mo_coeff.shape[1] nelec = mol.nelec h1e = mf.mo_coeff.T.dot(scf.hf.get_hcore(mol)).dot(mf.mo_coeff) eri = ao2mo.restore(1, ao2mo.kernel(mol, mf.mo_coeff), norb) orbsym = mf.orbsym degen_mapping = direct_spin1_cyl_sym.map_degeneracy(h1e.diagonal(), orbsym) orbsym = lib.tag_array(orbsym, degen_mapping=degen_mapping) u = direct_spin1_cyl_sym._cyl_sym_orbital_rotation(orbsym, degen_mapping) mo = mf.mo_coeff.dot(u.conj().T) h1e = mo.conj().T.dot(mf.get_hcore()).dot(mo) eri = mol.intor('int2e_sph').reshape([norb]*4) > eri = lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri, mo.conj(), mo, mo.conj(), mo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/fci/test/test_spin1_cyl_sym.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 2.39365368, 0. , 0. , -0. , 0. , 0. , 0. , 0. , -0.... 0.50718336+0.j , 0. +0.j , 0. +0.j , 0. +0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_contract_2e_1 ________________________ self = def test_contract_2e_1(self): mol = gto.M( atom = 'Li 0 0 0; Li 0 0 2.', basis = {'Li': [[0, [4.5, 1]], [1, [0.5, 1]]]}, spin=0, symmetry = True, ) mf = mol.RHF().run() norb = mf.mo_coeff.shape[1] nelec = mol.nelec h1e = mf.mo_coeff.T.dot(scf.hf.get_hcore(mol)).dot(mf.mo_coeff) eri = ao2mo.restore(1, ao2mo.kernel(mol, mf.mo_coeff), norb) orbsym = mf.orbsym degen_mapping = direct_spin1_cyl_sym.map_degeneracy(h1e.diagonal(), orbsym) orbsym = lib.tag_array(orbsym, degen_mapping=degen_mapping) u = direct_spin1_cyl_sym._cyl_sym_orbital_rotation(orbsym, degen_mapping) mo = mf.mo_coeff.dot(u.conj().T) h1e = mo.conj().T.dot(mf.get_hcore()).dot(mo) eri = mol.intor('int2e_sph').reshape([norb]*4) > eri = lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri, mo.conj(), mo, mo.conj(), mo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/fci/test/test_spin1_cyl_sym.py:109: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 2.39365368, 0. , 0. , 0. , 0. , 0. , 0. , -0.00646128], ... 0. +0.j , 0. +0.j , 0. +0.j , 0.77690879+0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_linearmole_a2 ________________________ self = def test_linearmole_a2(self): mol = gto.M( atom = 'H 0 0 0; H 0 0 1.2', basis = [[0, [3, 1]], [1, [1, 1]]], symmetry = True) mf = mol.RHF().run() mc = mcscf.CASCI(mf, mf.mo_energy.size, mol.nelec) mc.fcisolver.wfnsym = 'A2g' mc.run() self.assertAlmostEqual(mc.e_tot, 2.6561956585409616, 8) mc.fcisolver = direct_spin1_cyl_sym.FCI(mol) mc.fcisolver.wfnsym = 'A2g' > mc.run() pyscf/fci/test/test_spin1_cyl_sym.py:202: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcscf/casci_symm.py:59: in kernel return casci.CASCI.kernel(self, mo_coeff, ci0, verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcscf/casci.py:1153: in kernel kernel(self, mo_coeff, ci0=ci0, verbose=log) pyscf/mcscf/casci.py:608: in kernel e_tot, fcivec = casci.fcisolver.kernel(h1eff, eri_cas, ncas, nelecas, pyscf/fci/direct_spin1_cyl_sym.py:568: in kernel eri = lib.einsum('pqrs,ip,jq,kr,ls->ijkl', eri, u, u.conj(), u, u.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,ip,jq,kr,ls->ijkl' tensors = [array([[[[ 0.84704311, 0. , 0. , -0. , 0. , 0. , 0.05604313, -0. ], ... , 0. -0.j , 0. -0.j , 0. -0.j , 1. -0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ip,pqrs->iqrs', ['jq', 'kr', 'ls', 'iqrs']), ((3, 0), 'iqrs,jq->ijrs', ['kr', 'ls', 'ijrs']), ((2, 0), 'ijrs,kr->ijks', ['ls', 'ijks']), ((1, 0), 'ijks,ls->ijkl', ['ijkl'])] contraction = ((1, 0), 'ip,pqrs->iqrs', ['jq', 'kr', 'ls', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_spin1_cyl_sym ________________________ self = def test_spin1_cyl_sym(self): mol = gto.M( atom = 'N 0 0 0; N 0 0 1.5', basis = 'cc-pVDZ', spin = 0, symmetry = True, ) mc = mol.RHF().run().CASCI(12, 6) mc.fcisolver.wfnsym = 'E1ux' mc.run() e1 = mc.e_tot ci1 = mc.ci self.assertAlmostEqual(e1, -108.683383569227, 7) mc.fcisolver = direct_spin1_cyl_sym.FCI(mol) mc.fcisolver.wfnsym = 'E1ux' mc.fcisolver.davidson_only = True > mc.run() pyscf/fci/test/test_spin1_cyl_sym.py:163: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcscf/casci_symm.py:59: in kernel return casci.CASCI.kernel(self, mo_coeff, ci0, verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcscf/casci.py:1153: in kernel kernel(self, mo_coeff, ci0=ci0, verbose=log) pyscf/mcscf/casci.py:608: in kernel e_tot, fcivec = casci.fcisolver.kernel(h1eff, eri_cas, ncas, nelecas, pyscf/fci/direct_spin1_cyl_sym.py:568: in kernel eri = lib.einsum('pqrs,ip,jq,kr,ls->ijkl', eri, u, u.conj(), u, u.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,ip,jq,kr,ls->ijkl' tensors = [array([[[[ 0.5308804 , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.... , 0. -0.j , 0. -0.j , 0.70710678-0.j , 0. -0.70710678j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ip,pqrs->iqrs', ['jq', 'kr', 'ls', 'iqrs']), ((3, 0), 'iqrs,jq->ijrs', ['kr', 'ls', 'ijrs']), ((2, 0), 'ijrs,kr->ijks', ['ls', 'ijks']), ((1, 0), 'ijks,ls->ijkl', ['ijkl'])] contraction = ((1, 0), 'ip,pqrs->iqrs', ['jq', 'kr', 'ls', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_triplet_degeneracy ______________________ self = def test_triplet_degeneracy(self): mol = gto.M(atom='O; O 1 1.2', basis='631g', spin=2, symmetry=1) mf = mol.RHF().run() def casci(nelec): norb = 4 mc = mcscf.CASCI(mf, norb, nelec) mc.fcisolver = direct_spin1_cyl_sym.FCI(mol) mc.fcisolver.wfnsym = 'A2g' mc.kernel() return mc.e_tot > self.assertAlmostEqual(casci((4, 2)), -149.56827649707, 9) ^^^^^^^^^^^^^ pyscf/fci/test/test_spin1_cyl_sym.py:235: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/fci/test/test_spin1_cyl_sym.py:233: in casci mc.kernel() pyscf/mcscf/casci_symm.py:59: in kernel return casci.CASCI.kernel(self, mo_coeff, ci0, verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcscf/casci.py:1153: in kernel kernel(self, mo_coeff, ci0=ci0, verbose=log) pyscf/mcscf/casci.py:608: in kernel e_tot, fcivec = casci.fcisolver.kernel(h1eff, eri_cas, ncas, nelecas, pyscf/fci/direct_spin1_cyl_sym.py:568: in kernel eri = lib.einsum('pqrs,ip,jq,kr,ls->ijkl', eri, u, u.conj(), u, u.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,ip,jq,kr,ls->ijkl' tensors = [array([[[[ 0.59084219, 0. , -0. , 0. ], [ 0. , 0.54708788, -0. , -0. ...10678j], [ 0. -0.j , 0. -0.j , 0.70710678-0.j , 0. -0.70710678j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ip,pqrs->iqrs', ['jq', 'kr', 'ls', 'iqrs']), ((3, 0), 'iqrs,jq->ijrs', ['kr', 'ls', 'ijrs']), ((2, 0), 'ijrs,kr->ijks', ['ls', 'ijks']), ((1, 0), 'ijks,ls->ijkl', ['ijkl'])] contraction = ((1, 0), 'ip,pqrs->iqrs', ['jq', 'kr', 'ls', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_wrong_initial_guess _____________________ self = def test_wrong_initial_guess(self): mol = gto.M( atom = 'H 0 0 0; H 0 0 1.2', basis = [[0, [3, 1]], [1, [1, 1]]], spin = 1, charge = 1, symmetry = True) mf = mol.RHF().run() mc = mcscf.CASCI(mf, mf.mo_energy.size, mol.nelec) mc.fcisolver.wfnsym = 'A2g' self.assertRaises(RuntimeError, mc.run) mc.fcisolver = direct_spin1_cyl_sym.FCI(mol) mc.fcisolver.wfnsym = 'A2g' > self.assertRaises(RuntimeError, mc.run) pyscf/fci/test/test_spin1_cyl_sym.py:187: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcscf/casci_symm.py:59: in kernel return casci.CASCI.kernel(self, mo_coeff, ci0, verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcscf/casci.py:1153: in kernel kernel(self, mo_coeff, ci0=ci0, verbose=log) pyscf/mcscf/casci.py:608: in kernel e_tot, fcivec = casci.fcisolver.kernel(h1eff, eri_cas, ncas, nelecas, pyscf/fci/direct_spin1_cyl_sym.py:568: in kernel eri = lib.einsum('pqrs,ip,jq,kr,ls->ijkl', eri, u, u.conj(), u, u.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_spin_squre __________________________ self = def test_spin_squre(self): ss = fci.spin_op.spin_square(ci0, norb, nelec) self.assertAlmostEqual(ss[0], 6, 9) ss = fci.spin_op.spin_square0(ci0, norb, nelec) self.assertAlmostEqual(ss[0], 6, 9) numpy.random.seed(1) u,w,v = numpy.linalg.svd(numpy.random.random((norb,6))) u = u[:,:6] h1a = h1[:6,:6] h1b = reduce(numpy.dot, (v.T, h1a, v)) h2aa = ao2mo.restore(1, h2, norb)[:6,:6,:6,:6] > h2ab = lib.einsum('klpq,pi,qj->klij', h2aa, v, v) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/fci/test/test_spin_op.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klpq,pi,qj->klij' tensors = [array([[[[ 0.35131384, 0. , 0.00046601, 0. , 0. , 0. ], [ 0. , 0.35...81, -0.42331614, -0.24256982], [ 0.73016047, -0.14767356, 0.18756431, 0.23217458, -0.08446492, -0.5906255 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,klpq->iklq', ['qj', 'iklq']), ((1, 0), 'iklq,qj->klij', ['klij'])] contraction = ((1, 0), 'pi,klpq->iklq', ['qj', 'iklq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casci_grad __________________________ self = def test_casci_grad(self): mc = mcscf.CASCI(mf, 4, 4).run() > g1 = casci_grad.Gradients(mc).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:317: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00725847, -0.07458158, 0.1924222 , -0.01117946, 0.10011791, 0.93082823, -0.01117946, 0.10011791, 0.3... [-0. , 0.48701357, 0.55056359, -0. ], [-0. , -0.48701357, 0.55056359, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_casci_grad_excited_state ___________________ self = def test_casci_grad_excited_state(self): mc = mcscf.CASCI(mf, 4, 4) mc.fcisolver.nroots = 3 g_scan = mc.nuc_grad_method().as_scanner(state=2) > g1 = g_scan(mol, atmlst=range(4))[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:333: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00727796, -0.07477354, 0.19289715, -0.01099877, 0.09934205, 0.9367722 , -0.01099877, 0.09934205, 0.3... [-0. , 0.48701357, 0.55056359, 0. ], [ 0. , -0.48701357, 0.55056359, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_casci_grad_with_ccsd_solver _________________ self = def test_casci_grad_with_ccsd_solver(self): mol = gto.Mole() mol.atom = 'N 0 0 0; N 0 0 1.2; H 1 1 0; H 1 1 1.2' mol.verbose = 0 mol.build() mf = scf.RHF(mol).run(conv_tol=1e-14) mc = mcscf.CASCI(mf, 4, 4).run() > g1 = mc.nuc_grad_method().kernel(atmlst=range(mol.natm)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:352: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00725847, -0.07458158, 0.1924222 , -0.01117946, 0.10011791, 0.93082823, -0.01117946, 0.10011791, 0.3... [ 0. , 0.48701357, 0.55056359, -0. ], [ 0. , -0.48701357, 0.55056359, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_scanner ___________________________ self = def test_scanner(self): mc = mcscf.CASCI(mf, 4, 4) gs = mc.nuc_grad_method().as_scanner().as_scanner() > e, g1 = gs(mol.atom) ^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:361: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00725847, -0.07458158, 0.1924222 , -0.01117946, 0.10011791, 0.93082823, -0.01117946, 0.10011791, 0.3... [-0. , 0.48701357, 0.55056359, 0. ], [-0. , -0.48701357, 0.55056359, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_small_mem __________________________ self = def test_small_mem(self): mol = gto.M(atom=""" H -0.00021900 -0.20486000 -2.17721200 H -0.00035900 -1.27718700 -2.17669400 """, basis='6-31G') casci = mol.CASCI(2, 2).run() grad = casci.nuc_grad_method() grad.max_memory = 0 > nuc_grad = grad.kernel() ^^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:468: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.15083571, 0.37643028, 0.23485778, 0.30167142, 0.37643028, 0.15083571, 0.37643028, 0.46971555, 0.3...38, 0.17778096], [0.34647018, 1.1364926 ]]), array([[0.27766138, 0.17778096], [0.34647018, 1.1364926 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_state_average_mix_scanner __________________ self = def test_state_average_mix_scanner(self): mc = mcscf.CASCI(mf, 4, 4) mc = mcscf.addons.state_average_mix_(mc, [mc.fcisolver, mc.fcisolver], (.5, .5)) gs = mc.nuc_grad_method().as_scanner() > e, de = gs(mol) ^^^^^^^ pyscf/grad/test/test_casci.py:398: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00725847, -0.07458158, 0.1924222 , -0.01117946, 0.10011791, 0.93082823, -0.01117946, 0.10011791, 0.3... [-0. , 0.48701357, 0.55056359, -0. ], [-0. , -0.48701357, 0.55056359, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_state_average_scanner ____________________ self = def test_state_average_scanner(self): mc = mcscf.CASCI(mf, 4, 4) gs = mc.state_average_([0.5, 0.5]).nuc_grad_method().as_scanner() > e, de = gs(mol) ^^^^^^^ pyscf/grad/test/test_casci.py:381: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00669767, -0.06759699, 0.17140392, 0.02078495, -0.06181348, 0.94790897, 0.02078495, -0.06181348, 0.3... [-0. , 0.48701357, 0.55056359, -0. ], [-0. , -0.48701357, 0.55056359, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_state_specific_scanner ____________________ self = def test_state_specific_scanner(self): mc = mcscf.CASCI(mf, 4, 4) gs = mc.state_specific_(2).nuc_grad_method().as_scanner() > e, de = gs(mol) ^^^^^^^ pyscf/grad/test/test_casci.py:368: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00727796, -0.07477354, 0.19289715, -0.01099877, 0.09934205, 0.9367722 , -0.01099877, 0.09934205, 0.3... [-0. , 0.48701357, 0.55056359, 0. ], [-0. , -0.48701357, 0.55056359, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_symmetrize __________________________ self = def test_symmetrize(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', symmetry=True) > g = mol.RHF.run().CASCI(4, 4).run().Gradients().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:456: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ...600031, 0. , 0. , -0.59331315], [ 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_qmmm_scanner ______________________ self = def test_with_qmmm_scanner(self): from pyscf import qmmm mol = gto.Mole() mol.atom = ''' O 0.00000000 0.00000000 -0.11081188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''' mol.verbose = 0 mol.basis = '6-31g' mol.build() coords = [(0.5,0.6,0.1)] #coords = [(0.0,0.0,0.0)] charges = [-0.1] mf = qmmm.add_mm_charges(scf.RHF(mol), coords, charges) mc = mcscf.CASCI(mf, 4, 4).as_scanner() > e_tot, g = mc.nuc_grad_method().as_scanner()(mol) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casci.py:436: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00933381, -0.045751 , 0.05611084, -0.07757045, 0.18960251, 0.16255614, -0.0150834 , 0.05324918, -0.0... [ 0.14762369, 0.02364948, -0.08361564, 0.07720054], [ 0.12315552, 0.02428778, -0.83001969, 1.16474121]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_x2c_scanner _______________________ self = def test_with_x2c_scanner(self): with lib.light_speed(20.): mcs = mcscf.CASCI(mf, 4, 4).as_scanner().x2c() gscan = mcs.nuc_grad_method().as_scanner() > g1 = gscan(mol)[1] ^^^^^^^^^^ pyscf/grad/test/test_casci.py:414: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:144: in grad_elec h1ao = hcore_deriv(ia) ^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:42: in hcore_deriv h1 = get_h1_xmol(atm_id) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:83: in hcore_deriv h1_ao, s1_ao, e1, c1, x1, s_nesc1, R1, c_fw1 = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[-0.41141982, 0.41057717, 0.0388342 , 0.0385504 , 0.00056849, -0.00048345, 0.00000664, 0.00003217, -0.00...74, 0.28413821, 0.40621792, 0.74651575, -0.04599084, -0.07509461, -0.01135018, -0.01824541]], shape=(72, 72))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casscf_grad _________________________ self = def test_casscf_grad(self): mc = mcscf.CASSCF(mf, 4, 4).run() > g1 = casscf_grad.Gradients(mc).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casscf.py:102: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00517845, -0.05457635, 0.14400424, -0.01511682, 0.10156009, 0.97274714, -0.01511682, 0.10156009, 0.4... [-0. , -0.44766582, 0.566959 , -0. ], [-0. , 0.44766582, 0.566959 , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_df_casscf_grad ________________________ self = def test_df_casscf_grad(self): mc = mcscf.CASSCF(mf_df, 4, 4).run() > g1 = dfcasscf_grad.Gradients(mc).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casscf.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/df/grad/casscf.py:210: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/casscf.py:97: in grad_elec vj, vk = mc_grad.get_jk(mol, (dm_core, dm_cas)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/casscf.py:194: in get_jk vj, vk = dfrhf_grad.get_jk(self, mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...-0.00196647, -0.00117573, -0.00196647, 0. , -0.00266471, -0.00129546, -0.00100194, -0.00129546, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_df_state_average_scanner ___________________ self = def test_df_state_average_scanner(self): mc = mcscf.CASSCF(mf_df, 4, 4) mc.conv_tol = 1e-10 # B/c high sensitivity in the numerical test mc.fcisolver.conv_tol = 1e-10 gs = mc.state_average_([0.5, 0.5]).nuc_grad_method().as_scanner() > e_avg, de_avg = gs(mol) ^^^^^^^ pyscf/grad/test/test_casscf.py:194: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/sacasscf.py:390: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/sacasscf.py:367: in kernel return sacasscf_grad.Gradients.kernel (self, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:578: in kernel return casscf_grad.Gradients (self.base).kernel ( pyscf/df/grad/casscf.py:210: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/casscf.py:97: in grad_elec vj, vk = mc_grad.get_jk(mol, (dm_core, dm_cas)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/casscf.py:194: in get_jk vj, vk = dfrhf_grad.get_jk(self, mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...-0.00188678, -0.00334228, -0.00188678, -0. , -0.00247609, -0.00151106, -0.00228089, -0.00151106, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_scanner ___________________________ self = def test_scanner(self): mc = mcscf.CASSCF(mf, 4, 4) gs = mc.nuc_grad_method().as_scanner().as_scanner() > e, g1 = gs(mol.atom, atmlst=range(4)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casscf.py:141: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00517845, -0.05457635, 0.14400424, -0.01511682, 0.10156009, 0.97274714, -0.01511682, 0.10156009, 0.4... [-0. , -0.44766582, 0.566959 , 0. ], [-0. , 0.44766582, 0.566959 , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_state_average_mix_scanner __________________ self = def test_state_average_mix_scanner(self): mc = mcscf.CASSCF(mf, 4, 4) mc.conv_tol = 1e-10 # B/c high sensitivity in the numerical test fcisolvers = [fci.solver (mol, singlet=bool(i)) for i in range (2)] fcisolvers[0].conv_tol = fcisolvers[1].conv_tol = 1e-10 fcisolvers[0].spin = 2 mc = mcscf.addons.state_average_mix_(mc, fcisolvers, (.5, .5)) gs = mc.nuc_grad_method().as_scanner() > e_avg, de_avg = gs(mol) ^^^^^^^ pyscf/grad/test/test_casscf.py:256: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/sacasscf.py:390: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:578: in kernel return casscf_grad.Gradients (self.base).kernel ( pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.0038885 , -0.0416164 , 0.11139881, -0.01402781, 0.0857652 , 0.97346752, -0.01402781, 0.0857652 , 0.4... [-0. , -0.48372627, 0.55166198, 0. ], [-0. , 0.48372627, 0.55166198, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_state_average_scanner ____________________ self = def test_state_average_scanner(self): mc = mcscf.CASSCF(mf, 4, 4) mc.conv_tol = 1e-10 # B/c high sensitivity in the numerical test mc.fcisolver.conv_tol = 1e-10 gs = mc.state_average_([0.5, 0.5]).nuc_grad_method().as_scanner() > e_avg, de_avg = gs(mol) ^^^^^^^ pyscf/grad/test/test_casscf.py:165: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/sacasscf.py:390: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:578: in kernel return casscf_grad.Gradients (self.base).kernel ( pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.0038885 , -0.04161642, 0.11139886, -0.01402794, 0.08576589, 0.97346762, -0.01402794, 0.08576589, 0.4... [ 0. , -0.48372621, 0.55166195, -0. ], [ 0. , 0.48372621, 0.55166195, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________ KnownValues.test_state_average_scanner_spin_penalty ______________ self = def test_state_average_scanner_spin_penalty(self): mc = mcscf.CASSCF(mf, 4, 4) mc.conv_tol = 1e-10 # B/c high sensitivity in the numerical test mc.fcisolver.conv_tol = 1e-10 mc.fix_spin_(ss=0) gs = mc.state_average_([0.5, 0.5]).nuc_grad_method().as_scanner() > e_avg, de_avg = gs(mol) ^^^^^^^ pyscf/grad/test/test_casscf.py:224: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/sacasscf.py:390: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:578: in kernel return casscf_grad.Gradients (self.base).kernel ( pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00482935, -0.0504996 , 0.13233182, -0.00832506, 0.0714718 , 1.00849964, -0.00832506, 0.0714718 , 0.4... [-0. , -0.44590478, 0.54187321, 0. ], [-0. , 0.44590478, 0.54187321, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_state_specific_scanner ____________________ self = def test_state_specific_scanner(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', verbose=0) mf = scf.RHF(mol).run(conv_tol=1e-14) mc = mcscf.CASSCF(mf, 4, 4).set(conv_tol=1e-8) gs = mc.state_specific_(2).nuc_grad_method().as_scanner() > e, de = gs(mol) ^^^^^^^ pyscf/grad/test/test_casscf.py:150: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0. , -0. , 0. , -0. , 0. , 0. , 0. , -0. , -0. ... [ 0.02485827, 0.25957075, 0.06390626, -0.43348853], [-0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_symmetrize __________________________ self = def test_symmetrize(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', symmetry=True, verbose=0) > g = mol.RHF.run().CASSCF(4, 4).run().Gradients().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casscf.py:327: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ...236454, 0. , 0. , -0.2743266 ], [ 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_qmmm_scanner ______________________ self = def test_with_qmmm_scanner(self): from pyscf import qmmm mol = gto.Mole() mol.atom = ''' O 0.00000000 0.00000000 -0.11081188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''' mol.verbose = 0 mol.basis = '6-31g' mol.build() coords = [(0.5,0.6,0.1)] #coords = [(0.0,0.0,0.0)] charges = [-0.1] mf = qmmm.add_mm_charges(scf.RHF(mol), coords, charges) mc = mcscf.CASSCF(mf, 4, 4).as_scanner() > e_tot, g = mc.nuc_grad_method().as_scanner()(mol) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_casscf.py:307: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00336389, -0.01499197, 0.01735614, 0.00290034, -0.00330789, 0.00481944, -0.00317719, 0.00723736, -0.0... [ 0.21940386, 0.19565541, -0.37112692, 0.41781175], [ 0.15115412, 0.14858309, -0.28355867, 0.3721287 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_x2c_scanner _______________________ self = def test_with_x2c_scanner(self): with lib.light_speed(20.): mc = mcscf.CASSCF(mf.x2c(), 4, 4).run(conv_tol=1e-9) gscan = mc.nuc_grad_method().as_scanner() > g1 = gscan(mol)[1] ^^^^^^^^^^ pyscf/grad/test/test_casscf.py:284: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:119: in grad_elec h1ao = hcore_deriv(ia) ^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:42: in hcore_deriv h1 = get_h1_xmol(atm_id) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:83: in hcore_deriv h1_ao, s1_ao, e1, c1, x1, s_nesc1, R1, c_fw1 = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[-0.41141982, 0.41057717, 0.0388342 , 0.0385504 , 0.00056849, -0.00048345, 0.00000664, 0.00003217, -0.00...74, 0.28413821, 0.40621792, 0.74651575, -0.04599084, -0.07509461, -0.01135018, -0.01824541]], shape=(72, 72))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_ccsd_frozen _________________________ self = def test_ccsd_frozen(self): mycc = cc.ccsd.CCSD(mf) mycc.frozen = [0,1,10,11,12] mycc.diis_start_cycle = 1 mycc.max_memory = 1 > g1 = mycc.nuc_grad_method().kernel(atmlst=range(mol.natm)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd.py:85: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:436: in kernel l1, l2 = mycc.solve_lambda(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0., 0., -0., 0., 0.], [ 0., 0., -0., -0., 0.], [-0., -0., -0., -0., -0.]]), array([[-0. ... , 0. , -0. , 0.0059558 ], [-0. , 0. , 0. , 0.00102941, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ccsd_grad __________________________ self = def test_ccsd_grad(self): mycc = cc.ccsd.CCSD(mf) mycc.max_memory = 1 mycc.conv_tol = 1e-10 eris = mycc.ao2mo() ecc, t1, t2 = mycc.kernel(eris=eris) > l1, l2 = mycc.solve_lambda(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0., 0., -0., 0., 0., 0., 0.], [ 0., 0., -0., -0., -0., -0., 0., 0.], [ 0., 0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_rdm2_mo2ao __________________________ self = def test_rdm2_mo2ao(self): mycc = cc.ccsd.CCSD(mf) mycc.conv_tol = 1e-10 mycc.diis_start_cycle = 1 eris = mycc.ao2mo() ecc, t1, t2 = mycc.kernel(eris=eris) > l1, l2 = mycc.solve_lambda(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd.py:109: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0., -0., -0., 0., 0., 0., 0.], [ 0., -0., 0., -0., -0., -0., -0., 0.], [ 0., 0., -...93], [ 0. , 0. , 0. , 0.0059843 , 0. , 0. , -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_symmetrize __________________________ self = def test_symmetrize(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', symmetry=True) > g = mol.RHF.run().CCSD().run().Gradients().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd.py:173: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:436: in kernel l1, l2 = mycc.solve_lambda(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [NPArrayWithTag([[ 0. , 0. , -0. , 0. , 0. , 0. , 0.00000001, 0. ... , 0. , 0. , 0.03071886, 0. , 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_qmmm_scanner ______________________ self = def test_with_qmmm_scanner(self): from pyscf import qmmm mol = gto.Mole() mol.atom = ''' O 0.00000000 0.00000000 -0.11081188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''' mol.verbose = 0 mol.basis = '6-31g' mol.build() coords = [(0.5,0.6,0.1)] #coords = [(0.0,0.0,0.0)] charges = [-0.1] mf = qmmm.add_mm_charges(scf.RHF(mol), coords, charges) ccs = cc.ccsd.CCSD(mf).as_scanner() e1 = ccs(''' O 0.00100000 0.00000000 -0.11081188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''') e2 = ccs(''' O -0.00100000 0.00000000 -0.11081188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''') ref = (e1 - e2)/0.002 * lib.param.BOHR > g = ccs.nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd.py:168: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:436: in kernel l1, l2 = mycc.solve_lambda(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0. , 0.00000001, -0. , 0.00000001, 0.00000001, 0. , 0.00000001, 0. ], ...82], [-0.00177507, 0.0016859 , -0.00018984, 0.00021701, 0.00691531, -0.00055246, -0.00094725, -0.00026347]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_x2c_scanner _______________________ self = def test_with_x2c_scanner(self): with lib.light_speed(20.): mycc = cc.ccsd.CCSD(mf.x2c()) mycc.frozen = [0,1,10,11,12] gscan = mycc.nuc_grad_method().as_scanner().as_scanner() > e, g1 = gscan(mol) ^^^^^^^^^^ pyscf/grad/test/test_ccsd.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:255: in __call__ cc.solve_lambda(l1=cc.l1, l2=cc.l2, eris=eris) pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0., 0., -0., 0., -0.], [-0., 0., 0., 0., -0.], [-0., -0., -0., -0., -0.]]), array([[-0. ... , 0. , -0. , -0.00377855], [-0. , -0. , -0. , 0.00203904, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_ccsd_t_frozen ________________________ self = def test_ccsd_t_frozen(self): mycc = cc.ccsd.CCSD(mf) mycc.frozen = [0,1,10,11,12] mycc.diis_start_cycle = 1 mycc.max_memory = 1 eris = mycc.ao2mo() ecc, t1, t2 = mycc.kernel(eris=eris) e3ref = ccsd_t.kernel(mycc, eris, t1, t2) > conv, l1, l2 = ccsd_t_lambda.kernel(mycc, eris, t1, t2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd_t.py:88: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_t_lambda.py:36: in kernel return ccsd_lambda.kernel(mycc, eris, t1, t2, l1, l2, max_cycle, tol, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_t_lambda.py:45: in make_intermediates imds = ccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0., 0., 0., -0., 0.], [ 0., -0., 0., -0., 0.], [-0., -0., 0., -0., -0.]]), array([[-0. ... , -0. , 0. , 0.0059558 ], [ 0. , 0. , -0. , 0.00102941, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_ccsd_t_grad _________________________ self = def test_ccsd_t_grad(self): mycc = cc.ccsd.CCSD(mf) mycc.max_memory = 1 mycc.conv_tol = 1e-10 eris = mycc.ao2mo() ecc, t1, t2 = mycc.kernel(eris=eris) e3ref = ccsd_t.kernel(mycc, eris, t1, t2) > conv, l1, l2 = ccsd_t_lambda.kernel(mycc, eris, t1, t2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ccsd_t.py:57: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd_t_lambda.py:36: in kernel return ccsd_lambda.kernel(mycc, eris, t1, t2, l1, l2, max_cycle, tol, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_t_lambda.py:45: in make_intermediates imds = ccsd_lambda.make_intermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0., -0., -0., 0., 0., -0., 0.], [ 0., 0., 0., -0., -0., -0., 0., 0.], [ 0., 0., ...93], [ 0. , 0. , -0. , 0.0059843 , -0. , -0. , 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_diab_grad_sanity _______________________ self = def test_diab_grad_sanity (self): for mcs, stype in zip (get_mc_list (), ('nosymm','symm')): for mca, atype in zip (mcs, ('nomix','mix')): for mc, itype in zip (mca, ('conv', 'DF')): ci_arr = np.asarray (mc.ci) if itype == 'conv': mc_grad = mc.nuc_grad_method () else: continue #mc_grad = dfsacasscf.Gradients (mc) # TODO: proper DF functionality eris = mc.ao2mo (mc.mo_coeff) mf_grad = mc._scf.nuc_grad_method () with self.subTest (symm=stype, solver=atype, eri=itype): dh_test = diab_grad (mc_grad, Lis, mo=mc.mo_coeff, ci=mc.ci, eris=eris, mf_grad=mf_grad) > dh_ref = diab_grad_o0 (mc_grad, Lis, mo=mc.mo_coeff, ci=mc.ci, eris=eris, mf_grad=mf_grad) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_cmspdft.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/cmspdft.py:341: in diab_grad_o0 de = Lci_dot_dgci_dx (Lci, mc.weights, mc, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0. , 0. , -0. , 0. , -0. , -0. , -0. , 0. , 0. ... , -0.05092542, 0.22007884], [-0.06055989, -0. , 0.19443597, -0. , -0.08049602, 0.5465795 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ccsd _____________________________ self = def test_ccsd(self): from pyscf import cc rhf = scf.RHF(h2o) rhf.kernel() mycc = cc.CCSD(rhf) mycc.kernel() > mycc.solve_lambda() pyscf/grad/test/test_h2o.py:108: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0.00000001, 0. , -0. , -0. , 0. , -0.00000002, 0. , 0.00000002], ...99], [ 0. , -0. , -0. , 0.00598445, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ccsd _____________________________ self = def test_ccsd(self): rhf = scf.RHF(mol) rhf.set(conv_tol=1e-10).scf() mycc = cc.CCSD(rhf) mycc.kernel() > mycc.solve_lambda() pyscf/grad/test/test_hf.py:72: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0. , 0. , -0. , 0. , -0. , 0.00000001], [-0.00000001, -0. ...31, 0. , -0. ], [-0. , -0. , 0.00421831, 0.00300548, 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_ccsd_scanner _________________________ self = def test_ccsd_scanner(self): mycc = cc.CCSD(scf.RHF(mol).set(conv_tol=1e-14)) cc_scanner = mycc.nuc_grad_method().as_scanner() > e, de = cc_scanner(mol) ^^^^^^^^^^^^^^^ pyscf/grad/test/test_hf.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:255: in __call__ cc.solve_lambda(l1=cc.l1, l2=cc.l2, eris=eris) pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0., -0., 0., -0., -0.], [ 0., 0., 0., 0., 0., 0.], [-0., 0., -0., 0., -0., -0.], ...44, 0. , 0. ], [ 0. , 0. , 0.00496044, -0.00149039, 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_dfrohf_sanity ________________________ self = def test_dfrohf_sanity (self): n_states = 3 mc_grad = diatomic( "Li", "H", 1.4, "ftpbe", "6-31g", 4, 2, n_states, density_fit=True, spin=2 ) mc_grad_ref = diatomic( "Li", "H", 1.4, "ftpbe", "6-31g", 4, (2,0), n_states, density_fit=True, ) # Numerical from this software # PySCF commit: bee0ce288a655105e27fcb0293b203939b7aecc9 # PySCF-forge commit: 50bc1da117ced9613948bee14a99a02c7b2c5769 NUM_REF = [-0.062548, -0.058501, -0.058501] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:303: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/lpdft.py:34: in get_ham_response return lpdft_grad.Gradients.get_ham_response (self, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/lpdft.py:560: in get_ham_response return lpdft_HellmanFeynman_grad( pyscf/grad/lpdft.py:318: in lpdft_HellmanFeynman_grad dvj_all = mf_grad.get_j(dm=[dm1, dm1_0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:534: in get_j return get_j(self, mol, dm, hermi) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:293: in get_j vjaux[:,:,:,p0:p1] = lib.einsum('xwp,mw,np->mnxp', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xwp,mw,np->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ... 0. , -0.00168979, 0.01979124, -0.01456446, 0.0526614 , 0.02501771, 0.07572359, 0.05545479, 0.03132718]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mw,xwp->mxp', ['np', 'mxp']), ((1, 0), 'mxp,np->mnxp', ['mnxp'])] contraction = ((1, 0), 'mw,xwp->mxp', ['np', 'mxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_hhe_lin2ftlda22_631g_slow ________________ self = def test_grad_hhe_lin2ftlda22_631g_slow(self): """System has the following Lagrange multiplier sectors: orb: yes ci: yes """ n_states = 2 # The L-PDFT ground state is flat at 1.4, so shift it slightly mc_grad = diatomic( "He", "H", 1.2, "ftLDA,VWN3", "6-31G", 2, 2, n_states, charge=1 ) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [0.012903562, -0.239149778] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:157: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0.00030963, -0.00123108, -0.00040145, 0.00211105, -0.000163 , 0.00218089, 0.00270041, -0.00008436, 0.0...0.2121942 ], [ 0.40501178, -0.34466201], [ 0.1050059 , 0.51875629], [ 0.06985611, 0.66941017]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_hhe_lin2ftlda24_631g_slow ________________ self = def test_grad_hhe_lin2ftlda24_631g_slow(self): """System has the following Lagrange multiplier sectors: orb: no ci: yes """ n_states = 2 mc_grad = diatomic( "He", "H", 1.4, "ftLDA,VWN3", "6-31G", 4, 2, n_states, charge=1 ) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [0.0025153073, -0.1444551635] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:137: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.01692673, -0.00150781, -0.0077624 , 0.02698298, -0.00074512, 0.02088282, 0.00669847, -0.00859965, 0.0... [ 0.07233064, 0.42888868, -1.27104505, -0.04492987], [ 0.05682153, 0.7189443 , 1.27160623, -0.2754204 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_hhe_lin3ftlda22_631g_slow ________________ self = def test_grad_hhe_lin3ftlda22_631g_slow(self): """System has the following Lagrange multiplier sectors: orb: yes ci: no """ n_states = 3 mc_grad = diatomic( "He", "H", 1.4, "ftLDA,VWN3", "6-31G", 2, 2, n_states, charge=1 ) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [-0.0744181053, -0.0840211222, -0.0936241392] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:118: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0., -0., -0., 0., 0., 0., 0., 0., 0., 0.], [-0., -0., -0., 0., 0., -0., 0., 0., -0., -0....0.26741049], [ 0.43612942, -0.16635486], [ 0.06022166, 0.37038942], [ 0.0794329 , 0.74288537]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_lih_lin2ftlda22_sto3g_slow _______________ self = def test_grad_lih_lin2ftlda22_sto3g_slow(self): """System has the following Lagrange multiplier sectors: orb: yes ci: yes """ n_states = 2 mc_grad = diatomic("Li", "H", 1.4, "ftLDA,VWN3", "STO-3G", 2, 2, n_states) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [-0.0302731558, -0.0528615182] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:208: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.0004522 , -0.00331167, 0.00606198, 0.0020453 , -0.00748328, 0.00230544, 0. , -0. , 0. ...0.60664909], [ 0. , -0. ], [-0. , -0. ], [ 0.62784823, -0.13572903]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_lih_lin2ftlda46_sto3g_slow _______________ self = def test_grad_lih_lin2ftlda46_sto3g_slow(self): """System has the following Lagrange multiplier sectors: orb: no ci: yes """ n_states = 2 mc_grad = diatomic("Li", "H", 1.4, "ftLDA,VWN3", "STO-3G", 6, 4, n_states) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [-0.0289711885, -0.0525535764] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:191: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0.00650948, 0.04028065, -0.04725855, -0.01127788, -0.06538705, -0.0048155 , 0. , -0. , 0. ...11, 0.85065081, 0. ], [ 0.01059277, 0.54085045, -0.12941812, -0. , 0. , 1.29097233]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_grad_lih_lin2ftpbe22_sto3g __________________ self = def test_grad_lih_lin2ftpbe22_sto3g(self): """System has the following Lagrange multiplier sectors: orb: yes ci: yes """ n_states = 2 mc_grad = diatomic("Li", "H", 1.4, "ftpbe", "STO-3G", 2, 2, n_states) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [-0.0318512447, -0.0544779213] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:225: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.000384 , -0.00280265, 0.00511214, 0.00171391, -0.00624658, 0.00190295, -0. , 0. , -0. ...0.60664909], [-0. , 0. ], [ 0. , -0. ], [ 0.62784823, -0.13572903]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ KnownValues.test_grad_lih_lin2ftpbe22_sto3g_df ________________ self = def test_grad_lih_lin2ftpbe22_sto3g_df(self): """System has the following Lagrange multiplier sectors: orb: yes ci: yes """ n_states = 2 mc_grad = diatomic( "Li", "H", 1.4, "ftpbe", "STO-3G", 2, 2, n_states, density_fit=True ) # Numerical from this software # PySCF commit: eafc3575234aca3832d270f4e1193bec2119d2b4 # PySCF-forge commit: 2e1596dc919783c751c3cf24bb776e4efcb51a34 NUM_REF = [-0.03209560095886714, -0.05453488593608611] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:265: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/lpdft.py:34: in get_ham_response return lpdft_grad.Gradients.get_ham_response (self, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/lpdft.py:560: in get_ham_response return lpdft_HellmanFeynman_grad( pyscf/grad/lpdft.py:318: in lpdft_HellmanFeynman_grad dvj_all = mf_grad.get_j(dm=[dm1, dm1_0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:534: in get_j return get_j(self, mol, dm, hermi) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:293: in get_j vjaux[:,:,:,p0:p1] = lib.einsum('xwp,mw,np->mnxp', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xwp,mw,np->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ... , -0.00127749, 0. , 0.00221268, 0.06164539, 0.0185466 , 0.08438679, 0.07373615, 0.02513397]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mw,xwp->mxp', ['np', 'mxp']), ((1, 0), 'mxp,np->mnxp', ['mnxp'])] contraction = ((1, 0), 'mw,xwp->mxp', ['np', 'mxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_lih_lin3ftlda22_sto3g_slow _______________ self = def test_grad_lih_lin3ftlda22_sto3g_slow(self): """System has the following Lagrange multiplier sectors: orb: yes ci: no """ n_states = 3 mc_grad = diatomic("Li", "H", 1.4, "ftLDA,VWN3", "STO-3G", 2, 2, n_states) # Numerical from this software # PySCF commit: 6c1ea86eb60b9527d6731efa65ef99a66b8f84d2 # PySCF-forge commit: ea0a4c164de21e84eeb30007afcb45344cfc04ff NUM_REF = [-0.0269959347, -0.052808735, -0.0785029927] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:174: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0., -0., 0., 0., 0., -0., 0., -0., -0., 0., 0., -0., -0., 0., 0., 0., 0., -0., -0., -0., -0.], ...0.39223961], [-0. , -0. ], [-0. , -0. ], [ 0.59088126, -0.3806714 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_grad_scanner _________________________ self = def test_grad_scanner(self): # Tests API and Scanner capabilities n_states = 2 mc_grad1 = diatomic( "Li", "H", 1.5, "ftLDA,VWN3", "STO-3G", 2, 2, n_states, grids_level=1 ) mol1 = mc_grad1.base.mol mc_grad2 = diatomic( "Li", "H", 1.6, "ftLDA,VWN3", "STO-3G", 2, 2, n_states, grids_level=1 ).as_scanner() for state in range(n_states): with self.subTest(state=state): > de1 = mc_grad1.kernel(state=state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:241: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00048188, -0.00352065, 0.0064293 , 0.00217203, -0.00792766, 0.00243795, -0. , 0. , -0. ...0.60906114], [-0. , 0. ], [-0. , 0. ], [ 0.62929614, -0.13802018]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_rohf_sanity _________________________ self = def test_rohf_sanity (self): n_states = 3 mc_grad = diatomic( "Li", "H", 1.4, "ftpbe", "6-31g", 4, 2, n_states, density_fit=False, spin=2 ) mc_grad_ref = diatomic( "Li", "H", 1.4, "ftpbe", "6-31g", 4, (2,0), n_states, density_fit=False ) # Numerical from this software # PySCF commit: bee0ce288a655105e27fcb0293b203939b7aecc9 # PySCF-forge commit: 50bc1da117ced9613948bee14a99a02c7b2c5769 NUM_REF = [-0.062533, -0.058472, -0.058472] for i in range(n_states): with self.subTest(state=i): > de = mc_grad.kernel(state=i)[1, 0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_lpdft.py:283: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/lpdft.py:414: in kernel return super().kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0. , 0. , -0. , 0. , -0. , -0. , 0. , -0. , -0. ... [ 0.47062449, -0.10391681, -0. , -0. ], [ 0.53078262, -0.25794327, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_gradients __________________________ self = def test_gradients (self): ref_ss = 5.29903936e-03 ref_sa = [5.66392595e-03,3.67724051e-02,3.62698260e-02,2.53851408e-02,2.53848341e-02] # Source: numerical @ this program for mc, symm in zip (mcp[0], (False, True)): with self.subTest (case='SS', symmetry=symm): > de = mc.nuc_grad_method ().kernel ()[0,0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_mcpdft.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00080189, -0.00874307, 0.01786151, -0.01784971, 0.05677535, 0.03053303, 0. , -0. , -0. ... , 0. , 1. , 0. ], [ 0.54406219, -0.13375688, 0. , -0. , 1.23748831]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_scanner ___________________________ self = def test_scanner (self): mcp1 = auto_setup (xyz='Li 0 0 0\nH 1.55 0 0')[-1] for mol0, mc0, mc1 in zip ([mol_nosym, mol_sym], mcp[0], mcp1[0]): mc0_grad = mc0.nuc_grad_method () mc1_gradscanner = mc1.nuc_grad_method ().as_scanner () > de0 = lib.fp (mc0_grad.kernel ()) ^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_mcpdft.py:89: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00080189, -0.00874307, 0.01786151, -0.01784971, 0.05677535, 0.03053303, 0. , -0. , -0. ... , 0. , 1. , 0. ], [ 0.54406219, -0.13375688, 0. , -0. , 1.23748831]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_triplet_mol _________________________ self = def test_triplet_mol (self): '''Check that energies & gradients do not depend on if the parent MF is RHF or ROHF''' mc = mcpdft.CASSCF (mf_nosym, 'ftLDA,VWN3', 5, (2,0), grids_level=1).run (mo_coeff=mcp[1][0].mo_coeff.copy ()) mc_grad = mc.nuc_grad_method () e_ref = mc.e_tot > de_ref = mc_grad.kernel () ^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_mcpdft.py:135: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00161952, -0.01675205, 0.04185119, -0.00245856, 0.00355172, -0.01335893, -0. , 0. , -0. ... , -0. , 1. , 0. ], [ 0.54403315, -0.1337428 , 0. , -0. , 1.23750272]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_triplet_mol_df ________________________ self = def test_triplet_mol_df (self): '''Check that energies & gradients do not depend on if the parent MF is RHF or ROHF Density fitting can cause a weird interaction.''' mc = mcpdft.CASSCF (mf_nosym.density_fit ().run (), 'ftLDA,VWN3', 5, (2,0), grids_level=1).run (mo_coeff=mcp[1][0].mo_coeff.copy ()) mc_grad = mc.nuc_grad_method () e_ref = mc.e_tot > de_ref = mc_grad.kernel () ^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_mcpdft.py:158: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/mcpdft.py:34: in get_ham_response return mcpdft_grad.Gradients.get_ham_response (self, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mcpdft.py:516: in get_ham_response return mcpdft_HellmanFeynman_grad( pyscf/grad/mcpdft.py:221: in mcpdft_HellmanFeynman_grad vj = mf_grad.get_jk (dm=dm1)[0] ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -1.92072641, -0. ... 0. , 0.00005833, 0. , -0.00010103, 0. , -0. , -0.00005722, 0. , 0.0000991 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_grad_lih_sa2mc2322_sto3g ___________________ self = def test_grad_lih_sa2mc2322_sto3g(self): mc = diatomic("Li", "H", 0.8, "MC23", "STO-3G", 2, 2, 2, grids_level=1) # Numerical from this software # PySCF commit: f2c2d3f963916fb64ae77241f1b44f24fa484d96 # PySCF-forge commit: e82ba940654cd0b91f799e889136a316fda34b10 DE_REF = [-1.0510225010, -0.8963063432] for state in range(2): with self.subTest(state=state): > de = mc.kernel(state=state)[1, 0] / BOHR ^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_metagga_mcpdft.py:143: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mcpdft.py:516: in get_ham_response return mcpdft_HellmanFeynman_grad( pyscf/grad/mcpdft.py:192: in mcpdft_HellmanFeynman_grad de_cas = cas_hyb * cas_grad.grad_elec( pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.24023445, -0.47481165, 0.23461051, -0.47134178, 0.46579199, 0.23119402, 0. , -0. , -0. ...0.56029073], [-0. , 0. ], [ 0. , 0. ], [ 0.62778498, -0.17091463]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_grad_lih_sa2mc2322_sto3g_df _________________ self = def test_grad_lih_sa2mc2322_sto3g_df(self): mc = diatomic( "Li", "H", 0.8, "MC23", "STO-3G", 2, 2, 2, grids_level=1, density_fit=df ) # Numerical from this software # PySCF commit: f2c2d3f963916fb64ae77241f1b44f24fa484d96 # PySCF-forge commit: ee6ac742fbc79d170bc4b63ef2b2c4b49478c53a DE_REF = [-1.0510303416, -0.8963992331] for state in range(2): with self.subTest(state=state): > de = mc.kernel(state=state)[1, 0] / BOHR ^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_metagga_mcpdft.py:158: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/mcpdft.py:34: in get_ham_response return mcpdft_grad.Gradients.get_ham_response (self, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mcpdft.py:516: in get_ham_response return mcpdft_HellmanFeynman_grad( pyscf/grad/mcpdft.py:192: in mcpdft_HellmanFeynman_grad de_cas = cas_hyb * cas_grad.grad_elec( pyscf/df/grad/casscf.py:97: in grad_elec vj, vk = mc_grad.get_jk(mol, (dm_core, dm_cas)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/casscf.py:194: in get_jk vj, vk = dfrhf_grad.get_jk(self, mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ... , -0.00102305, 0. , 0.00177197, 0.08290278, 0.02163422, 0.11197031, 0.10563832, 0.04914726]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_grad_lih_sa2tm06l22_sto3g __________________ self = def test_grad_lih_sa2tm06l22_sto3g(self): mc = diatomic("Li", "H", 0.8, "tM06L", "STO-3G", 2, 2, 2, grids_level=1) # Numerical from this software # PySCF commit: f2c2d3f963916fb64ae77241f1b44f24fa484d96 # PySCF-forge commit: 4015363355dc691a80bc94d4b2b094318b213e36 DE_REF = [-1.0351271000, -0.8919881992] for state in range(2): with self.subTest(state=state): > de = mc.kernel(state=state)[1, 0] / BOHR ^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_metagga_mcpdft.py:119: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0.00783892, 0.05349202, -0.04448202, -0.02339594, -0.01563564, 0.03125013, -0. , 0. , 0. ...0.56029073], [-0. , -0. ], [ 0. , 0. ], [ 0.62778498, -0.17091463]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_grad_lih_ssmc2322_sto3g ___________________ self = def test_grad_lih_ssmc2322_sto3g(self): mc = diatomic("Li", "H", 0.8, "MC23", "STO-3G", 2, 2, 1, grids_level=1) > de = mc.kernel()[1, 0] / BOHR ^^^^^^^^^^^ pyscf/grad/test/test_metagga_mcpdft.py:124: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mcpdft.py:516: in get_ham_response return mcpdft_HellmanFeynman_grad( pyscf/grad/mcpdft.py:192: in mcpdft_HellmanFeynman_grad de_cas = cas_hyb * cas_grad.grad_elec( pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.14046833, -0.41838378, 0.31153817, -0.42701659, 0.63593271, 0.32452718, 0. , -0. , -0. ...0.76635092], [-0. , 0. ], [ 0. , -0. ], [ 0.56317483, -1.45956459]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_grad_lih_sstm06l22_sto3g ___________________ self = def test_grad_lih_sstm06l22_sto3g(self): mc = diatomic("Li", "H", 0.8, "tM06L", "STO-3G", 2, 2, 1, grids_level=1) > de = mc.kernel()[1, 0] / BOHR ^^^^^^^^^^^ pyscf/grad/test/test_metagga_mcpdft.py:100: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00632683, 0.01464222, -0.03583785, 0.00445141, -0.05752807, -0.02138305, -0. , 0. , 0. ...0.76635092], [ 0. , -0. ], [-0. , 0. ], [ 0.56317483, -1.45956459]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_with_x2c_scanner _______________________ self = def test_with_x2c_scanner(self): with lib.light_speed(20.): pt = mp.mp2.MP2(mf.x2c()) pt.frozen = [0,1,10,11,12] gscan = pt.nuc_grad_method().as_scanner().as_scanner() > e, g1 = gscan(mol) ^^^^^^^^^^ pyscf/grad/test/test_mp2.py:129: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mp2.py:244: in __call__ de = self.kernel(mp_scanner.t2) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mp2.py:308: in kernel de = self.grad_elec(t2, atmlst, verbose=log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mp2.py:176: in grad_elec h1ao = hcore_deriv(ia) ^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:42: in hcore_deriv h1 = get_h1_xmol(atm_id) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:83: in hcore_deriv h1_ao, s1_ao, e1, c1, x1, s_nesc1, R1, c_fw1 = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.85265387, 0.07669934, 0.00488276, -0.00030835, 0.00058379, -0. , -0.00000017, 0. ...8302827, -0.14191968, 0.08551087, 0.04135178, 0.01154354, -0.00216251, -0.0042573 ]], shape=(60, 60))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_offdiag_grad_sanity _____________________ self = def test_offdiag_grad_sanity (self): for mcs, stype in zip (get_mc_list (), ('nosymm','symm')): for mca, atype in zip (mcs, ('nomix','mix')): if 'no' not in atype: continue # TODO: redesign this test case. MS-PDFT "_mix" is undefined except # for L-PDFT and XMS-PDFT, whose gradients aren't implemented yet for mc, itype in zip (mca, ('conv', 'DF')): ci_arr = np.asarray (mc.ci) if itype == 'conv': mc_grad = mc.nuc_grad_method () else: continue #mc_grad = dfsacasscf.Gradients (mc) # TODO: proper DF functionality > de_ref = np.stack ([mc_grad.get_ham_response (state=i) for i in (0,1)], axis=0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_mspdft.py:134: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/sacasscf.py:643: in get_ham_response return fcasscf_grad.kernel (mo_coeff=mo, ci=ci[state], atmlst=atmlst, verbose=verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.01664394, -0.08155976, 0.10077547, -0.00027736, 0.00241041, 0.00087276, 0.14949695, -0.36774156, -0.0... , -0.05092542, -0.22007884], [-0.06055989, 0. , 0.19443597, 0. , -0.08049602, -0.5465795 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_scanner ___________________________ self = def test_scanner (self): def get_lih (r): mol = gto.M (atom='Li 0 0 0\nH {} 0 0'.format (r), basis='sto3g', output='/dev/null', verbose=0) mf = scf.RHF (mol).run () mc = mcpdft.CASSCF (mf, 'ftLDA,VWN3', 2, 2, grids_level=1) mc.fix_spin_(ss=0) mc = mc.multi_state ([0.5,0.5], 'cms').run (conv_tol=1e-8) return mol, mc.nuc_grad_method () > mol1, mc_grad1 = get_lih (1.5) ^^^^^^^^^^^^^ pyscf/grad/test/test_mspdft.py:157: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_mspdft.py:155: in get_lih mc = mc.multi_state ([0.5,0.5], 'cms').run (conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_dfrohf_sanity ________________________ self = def test_dfrohf_sanity (self): > mc_grad = diatomic ('Li', 'H', 1.8, 'ftLDA,VWN3', '6-31g', 4, 2, 2, symmetry=True, density_fit=True, cas_irrep={'A1': 4}, spin=2) pyscf/grad/test/test_pdft_diatomic_gradients.py:206: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[1.25894582, 0.02431361], [0.02431361, 1.19244289]], [[0.02431361, 0.01727439], [...87316656], [-0.87316656, 0.48742194]]), array([[ 0.48742194, 0.87316656], [-0.87316656, 0.48742194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ KnownValues.test_grad_h2_cms2ftlda22_631g_slow ________________ self = def test_grad_h2_cms2ftlda22_631g_slow (self): # z_orb: yes # z_ci: yes # z_is: no > mc_grad = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', '6-31G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:106: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.99764075, -0. ], [-0. , 1.88438256]], [[-0. , 0.14946626], ...00000001], [-0.00000001, 1. ]]), array([[ 1. , 0.00000001], [-0.00000001, 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_h2_cms2ftlda22_sto3g_slow ________________ self = def test_grad_h2_cms2ftlda22_sto3g_slow (self): # z_orb: no # z_ci: yes # z_is: no > mc_grad = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.31567201, 0. ], [0. , 2.3243598 ]], [[0. , 0.20340799], [...00000001], [-0.00000001, 1. ]]), array([[ 1. , 0.00000001], [-0.00000001, 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ KnownValues.test_grad_h2_cms3ftlda22_631g_slow ________________ self = def test_grad_h2_cms3ftlda22_631g_slow (self): # z_orb: yes # z_ci: no # z_is: no > mc_grad = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', '6-31G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.98414506, -0. , 0.04610065], [-0. , 1.89275964, -0. ], [ 0.0461...000001, -0.33191416], [-0.00000001, 1. , 0. ], [ 0.33191416, -0. , 0.9433096 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_h2_cms3ftlda22_sto3g_slow ________________ self = def test_grad_h2_cms3ftlda22_sto3g_slow (self): # z_orb: no # z_ci: no # z_is: no > mc_grad = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', 'STO-3G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:70: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 2.31567201, 0. , 0.00543069], [ 0. , 2.3243598 , -0. ], [ 0.0054...000001, 0.49079075], [-0.00000001, 1. , -0.00000001], [-0.49079075, 0. , 0.87127747]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________ KnownValues.test_grad_lih_cms2ftlda22_sto3g_df ________________ self = def test_grad_lih_cms2ftlda22_sto3g_df (self): # z_orb: yes # z_ci: yes # z_is: yes > mc_grad = diatomic ('Li', 'H', 2.5, 'ftLDA,VWN3', 'STO-3G', 2, 2, 2, density_fit=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:181: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.59448221, -0.24786989], [-0.24786989, 1.50346521]], [[-0.24786989, 0.12118063], ...12526222], [-0.12526222, 0.99212367]]), array([[ 0.99212367, 0.12526222], [-0.12526222, 0.99212367]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_lih_cms2ftlda22_sto3g_slow _______________ self = def test_grad_lih_cms2ftlda22_sto3g_slow (self): # z_orb: yes # z_ci: yes # z_is: yes > mc_grad = diatomic ('Li', 'H', 2.5, 'ftLDA,VWN3', 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:142: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.59222469, -0.24773984], [-0.24773984, 1.50490458]], [[-0.24773984, 0.1216801 ], ...12092239], [-0.12092239, 0.99266196]]), array([[ 0.99266196, 0.12092239], [-0.12092239, 0.99266196]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_lih_cms2ftlda44_sto3g_slow _______________ self = def test_grad_lih_cms2ftlda44_sto3g_slow (self): # z_orb: no # z_ci: yes # z_is: yes > mc_grad = diatomic ('Li', 'H', 1.8, 'ftLDA,VWN3', 'STO-3G', 4, 4, 2, symmetry=True, cas_irrep={'A1': 4}) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:118: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[11.26065239, -0.09447237], [-0.09447237, 10.95773081]], [[-0.09447237, 0.02218102], ...39313965], [-0.39313965, 0.91947878]]), array([[ 0.91947878, 0.39313965], [-0.39313965, 0.91947878]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_grad_lih_cms2ftpbe22_sto3g __________________ self = def test_grad_lih_cms2ftpbe22_sto3g (self): # z_orb: yes # z_ci: yes # z_is: yes > mc_grad = diatomic ('Li', 'H', 2.5, 'ftPBE', 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:154: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.59222469, -0.24773984], [-0.24773984, 1.50490458]], [[-0.24773984, 0.1216801 ], ...12092239], [-0.12092239, 0.99266196]]), array([[ 0.99266196, 0.12092239], [-0.12092239, 0.99266196]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_grad_lih_cms2tm06l22_sto3g __________________ self = def test_grad_lih_cms2tm06l22_sto3g (self): # z_orb: yes # z_ci: yes # z_is: yes > mc_grad = diatomic ('Li', 'H', 0.8, 'tM06L', 'STO-3G', 2, 2, 2, grids_level=1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 2.20557663, -0.13171378], [-0.13171378, 1.65108086]], [[-0.13171378, 0.02305298], ...22605744], [-0.22605744, 0.97411397]]), array([[ 0.97411397, 0.22605744], [-0.22605744, 0.97411397]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_grad_lih_cms3ftlda22_sto3g_slow _______________ self = def test_grad_lih_cms3ftlda22_sto3g_slow (self): # z_orb: yes # z_ci: no # z_is: yes > mc_grad = diatomic ('Li', 'H', 2.5, 'ftLDA,VWN3', 'STO-3G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_diatomic_gradients.py:130: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.54728177, -0.21101854, 0.0074644 ], [-0.21101854, 1.58973415, 0.08792687], [ 0.0074...015242, -0.12033208], [ 0.14761893, 0.94371561, -0.29598902], [ 0.16984229, 0.27063427, 0.9475815 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_rohf_sanity _________________________ self = def test_rohf_sanity (self): > mc_grad = diatomic ('Li', 'H', 1.8, 'ftLDA,VWN3', '6-31g', 4, 2, 2, symmetry=True, cas_irrep={'A1': 4}, spin=2) pyscf/grad/test/test_pdft_diatomic_gradients.py:190: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/test/test_pdft_diatomic_gradients.py:46: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.259075 , -0.02441382], [-0.02441382, 1.19270248]], [[-0.02441382, 0.01733876], ...87940054], [ 0.87940054, 0.47608264]]), array([[ 0.47608264, -0.87940054], [ 0.87940054, 0.47608264]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_sa ______________________________ self = def test_sa (self): ref_nosymm = [-0.5126958322662911, -0.5156542636903004] ref_symm = [-0.512695920915627, -0.5156482433418408] for mol, ref in zip ((mol_nosymm, mol_symm), (ref_nosymm, ref_symm)): ref_conv, ref_df = ref mc_conv = get_mc_ref (mol, ri=False, sa2=True, mo0=mo0) mc_conv_grad = mc_conv.nuc_grad_method () mc_df = get_mc_ref (mol, ri=True, sa2=True, mo0=mo0) mc_df_grad = mc_df.nuc_grad_method () for lbl, mc_grad, ref in (('conv', mc_conv_grad, ref_conv), ('DF', mc_df_grad, ref_df)): with self.subTest (symm=mol.symmetry, eri=lbl): > test = np.stack ((mc_grad.kernel (state=0), ^^^^^^^^^^^^^^^^^^^^^^^^ mc_grad.kernel (state=1)), axis=0) pyscf/grad/test/test_pdft_h2co.py:86: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0. , 0. , -0. , -0. , 0. , -0. , -0. , 0. , -0. ... [ 0.95785604, 0. ], [-0.26288592, -0. ], [ 0.26288592, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_ss ______________________________ self = def test_ss (self): ref_nosymm = [-0.14738492029847025, -0.14788287172179898] ref_symm = [-0.14738492029577735, -0.14788570886155353] for mol, ref in zip ((mol_nosymm, mol_symm), (ref_nosymm, ref_symm)): ref_conv, ref_df = ref mc_conv = get_mc_ref (mol, ri=False, sa2=False, mo0=mo0) mc_conv_grad = mc_conv.nuc_grad_method () mc_df = get_mc_ref (mol, ri=True, sa2=False, mo0=mo0) mc_df_grad = mc_df.nuc_grad_method () for lbl, mc_grad, ref in (('conv', mc_conv_grad, ref_conv), ('DF', mc_df_grad, ref_df)): with self.subTest (symm=mol.symmetry, eri=lbl): > test = mc_grad.kernel () ^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_pdft_h2co.py:72: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mcpdft.py:616: in kernel return super().kernel (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:166: in kernel LdotJnuc = self.get_LdotJnuc (self.Lvec, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:666: in get_LdotJnuc de_Lci = Lci_dot_dgci_dx(Lci, self.weights, self.base, mo_coeff=mo, ci=ci, pyscf/grad/sacasscf.py:315: in Lci_dot_dgci_dx dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0. , 0. , 0. , 0. , 0. , -0. , 0. , 0. , 0. ... [ 0.941392 , 0. ], [-0.29240936, 0. ], [ 0.29240936, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_df_rhf_grad _________________________ self = def test_df_rhf_grad(self): g_scan = scf.RHF(mol).density_fit ().nuc_grad_method().as_scanner() > g = g_scan(mol)[1] ^^^^^^^^^^^ pyscf/grad/test/test_rhf.py:70: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:260: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:543: in get_veff vj, vk = self.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...671, 0.00078095, -0. , -0.00647602, 0. , -0.00251434, -0.00076189, 0. , 0.00144139]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_finite_diff_df_rhf_grad ___________________ self = def test_finite_diff_df_rhf_grad(self): mf = scf.RHF(mol).density_fit () mf.conv_tol = 1e-14 e0 = mf.kernel() > g = mf.nuc_grad_method ().kernel(atmlst=range(mol.natm)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_rhf.py:176: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:543: in get_veff vj, vk = self.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...671, 0.00078095, -0. , -0.00647602, 0. , -0.00251433, -0.00076188, 0. , 0.00144139]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_finite_diff_x2c_rhf_grad ___________________ self = def test_finite_diff_x2c_rhf_grad(self): mf = scf.RHF(mol).x2c() mf.conv_tol = 1e-14 e0 = mf.kernel() > g = grad.RHF(mf).kernel() ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_rhf.py:126: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:64: in grad_elec h1ao = hcore_deriv(ia) ^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:42: in hcore_deriv h1 = get_h1_xmol(atm_id) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:83: in hcore_deriv h1_ao, s1_ao, e1, c1, x1, s_nesc1, R1, c_fw1 = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.51447848, 0.02135368, 0.00100961, -0.00009752, -0.00010958, 0. , 0.00000005, 0. ...8669217, 0.14940985, -0.09338241, 0.05538922, 0.02960141, 0.01241118, 0.00265706]], shape=(60, 60))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_x2c_rhf_grad _________________________ self = def test_x2c_rhf_grad(self): h2o = gto.Mole() h2o.verbose = 0 h2o.atom = [ ['O' , (0. , 0. , 0.)], [1 , (0. , -0.757 , 0.587)], [1 , (0. , 0.757 , 0.587)] ] h2o.basis = {'H': '631g', 'O': '631g',} h2o.symmetry = True h2o.build() mf = scf.RHF(h2o).x2c() mf.conv_tol = 1e-14 e0 = mf.scf() > g1 = mf.Gradients().grad() ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_rhf.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in grad ??? pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:64: in grad_elec h1ao = hcore_deriv(ia) ^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:42: in hcore_deriv h1 = get_h1_xmol(atm_id) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:83: in hcore_deriv h1_ao, s1_ao, e1, c1, x1, s_nesc1, R1, c_fw1 = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.51447848, 0.02135368, 0.00100961, -0.00009752, -0.00010958, 0. , 0.00000005, 0. ...8669217, 0.14940985, -0.09338241, 0.05538922, 0.02960141, 0.01241118, 0.00265706]], shape=(60, 60))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_finite_diff_df_rks_grad ___________________ self = def test_finite_diff_df_rks_grad(self): mf1 = mf.density_fit ().run () > g = mf1.nuc_grad_method ().set (grid_response=True).kernel () ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_rks.py:233: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/rhf.py:53: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rks.py:75: in get_veff vj = ks_grad.get_j(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:534: in get_j return get_j(self, mol, dm, hermi) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:293: in get_j vjaux[:,:,:,p0:p1] = lib.einsum('xwp,mw,np->mnxp', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xwp,mw,np->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...978, 0.00073209, 0. , -0.00667478, 0. , -0.00332939, -0.0009414 , 0. , 0.00190354]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mw,xwp->mxp', ['np', 'mxp']), ((1, 0), 'mxp,np->mnxp', ['mnxp'])] contraction = ((1, 0), 'mw,xwp->mxp', ['np', 'mxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_finite_diff_df_rohf_grad ___________________ self = def test_finite_diff_df_rohf_grad(self): mf = scf.ROHF(mol).density_fit () mf.conv_tol = 1e-14 e0 = mf.kernel() mf_grad = mf.nuc_grad_method () > g = mf_grad.kernel() ^^^^^^^^^^^^^^^^ pyscf/grad/test/test_rohf.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uhf.py:48: in get_veff vj, vk = self.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...815, 0.00146526, 0.0010564 , -0.00296381, -0.00023661, 0.00064697, 0.00029538, 0.00003009, -0.00040994]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_finite_diff_df_roks_grad ___________________ self = def test_finite_diff_df_roks_grad(self): mf = scf.ROKS(mol).density_fit () mf.xc = 'b3lypg' mf.conv_tol = 1e-14 e0 = mf.kernel() mf_grad = mf.nuc_grad_method () > g = mf_grad.kernel() ^^^^^^^^^^^^^^^^ pyscf/grad/test/test_roks.py:74: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uks.py:83: in get_veff vj, vk = ks_grad.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...146, 0.00148739, 0.00110205, -0.00316542, -0.00018432, 0.00069609, 0.00033161, 0.0000572 , -0.000444 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_symmetrize __________________________ self = def test_symmetrize(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', symmetry=True) > g = mol.RHF.run().TDA().run(nstates=1).Gradients().kernel(state=1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrhf_grad.py:204: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [...62, 0. ], [ 0.00198915, -0.01060668, -0.05964006, -0.05813249, -0.39694226, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_tda_singlet _________________________ self = def test_tda_singlet(self): > td = tdscf.TDA(mf).run(nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrhf_grad.py:137: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.18909082, 0.96145236], [-0.00271479, 0.09518426, 0.71615962, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_tda_triplet _________________________ self = def test_tda_triplet(self): > td = tdscf.TDA(mf).run(singlet=False, nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrhf_grad.py:158: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.18909082, 0.96145236], [-0.00271479, 0.09518426, 0.71615962, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_tdhf_singlet _________________________ self = def test_tdhf_singlet(self): > td = tdscf.TDDFT(mf).run(nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrhf_grad.py:173: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.18909082, 0.96145236], [-0.00271479, 0.09518426, 0.71615962, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_tdhf_triplet _________________________ self = def test_tdhf_triplet(self): > td = tdscf.TDDFT(mf).run(singlet=False, nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrhf_grad.py:188: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.18909082, 0.96145236], [-0.00271479, 0.09518426, 0.71615962, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_tda_singlet_b3lyp_xcfun ___________________ self = @unittest.skipIf(not hasattr(dft, 'xcfun'), 'xcfun not available') def test_tda_singlet_b3lyp_xcfun(self): mf = dft.RKS(mol) mf.xc = 'b3lyp5' mf._numint.libxc = dft.xcfun mf.conv_tol = 1e-14 mf.scf() td = mf.TDA() td.nstates = nstates > e, z = td.kernel() ^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , 0.06067652, 0.97011741], [-0.00369089, 0.11456664, 0.64789329, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_tda_singlet_b88 _______________________ self = def test_tda_singlet_b88(self): > td = tdscf.TDA(mf_gga).run(conv_tol=1e-6, nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , 0. , 0.8679309 , -0.44396293], [-0.0038855 , 0.11715653, 0.62518172, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_tda_singlet_lda _______________________ self = def test_tda_singlet_lda(self): > td = tdscf.TDA(mf_lda).run(conv_tol=1e-6, nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:62: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.51403835, 0.84175544], [-0.00438958, 0.12909377, 0.64270028, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_tda_singlet_mgga _______________________ self = def test_tda_singlet_mgga(self): mf = dft.RKS(mol) mf.xc = 'm06l' mf.conv_tol = 1e-14 mf.kernel() > td = mf.TDA().run(nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:128: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , 0. , -0.20021211, 0.96357966], [-0.00329053, 0.12064273, 0.66505984, 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_tda_triplet_b3lyp ______________________ self = def test_tda_triplet_b3lyp(self): mf = dft.RKS(mol) mf.xc = 'b3lyp5' mf.conv_tol = 1e-12 mf.kernel() > td = tdscf.TDA(mf).run(singlet=False, nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.26285476, 0.93579741], [-0.00369089, 0.11456664, 0.64789329, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_tda_triplet_lda _______________________ self = def test_tda_triplet_lda(self): > td = tdscf.TDA(mf_lda).run(singlet=False, nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:68: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , -0. , -0.51403835, 0.84175544], [-0.00438958, 0.12909377, 0.64270028, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_tddft_lda __________________________ self = def test_tddft_lda(self): > td = tdscf.TDDFT(mf_lda).run(nstates=nstates, conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tdrks_grad.py:141: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rks.py:138: in kernel self.converged, w2, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rks.py:91: in vind dms = lib.einsum('xov,pv,qo->xpq', zs * (d_ia*2), orbv, orbo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0. , 0. , 0. , 0. , 0. , 0. ], [0. , 0. , 0.... , -0. , -0.25701917, 0.42087772], [-0.00219479, 0.06454688, 0.32135014, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_tda _____________________________ self = def test_tda(self): > td = tdscf.TDA(mf).run(nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduhf_grad.py:49: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , 0.23259533, 0.20870411, 0. ], [-0.00145851, 0.05829874, 0. , 0. , 0.29413557]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_tdhf _____________________________ self = def test_tdhf(self): > td = tdscf.TDDFT(mf).run(nstates=nstates, conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduhf_grad.py:60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... , 0.23259533, 0.20870411, 0. ], [-0.00145851, 0.05829874, 0. , 0. , 0.29413557]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_custom_xc __________________________ self = def test_custom_xc(self): mol = gto.Mole() mol.verbose = 0 mol.atom = [ ['H' , (0. , 0. , 1.804)], ['F' , (0. , 0. , 0.)], ] mol.unit = 'B' mol.basis = '631g' mol.charge = -2 mol.spin = 2 mol.build() mf = dft.UKS(mol).set(conv_tol=1e-14) mf.xc = '.2*HF + .8*b88, vwn' mf.grids.prune = False mf.kernel() td = mf.TDA() td.nstates = nstates > e, z = td.kernel() ^^^^^^^^^^^ pyscf/grad/test/test_tduks_grad.py:156: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0.], [0., 0., 0., 0.], [0., 0., 0., 0.], [0., 0., 0., 0.], [0., ... , 0. ], [-0.0012717 , -0.02588963, 0.38105696, -0. , -0. , -0.4619898 , -0.0400476 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_range_separated _______________________ self = def test_range_separated(self): mol = gto.M(atom="H; H 1 1.", basis='631g', verbose=0) mf = dft.UKS(mol).set(xc='CAMB3LYP') td = mf.apply(tdscf.TDA).set(nstates=nstates) tdg_scanner = td.nuc_grad_method().as_scanner() > g = tdg_scanner(mol, state=3)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduks_grad.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/tdrhf.py:225: in __call__ td_scanner(mol) pyscf/tdscf/rhf.py:695: in __call__ self.kernel(**kwargs) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[1., 0., 0.]], [[0., 1., 0.]], [[0., 0., 1.]], [[0., 0., 0.]], [[0., 0., 0.]]...497, -0.70240527, -1.26362619]]), array([[0.29773965], [0.32330336], [0.29773965], [0.32330336]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->opx', ['qo', 'opx']), ((1, 0), 'opx,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->opx', ['qo', 'opx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_tda_b88 ___________________________ self = def test_tda_b88(self): > td = tdscf.TDA(mf_gga).run(nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduks_grad.py:73: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0.... , 0.30687962, 0.074059 , -0. ], [-0.00201458, 0.06702981, 0. , 0. , 0.27323635]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_tda_lda ___________________________ self = def test_tda_lda(self): > td = tdscf.TDA(mf_lda).run(nstates=nstates) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduks_grad.py:62: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0.... , -0.15087396, 0.28273449, -0. ], [-0.00225069, 0.07067413, 0. , 0. , 0.27872952]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_tddft_b3lyp _________________________ self = def test_tddft_b3lyp(self): mf = dft.UKS(mol).set(conv_tol=1e-12) mf.xc = '.2*HF + .8*b88, vwn' mf.scf() > td = tdscf.TDDFT(mf).run(nstates=nstates, conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduks_grad.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0.... , 0.30813412, 0.04764416, 0. ], [-0.00186943, 0.06470696, -0. , -0. , 0.27474365]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_tddft_lda __________________________ self = def test_tddft_lda(self): > td = tdscf.TDDFT(mf_lda).run(nstates=nstates, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_tduks_grad.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uks.py:152: in kernel self.converged, w2, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uks.py:102: in vind dmsa = lib.einsum('xov,pv,qo->xpq', dmsa, orbva, orboa) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [0., 0.... , -0.15087396, 0.28273449, -0. ], [-0.00225069, 0.07067413, 0. , 0. , 0.27872952]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_finite_diff_df_uhf_grad ___________________ self = def test_finite_diff_df_uhf_grad(self): mf = scf.UHF(mol).density_fit () mf.conv_tol = 1e-14 e0 = mf.kernel() > g = mf.nuc_grad_method ().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_uhf.py:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uhf.py:48: in get_veff vj, vk = self.get_jk(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:527: in get_jk return get_jk(self, mol, dm, hermi, with_j, with_k) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:212: in get_jk vjaux -= lib.einsum('xpq,mp,nq->mnxp', int2c_e1, rhoj, rhoj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,mp,nq->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...048, 0.0003986 , -0. , -0.0041744 , -0. , 0.00159044, 0.00014052, -0. , -0.00083451]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']), ((1, 0), 'nxp,mp->mnxp', ['mnxp'])] contraction = ((2, 0), 'nq,xpq->nxp', ['mp', 'nxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_finite_diff_df_uks_grad ___________________ self = def test_finite_diff_df_uks_grad(self): mf1 = mf.density_fit ().run () > g = mf1.nuc_grad_method().set(grid_response=True).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_uks.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/rhf.py:409: in kernel de = self.grad_elec(mo_energy, mo_coeff, mo_occ, atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/uhf.py:50: in grad_elec vhf = mf_grad.get_veff(mol, dm0) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/uks.py:77: in get_veff vj = ks_grad.get_j(mol, dm) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:534: in get_j return get_j(self, mol, dm, hermi) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/df/grad/rhf.py:293: in get_j vjaux[:,:,:,p0:p1] = lib.einsum('xwp,mw,np->mnxp', _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xwp,mw,np->mnxp' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ...312, 0.00049827, -0. , -0.00354548, 0. , -0.0009129 , -0.00043953, 0. , 0.0002734 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mw,xwp->mxp', ['np', 'mxp']), ((1, 0), 'mxp,np->mnxp', ['mnxp'])] contraction = ((1, 0), 'mw,xwp->mxp', ['np', 'mxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_as_scanner __________________________ self = def test_as_scanner(self): pt = mp.MP2(mf) pt.frozen = [0,1,10,11,12] gscan = pt.nuc_grad_method().as_scanner() > e, g1 = gscan(mol) ^^^^^^^^^^ pyscf/grad/test/test_ump2.py:92: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mp2.py:244: in __call__ de = self.kernel(mp_scanner.t2) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/mp2.py:308: in kernel de = self.grad_elec(t2, atmlst, verbose=log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/ump2.py:67: in grad_elec part_dm2ab = lib.einsum('ijab,pa,qb->ipqj', t2ab, orbva, orbvb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijab,pa,qb->ipqj' tensors = [array([[[[-0. , 0. , 0.03235336, -0.01126444, 0. , -0. ], [ 0.00155095, -0. ...98, 0.09892495, -0. ], [-0. , -0.97692001, 1.33728916, 0.47519705, -0.24038947, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qb,ijab->jaiq', ['pa', 'jaiq']), ((1, 0), 'jaiq,pa->ipqj', ['ipqj'])] contraction = ((2, 0), 'qb,ijab->jaiq', ['pa', 'jaiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_frozen ____________________________ self = def test_frozen(self): pt = mp.MP2(mf) pt.frozen = [0,1,10,11,12] pt.max_memory = 1 pt.kernel() > g1 = ump2_grad.Gradients(pt).kernel(pt.t2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ump2.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mp2.py:308: in kernel de = self.grad_elec(t2, atmlst, verbose=log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/ump2.py:67: in grad_elec part_dm2ab = lib.einsum('ijab,pa,qb->ipqj', t2ab, orbva, orbvb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijab,pa,qb->ipqj' tensors = [array([[[[ 0. , 0. , 0.03235336, -0.01126444, -0. , 0. ], [ 0.00155095, 0. ...98, 0.09892494, 0. ], [-0. , -0.97692001, 1.33728916, 0.47519705, -0.24038946, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qb,ijab->jaiq', ['pa', 'jaiq']), ((1, 0), 'jaiq,pa->ipqj', ['ipqj'])] contraction = ((2, 0), 'qb,ijab->jaiq', ['pa', 'jaiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_mp2_grad ___________________________ self = def test_mp2_grad(self): pt = mp.MP2(mf) pt.kernel() > g1 = pt.nuc_grad_method().kernel(pt.t2, atmlst=[0,1,2]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ump2.py:48: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mp2.py:308: in kernel de = self.grad_elec(t2, atmlst, verbose=log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/ump2.py:67: in grad_elec part_dm2ab = lib.einsum('ijab,pa,qb->ipqj', t2ab, orbva, orbvb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijab,pa,qb->ipqj' tensors = [array([[[[-0. , 0. , 0.00020805, -0.00003568, -0. , 0. , -0. , 0.00050306, -0....-0. , -0.97692001, 1.33728916, 0.47519705, -0.24038946, -0. , -0.50799478, -0.99144411, -0.63119749]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qb,ijab->jiaq', ['pa', 'jiaq']), ((1, 0), 'jiaq,pa->ipqj', ['ipqj'])] contraction = ((2, 0), 'qb,ijab->jiaq', ['pa', 'jiaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_mp2_grad_finite_diff _____________________ self = def test_mp2_grad_finite_diff(self): mol = gto.M( verbose = 0, atom = 'H 0 0 0; H 0 0 1.706', basis = '631g', unit='Bohr') mp_scanner = scf.UHF(mol).set(conv_tol=1e-14).apply(mp.MP2).as_scanner() e0 = mp_scanner(mol) mol = gto.M( verbose = 0, atom = 'H 0 0 0; H 0 0 1.704', basis = '631g', unit='Bohr') e1 = mp_scanner(mol) mol = gto.M( verbose = 0, atom = 'H 0 0 0; H 0 0 1.705', basis = '631g', unit='Bohr') mp_scanner(mol) > g1 = mp_scanner.nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/test/test_ump2.py:74: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/mp2.py:308: in kernel de = self.grad_elec(t2, atmlst, verbose=log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/ump2.py:67: in grad_elec part_dm2ab = lib.einsum('ijab,pa,qb->ipqj', t2ab, orbva, orbvb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijab,pa,qb->ipqj' tensors = [array([[[[-0.06522171, -0. , 0.03206603], [-0. , -0.03562838, 0. ], [ 0.0320...513793, 1.24957185], [-0.15250383, 0.8335177 , 1.02056428], [-1.37728191, -0.69513793, -1.24957185]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pa,ijab->ijbp', ['qb', 'ijbp']), ((1, 0), 'ijbp,qb->ipqj', ['ipqj'])] contraction = ((1, 0), 'pa,ijab->ijbp', ['qb', 'ijbp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_gw_exact ___________________________ self = def test_gw_exact(self): mol = gto.Mole() mol.verbose = 7 mol.output = '/dev/null' mol.atom = [ ['O' , (0. , 0. , 0.)], ['H' , (0. , -0.757 , 0.587)], ['H' , (0. , 0.757 , 0.587)]] mol.basis = 'cc-pvdz' mol.build() mf = dft.RKS(mol) mf.xc = 'hf' mf.kernel() nocc = mol.nelectron // 2 nvir = mf.mo_energy.size - nocc td = tdscf.dRPA(mf) td.nstates = min(100, nocc*nvir) > td.kernel() pyscf/gw/test/test_gw.py:68: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rks.py:138: in kernel self.converged, w2, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rks.py:91: in vind dms = lib.einsum('xov,pv,qo->xpq', zs * (d_ia*2), orbv, orbo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[9.10736727, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , ...97, -0.02328554, -0.03177645, 0. ], [ 0.00048119, -0.02050168, -0.03267559, 0.00748959, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->opx', ['qo', 'opx']), ((1, 0), 'opx,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->opx', ['qo', 'opx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_finite_diff_x2c_rhf_hess ___________________ self = def test_finite_diff_x2c_rhf_hess(self): mf = scf.RHF(mol).x2c() mf.conv_tol = 1e-14 e0 = mf.kernel() > hess = hessian.RHF(mf).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/test/test_rhf.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/hessian/rhf.py:94: in partial_hess_elec e1, ej, ek = _partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/hessian/rhf.py:168: in _partial_hess_ejk h1ao = hcore_deriv(ia, ja) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_hess.py:44: in hcore_deriv h1 = get_h1_xmol(ia, ja) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_hess.py:195: in hcore_deriv h1i, s1i, e1i, c1i, x1i, s_nesc1i, R1i, c_fw1i = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.61493508, -0.02762147, -0.0015746 , -0.00009346, 0.00012158, -0. , -0.00000022, 0. ...9327144, 0.12925751, 0.04846175, 0.02076039, 0.00945827, 0.00376626, 0.00088942]], shape=(80, 80))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________ KnownValues.test_vv10_only_hessian_density_fitting ______________ self = def test_vv10_only_hessian_density_fitting(self): mf = make_mf(mol, nlcgrid=(6, 50), vv10_only = True, density_fitting = True) print('test_vv10_only_hessian_density_fitting') # reference_hessian = numerical_d2enlc(mf) reference_hessian = np.array([[[[ 0.542168430863188 , 0.0609222841019275, 0.405984842392626 ], [ 0.0608663024931344, 0.2411645990134659, 0.0172038828970544], [ 0.4059818139032778, 0.0171681571874416, 0.071982739693055 ]], [[ 0.0138624531238994, -0.030753281953011 , -0.011391700686314 ], [-0.0046718942045276, -0.3668973349446603, -0.0329731695137836], [-0.0077417098879456, -0.0420075016576149, 0.0212935375722978]], [[-0.5638612124752029, -0.0127755047237832, -0.4031785618546779], [-0.0421554120917378, 0.1456378880321796, -0.0166844553116663], [-0.4027474975891732, -0.0044523772413929, -0.0915300473287584]], [[ 0.0078303284871684, -0.0173934974137535, 0.008585420150975 ], [-0.0140389961968967, -0.0199051521382332, 0.032453741928784 ], [ 0.0045073935751039, 0.0292917217102895, -0.0017462299338744]]], [[[ 0.0138627725791984, -0.0044830416854325, -0.0077689479912046], [-0.0307033815374336, -0.3668782336108123, -0.0420316349443173], [-0.011416036342915 , -0.0329680821886669, 0.0213094739394681]], [[-0.0267047939085836, 0.0278498880152966, 0.0028205881821286], [ 0.0280123104940827, 0.4306583716680024, 0.0713229735657128], [ 0.002716706747629 , 0.0713137343293369, -0.0188255899165046]], [[ 0.0216086238817859, -0.031129264683738 , 0.0035280544075089], [-0.0042696833535416, -0.0574589407569825, -0.0113311991081222], [ 0.0060647834763117, -0.02382966993697 , 0.0092297279771225]], [[-0.0087666025508359, 0.0077624183455471, 0.0014203053994022], [ 0.0069607543997652, -0.0063211972930188, -0.0179601395100537], [ 0.0026345461165422, -0.01451598221619 , -0.0117136120006411]]], [[[-0.5638547756169343, -0.0421853018996998, -0.4027489367187109], [-0.0127656104511598, 0.1456436572109254, -0.0044564700579786], [-0.4031782977184095, -0.0166777303007848, -0.0915248894605147]], [[ 0.0216136396733041, -0.0042396699795333, 0.0060505042513981], [-0.0310972333722112, -0.0574617112567566, -0.0238279645358164], [ 0.0034860909206118, -0.0113321365784458, 0.0092292669409133]], [[ 0.5454448936412781, 0.0467928278031216, 0.3963708627952034], [ 0.0467864996647194, -0.0872893943619224, 0.026974441280414 ], [ 0.3963719738691029, 0.0269737337457165, 0.0825801313625307]], [[-0.0032037577029076, -0.0003678559157838, 0.0003275696731087], [-0.0029236558411472, -0.000892551613535 , 0.0013099933099392], [ 0.0033202329213777, 0.0010361331211073, -0.0002845088384884]]], [[[ 0.0078053031556946, -0.0140306109983612, 0.0045168348619118], [-0.0174043414807867, -0.0197821597556214, 0.0292915769945501], [ 0.0086166148194344, 0.0324541742315887, -0.0017644739562228]], [[-0.008832216989163 , 0.0069423500521637, 0.0026415983758188], [ 0.0077126990719739, -0.0064333042244513, -0.0144527745323808], [ 0.00154617825978 , -0.0179540412803547, -0.0117113252550149]], [[-0.0031904972070951, -0.0029275652797534, 0.0033219078221514], [-0.0003700651405314, -0.000914282871356 , 0.0010491373123589], [ 0.0003082802009224, 0.0013125269376357, -0.000284007220519 ]], [[ 0.0042174110524429, 0.010015826224008 , -0.0104803410539422], [ 0.0100617075471376, 0.0271297468399656, -0.0158879397739731], [-0.0104710732851121, -0.0158126598952257, 0.0137598064317013]]]]) > test_hessian = analytical_d2enlc(mf) ^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/test/test_vv10_hessian.py:565: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/test/test_vv10_hessian.py:110: in analytical_d2enlc analytical_hessian = hess_obj.kernel() ^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:189: in _partial_hess_ejk int2c_ip_ip = lib.einsum('xpq,qr,ysr->xyps', int2c_ip1, int2c_inv, int2c_ip1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xpq,qr,ysr->xyps' tensors = [array([[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. .... , 0. , 0. , 0. , 0. , 0. , 0. ]]], shape=(3, 190, 190))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'qr,xpq->xpr', ['ysr', 'xpr']), ((1, 0), 'xpr,ysr->xyps', ['xyps'])] contraction = ((1, 0), 'qr,xpq->xpr', ['ysr', 'xpr']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_wb97xv_hessian ________________________ self = def test_wb97xv_hessian(self): mf = make_mf(mol, nlcgrid=(6, 50), vv10_only = False, density_fitting = True) # reference_hessian = numerical_d2enlc(mf) reference_hessian = np.array([[[[ 0.4988631231107599, 0.0489672839414368, 0.2660577198785319], [ 0.0489734877394676, 0.1897255830431988, -0.0078101261571928], [ 0.2660599405173159, -0.0078137822629998, 0.1868350936873875]], [[-0.051771569530977 , -0.0366657150712157, -0.0084571181140358], [ 0.0115135376406936, -0.1374562090887821, 0.0051198866219959], [-0.0021482104426498, -0.0056229068539082, -0.0457791297491239]], [[-0.4511626969443405, -0.0005718768824048, -0.2611939416498066], [-0.0440763711142544, -0.0213677280480606, -0.0269206001783928], [-0.2624601358143241, -0.0027332207694353, -0.1460975133965592]], [[ 0.0040769871449409, -0.0117313768899785, 0.0036000488370935], [-0.0164145086085088, -0.0309006412363977, 0.0296110518733794], [-0.0014482905957292, 0.0161724903490201, 0.0050415106733204]]], [[[-0.0517810751464731, 0.0115134106239978, -0.0021413970734963], [-0.0366680715491174, -0.137456690429083 , -0.0056334229160959], [-0.0084643006763585, 0.0051188671124081, -0.045771603517375 ]], [[ 0.0605579536767445, 0.0148391214169763, 0.0368378070428887], [ 0.0148416118147185, 0.1872218688099281, 0.0352017457353471], [ 0.0368422860602124, 0.03519618041814 , 0.015470289529862 ]], [[ 0.0066125287137009, -0.0361419880820502, -0.0023317625458263], [ 0.0062373106164415, -0.0364063830698425, 0.0001598393409852], [ 0.0037036923532519, -0.0227040970159353, 0.001451774162442 ]], [[-0.0153913803045969, 0.0097899022819259, -0.0323681063152392], [ 0.0155889141273957, -0.0133553522042584, -0.0297307874967956], [-0.0320854087921818, -0.0176186038926551, 0.0288496001697447]]], [[[-0.451159345403962 , -0.0440801979015859, -0.2624618870713524], [-0.0005596911450967, -0.0213675101683464, -0.0027215831065464], [-0.2612002796613666, -0.0269246484547736, -0.1460934137018088]], [[ 0.0066130286903998, 0.0062411816443841, 0.003706422429528 ], [-0.0361560863584784, -0.0364033278010822, -0.0227120261816482], [-0.0023337153170974, 0.0001573468182414, 0.001453759111425 ]], [[ 0.4451884345406665, 0.0380248152018758, 0.2600027132105831], [ 0.0380226037735021, 0.058595325462707 , 0.0247693793083981], [ 0.2600041998666036, 0.0247752873194784, 0.1450814677061985]], [[-0.0006382995647036, -0.0001875031252485, -0.001245653350801 ], [-0.001302387582558 , -0.0008200772848854, 0.0006668422152245], [ 0.0035264024371151, 0.0019895196946285, -0.0004391935750081]]], [[[ 0.0040892562166439, -0.0164117955323562, -0.0014552053189121], [-0.0117341212848565, -0.0308982989043471, 0.0161749134836575], [ 0.0036021915061912, 0.0296147042568862, 0.0050379575677328]], [[-0.015389526193503 , 0.0156001358382341, -0.0320831071690675], [ 0.009787943389114 , -0.0133567006015411, -0.0176186446311233], [-0.0323661340360867, -0.0297316096826705, 0.0288474367043934]], [[-0.0006373766803236, -0.0013134771926215, 0.0035267654011628], [-0.000186969273841 , -0.0008195549733858, 0.0019887957584119], [-0.0012462138236913, 0.0006628131786202, -0.0004407752141056]], [[ 0.0119453748912424, 0.0021267717670859, 0.0300156238953186], [ 0.0021290136149599, 0.0450750641534936, -0.0005457257277741], [ 0.0300147763035441, -0.0005453235773223, -0.0334444976666792]]]]) > test_hessian = analytical_d2enlc(mf) ^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/test/test_vv10_hessian.py:639: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/hessian/test/test_vv10_hessian.py:110: in analytical_d2enlc analytical_hessian = hess_obj.kernel() ^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:180: in _partial_hess_ejk wk_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocc_2, mocc_2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0.... 0.00159291, 0.0001051 , -0.00249504, -0.00647684, -0.00181934, -0.01175745, -0.00699625, 0.00362396, 0.00717785]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_3operands __________________________ self = def test_3operands(self): a = numpy.random.random((7,1,3,4)) + 1j b = numpy.random.random((2,4,5,7)) c = numpy.random.random((2,8,3,6)) c0 = numpy.einsum('abcd,fdea,ficj->iebj', a, b, c) > c1 = einsum('abcd,fdea,ficj->iebj', a, b, c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/test/test_einsum.py:124: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'abcd,fdea,ficj->iebj' tensors = [array([[[[0.41584872+1.j, 0.61668507+1.j, 0.23366614+1.j, 0.10196726+1.j], [0.51585702+1.j, 0.47714099+1.j, ...825859, 0.03972871, 0.07033344], [0.47400629, 0.34916741, 0.93725206, 0.48956496, 0.53964911, 0.89526037]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'fdea,abcd->bfce', ['ficj', 'bfce']), ((1, 0), 'bfce,ficj->iebj', ['iebj'])] contraction = ((1, 0), 'fdea,abcd->bfce', ['ficj', 'bfce']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_3operands1 __________________________ self = def test_3operands1(self): a = numpy.random.random((2,2,2,2)) + 1j b = numpy.random.random((2,2,2,2)) c = numpy.random.random((2,2,2,2)) c0 = numpy.einsum('abcd,acde,adef->ebf', a, b, c) > c1 = einsum('abcd,acde,adef->ebf', a, b, c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/test/test_einsum.py:133: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'abcd,acde,adef->ebf' tensors = [array([[[[0.44663505+1.j, 0.87703439+1.j], [0.25358175+1.j, 0.2738097 +1.j]], [[0.32836139+1.j, 0.5...600849], [0.03985993, 0.13479312]], [[0.1934164 , 0.3356638 ], [0.05231295, 0.60511678]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'acde,abcd->abde', ['adef', 'abde']), ((1, 0), 'abde,adef->ebf', ['ebf'])] contraction = ((1, 0), 'acde,abcd->abde', ['adef', 'abde']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_3operands2 __________________________ self = def test_3operands2(self): a = numpy.random.random(4) ab = numpy.random.rand(4, 5) b = numpy.random.random(5) c0 = numpy.einsum('i,ij,j->ij', a, ab, b) > c1 = einsum('i,ij,j->ij', a, ab, b) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/test/test_einsum.py:142: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'i,ij,j->ij' tensors = [array([0.51206103, 0.61746101, 0.43235559, 0.84770047]), array([[0.45405906, 0.01540352, 0.87306815, 0.65620155, 0.82...0.04329094, 0.48644074, 0.23941104, 0.95247378]]), array([0.94389263, 0.613934 , 0.9734874 , 0.34486134, 0.89785072])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1, 0), 'j,ij,i->ij', ['ij'])] contraction = ((2, 1, 0), 'j,ij,i->ij', ['ij']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_4operands __________________________ self = def test_4operands(self): a = numpy.random.random((30,40,5,10)) b = numpy.random.random((10,30,5,20)) c = numpy.random.random((10,20,20)) d = numpy.random.random((20,10)) > f = lib.einsum('ijkl,xiky,ayp,px->ajl', a,b,c,d, optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/test/test_einsum.py:236: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijkl,xiky,ayp,px->ajl' tensors = [array([[[[0.43459497, 0.23581464, 0.94082796, 0.68421805, 0.06491159, 0.87042486, 0.70138029, 0.60492687, 0.7323749 ,...2125907, 0.36054459, 0.34156214, 0.08498324, 0.86527843, 0.96558069, 0.96139102, 0.74496124, 0.80788408, 0.93299308]])] kwargs = {}, contract = , optimize = True contraction_list = [((3, 2), 'px,ayp->axy', ['ijkl', 'xiky', 'axy']), ((2, 1), 'axy,xiky->kai', ['ijkl', 'kai']), ((1, 0), 'kai,ijkl->ajl', ['ajl'])] contraction = ((3, 2), 'px,ayp->axy', ['ijkl', 'xiky', 'axy']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_ibo_PM ____________________________ self = def test_ibo_PM(self): mf = scf.RHF(mol).run() > b = ibo.ibo(mol, mf.mo_coeff[:,mf.mo_occ>0], locmethod='PM', exponent=4).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lo/test/test_ibo.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lo/boys.py:63: in kernel u, g_orb, stat = next(rotaiter) ^^^^^^^^^^^^^^ pyscf/soscf/ciah.py:123: in rotate_orb_cc in davidson_cc(h_op, g_op, precond, x0_guess, pyscf/soscf/ciah.py:222: in davidson_cc ax.append(h_op(x0)) ^^^^^^^^ pyscf/lo/pipek.py:248: in h_op j1 = lib.einsum('xj,xik,kj->ij', popexp1, projR, xR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xj,xik,kj->ij' tensors = [array([[ 1.00087829, 0.85448942, 1. , 0.25649668, 0.5610601 ], [-0. , 0.00001665, -0. ... , -0. , 0. , -0. ], [ 0.04451056, -0.31630602, -0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kj,xik->xij', ['xj', 'xij']), ((1, 0), 'xij,xj->ij', ['ij'])] contraction = ((2, 1), 'kj,xik->xij', ['xj', 'xij']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_pipek ____________________________ self = def test_pipek(self): idx = numpy.array([17,20,21,22,23,30,36,41,42,47,48,49])-1 # Initial guess from Boys localization. Otherwise uncertainty between # two solutions found in PM kernel mo = boys.Boys(mol, mf.mo_coeff[:,idx]).kernel() loc = pipek.PipekMezey(mol, mo) loc.max_cycle = 100 > mo = loc.kernel() ^^^^^^^^^^^^ pyscf/lo/test/test_localizer.py:86: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lo/boys.py:63: in kernel u, g_orb, stat = next(rotaiter) ^^^^^^^^^^^^^^ pyscf/soscf/ciah.py:123: in rotate_orb_cc in davidson_cc(h_op, g_op, precond, x0_guess, pyscf/soscf/ciah.py:222: in davidson_cc ax.append(h_op(x0)) ^^^^^^^^ pyscf/lo/pipek.py:248: in h_op j1 = lib.einsum('xj,xik,kj->ij', popexp1, projR, xR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xj,xik,kj->ij' tensors = [array([[0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0...369, 0.02613749, 0.00000013, -0.00206889, 0.00424117, 0.00692391, 0.0048476 , -0.00448304, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xik,xj->ijk', ['kj', 'ijk']), ((1, 0), 'ijk,kj->ij', ['ij'])] contraction = ((1, 0), 'xik,xj->ijk', ['kj', 'ijk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_pipek_becke_scheme ______________________ self = def test_pipek_becke_scheme(self): loc = pipek.PipekMezey(h2o, mf_h2o.mo_coeff[:,3:8]) loc.pop_method = 'becke' > mo = loc.kernel() ^^^^^^^^^^^^ pyscf/lo/test/test_localizer.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lo/boys.py:63: in kernel u, g_orb, stat = next(rotaiter) ^^^^^^^^^^^^^^ pyscf/soscf/ciah.py:123: in rotate_orb_cc in davidson_cc(h_op, g_op, precond, x0_guess, pyscf/soscf/ciah.py:222: in davidson_cc ax.append(h_op(x0)) ^^^^^^^^ pyscf/lo/pipek.py:248: in h_op j1 = lib.einsum('xj,xik,kj->ij', popexp1, projR, xR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xj,xik,kj->ij' tensors = [array([[0.83786353, 0.79624422, 0.22174502, 0.25217888, 0.14588192], [0.0810682 , 0.12183445, 0.73112766, 0.08...85, -0.15312548, 0. , -0.22024624], [ 0. , -0.03470319, -0.27933718, 0.22024624, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kj,xik->xij', ['xj', 'xij']), ((1, 0), 'xij,xj->ij', ['ij'])] contraction = ((2, 1), 'kj,xik->xij', ['xj', 'xij']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_pipek_exp4 __________________________ self = def test_pipek_exp4(self): loc = pipek.PipekMezey(h2o, mf_h2o.mo_coeff[:,3:8]) loc.exponent = 4 loc.max_cycle = 100 > mo = loc.kernel() ^^^^^^^^^^^^ pyscf/lo/test/test_localizer.py:108: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lo/boys.py:63: in kernel u, g_orb, stat = next(rotaiter) ^^^^^^^^^^^^^^ pyscf/soscf/ciah.py:123: in rotate_orb_cc in davidson_cc(h_op, g_op, precond, x0_guess, pyscf/soscf/ciah.py:222: in davidson_cc ax.append(h_op(x0)) ^^^^^^^^ pyscf/lo/pipek.py:248: in h_op j1 = lib.einsum('xj,xik,kj->ij', popexp1, projR, xR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xj,xik,kj->ij' tensors = [array([[1. , 0.87561492, 0.02853584, 0.03482476, 0.0000311 ], [0. , 0.00004241, 0.32513859, 0.00...09, -0.15668413, 0. , -0.17489153], [ 0. , -0.34872412, -0.31818743, 0.17489153, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kj,xik->xij', ['xj', 'xij']), ((1, 0), 'xij,xj->ij', ['ij'])] contraction = ((2, 1), 'kj,xik->xij', ['xj', 'xij']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ Water.test_grad_hess _____________________________ self = def test_grad_hess(self): ''' Test for `get_grad` and `gen_g_hop` ''' mol = self.mol s = mol.intor_symmetric('int1e_ovlp') mo_coeff = lo.orth.schmidt(s) mo_idx = [1,6,9] mo_coeff = mo_coeff[:,mo_idx] norb = mo_coeff.shape[1] u0 = np.eye(norb) mlo = lo.pipek.PipekMezey(mol, mo_coeff) x0 = mlo.pack_uniq_var(np.zeros((norb,norb))) step_length = 1e-3 precision = 4 for exponent in [2,3,4]: mlo.set(exponent=exponent) g = mlo.get_grad(u0) g1, h_op, h_diag = mlo.gen_g_hop(u0) self.assertAlmostEqual(abs(g-g1).max(), 0, 6) H = np.zeros((norb,norb)) for i in range(norb): xi = np.zeros(norb) xi[i] = 1 > H[:,i] = h_op(xi) ^^^^^^^^ pyscf/lo/test/test_pipek.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lo/pipek.py:248: in h_op j1 = lib.einsum('xj,xik,kj->ij', popexp1, projR, xR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xj,xik,kj->ij' tensors = [array([[0.91936586, 0.01696848, 0.02551951], [0.01629409, 0.92096626, 0.96965883], [0.06334554, 0.00003... [ 0.00218541, 0.01725941, 0.00480237]]]), array([[ 0., -1., 0.], [ 1., 0., 0.], [ 0., 0., 0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xik,xj->ijk', ['kj', 'ijk']), ((1, 0), 'ijk,kj->ij', ['ij'])] contraction = ((1, 0), 'xik,xj->ijk', ['kj', 'ijk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_livvo_PM ___________________________ self = def test_livvo_PM(self): mf = scf.RHF(mol).run() nocc = numpy.sum(mf.mo_occ>0) > b = vvo.livvo(mol, mf.mo_coeff[:,0:nocc], mf.mo_coeff[:,nocc:], locmethod='PM', exponent=4).kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lo/test/test_vvo.py:71: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lo/boys.py:63: in kernel u, g_orb, stat = next(rotaiter) ^^^^^^^^^^^^^^ pyscf/soscf/ciah.py:123: in rotate_orb_cc in davidson_cc(h_op, g_op, precond, x0_guess, pyscf/soscf/ciah.py:222: in davidson_cc ax.append(h_op(x0)) ^^^^^^^^ pyscf/lo/pipek.py:248: in h_op j1 = lib.einsum('xj,xik,kj->ij', popexp1, projR, xR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xj,xik,kj->ij' tensors = [array([[0.01154281, 0.04847902], [0.05762956, 0.0322865 ], [0.058294 , 0.03183876]]), array([[[ 0.2259...963134], [ 0.36963134, 0.31694606]]]), array([[ 0. , 0.00321971], [-0.00321971, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xik,xj->ijk', ['kj', 'ijk']), ((1, 0), 'ijk,kj->ij', ['ij'])] contraction = ((1, 0), 'xik,xj->ijk', ['kj', 'ijk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_lih_cms2ftlda22 _______________________ self = def test_lih_cms2ftlda22(self): # Reference values from OpenMolcas v22.02, tag 177-gc48a1862b # Ignoring the PDFT energies and final states because of grid nonsense > mc = get_lih(1.5) ^^^^^^^^^^^^ pyscf/mcpdft/test/test_cmspdft.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_cmspdft.py:62: in get_lih mc = mc.multi_state([0.5, 0.5], "cms").run(conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_lih_cms2mc2322 ________________________ self = def test_lih_cms2mc2322(self): > mc = get_lih(1.5, fnal="MC23") ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_cmspdft.py:155: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_cmspdft.py:62: in get_lih mc = mc.multi_state([0.5, 0.5], "cms").run(conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_scanner ___________________________ self = def test_scanner(self): > mc1 = get_lih(1.5) ^^^^^^^^^^^^ pyscf/mcpdft/test/test_cmspdft.py:146: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_cmspdft.py:62: in get_lih mc = mc.multi_state([0.5, 0.5], "cms").run(conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.09509972, 0.18299461], [0.18299461, 1.56156176]], [[0.18299461, 0.03646495], [...46891756], [ 0.46891756, 0.88324194]]), array([[ 0.88324194, -0.46891756], [ 0.46891756, 0.88324194]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_h2_cms2ftlda22_631g _____________________ self = def test_h2_cms2ftlda22_631g (self): > e = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', '6-31G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[1.99764075, 0. ], [0. , 1.88438256]], [[0. , 0.14946626], [...00000001], [-0.00000001, 1. ]]), array([[ 1. , 0.00000001], [-0.00000001, 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_h2_cms2ftlda22_sto3g _____________________ self = def test_h2_cms2ftlda22_sto3g (self): > e = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:109: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.31567201, 0. ], [0. , 2.3243598 ]], [[0. , 0.20340799], [...00000001], [-0.00000001, 1. ]]), array([[ 1. , 0.00000001], [-0.00000001, 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_h2_cms3ftlda22_631g _____________________ self = def test_h2_cms3ftlda22_631g (self): > e = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', '6-31G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:120: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.98414506, 0. , -0.04610065], [ 0. , 1.89275964, -0. ], [-0.0461...000001, 0.33191416], [-0.00000001, 1. , -0.00000001], [-0.33191416, 0.00000001, 0.9433096 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_h2_cms3ftlda22_sto3g _____________________ self = def test_h2_cms3ftlda22_sto3g (self): > e = diatomic ('H', 'H', 1.3, 'ftLDA,VWN3', 'STO-3G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:98: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 2.31567201, 0. , 0.00543069], [ 0. , 2.3243598 , -0. ], [ 0.0054...000001, 0.49079075], [-0.00000001, 1. , -0.00000001], [-0.49079075, 0. , 0.87127747]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_lih_cms2ftlda22_sto3g ____________________ self = def test_lih_cms2ftlda22_sto3g (self): > e = diatomic ('Li', 'H', 2.5, 'ftLDA,VWN3', 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:153: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.59222469, -0.24773984], [-0.24773984, 1.50490458]], [[-0.24773984, 0.1216801 ], ...12092239], [-0.12092239, 0.99266196]]), array([[ 0.99266196, 0.12092239], [-0.12092239, 0.99266196]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_lih_cms2ftlda22_sto3g_df ___________________ self = def test_lih_cms2ftlda22_sto3g_df (self): > e = diatomic ('Li', 'H', 2.5, 'ftLDA,VWN3', 'STO-3G', 2, 2, 2, density_fit=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:175: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.59448221, -0.24786989], [-0.24786989, 1.50346521]], [[-0.24786989, 0.12118063], ...12526222], [-0.12526222, 0.99212367]]), array([[ 0.99212367, 0.12526222], [-0.12526222, 0.99212367]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_lih_cms2ftlda44_sto3g ____________________ self = def test_lih_cms2ftlda44_sto3g (self): > e = diatomic ('Li', 'H', 1.8, 'ftLDA,VWN3', 'STO-3G', 4, 4, 2, symmetry=True, cas_irrep={'A1': 4}) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:142: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[11.26065239, -0.09447237], [-0.09447237, 10.95773081]], [[-0.09447237, 0.02218102], ...39313965], [-0.39313965, 0.91947878]]), array([[ 0.91947878, 0.39313965], [-0.39313965, 0.91947878]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_lih_cms2ftpbe22_sto3g ____________________ self = def test_lih_cms2ftpbe22_sto3g (self): > e = diatomic ('Li', 'H', 2.5, 'ftPBE', 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:164: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.59222469, -0.24773984], [-0.24773984, 1.50490458]], [[-0.24773984, 0.1216801 ], ...12092239], [-0.12092239, 0.99266196]]), array([[ 0.99266196, 0.12092239], [-0.12092239, 0.99266196]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_lih_cms3ftlda22_sto3g ____________________ self = def test_lih_cms3ftlda22_sto3g (self): > e = diatomic ('Li', 'H', 2.5, 'ftLDA,VWN3', 'STO-3G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/test/test_diatomic_energies.py:183: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcpdft/test/test_diatomic_energies.py:88: in diatomic mc.kernel (mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.54728179, -0.21101851, 0.0074644 ], [-0.21101851, 1.58973443, 0.08792695], [ 0.0074...01531 , -0.12033229], [ 0.14761945, 0.9437154 , -0.29598944], [ 0.16984274, 0.27063454, 0.94758134]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________ KnownValues.test_make_natural_orbitals_from_restricted ____________ self = def test_make_natural_orbitals_from_restricted(self): from pyscf import mp, ci, cc npt = numpy.testing mol = gto.M(atom = 'C 0 0 0; O 0 0 1.2', basis = '3-21g', spin = 0) myhf = scf.RHF(mol).run() ncas, nelecas = (8, 10) mymc = mcscf.CASCI(myhf, ncas, nelecas) # Test MP2 # Trusted results from ORCA v4.2.1 rmp2_noons = [1.99992732,1.99989230,1.99204357,1.98051334,1.96825487,1.94377615,1.94376239,0.05792320,0.05791037,0.02833335,0.00847013,0.00531989,0.00420320,0.00420280,0.00257965,0.00101638,0.00101606,0.00085503] mymp = mp.MP2(myhf).run() > noons, natorbs = mcscf.addons.make_natural_orbitals(mymp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcscf/test/test_addons.py:215: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcscf/addons.py:327: in make_natural_orbitals rdm1 = method_obj.make_rdm1(ao_repr=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/mp2.py:171: in make_rdm1 return ccsd_rdm._make_rdm1(mp, (doo, dov, dvo, dvv), with_frozen=with_frozen, pyscf/cc/ccsd_rdm.py:275: in _make_rdm1 dm1 = lib.einsum('pi,ij,qj->pq', mo, dm1, mo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,ij,qj->pq' tensors = [array([[ 0.0002504 , 0.98626273, -0.1112472 , 0.15018705, -0. , 0. , -0.14232497, 0. , -0. ...767, 0. , 0. , 0.45854705, 0.00332605, 0. , 0. , 1.31767527, -0.95333686]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ij,pi->jp', ['qj', 'jp']), ((1, 0), 'jp,qj->pq', ['pq'])] contraction = ((1, 0), 'ij,pi->jp', ['qj', 'jp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________ KnownValues.test_make_natural_orbitals_from_unrestricted ___________ self = def test_make_natural_orbitals_from_unrestricted(self): from pyscf import mp, ci, cc npt = numpy.testing mol = gto.M(atom = 'O 0 0 0; O 0 0 1.2', basis = '3-21g', spin = 2) myhf = scf.UHF(mol).run() ncas, nelecas = (8, 12) mymc = mcscf.CASCI(myhf, ncas, nelecas) # Test UHF # The tests below are only to ensure that `make_natural_orbitals` can # run at all since we've confirmed above that the NOONs are correct for MP2 mcscf.addons.make_natural_orbitals(myhf) # Test MP2 # Trusted results from ORCA v4.2.1 rmp2_noons = [1.99992786,1.99992701,1.99414062,1.98906552,1.96095173,1.96095165,1.95280755,1.02078458,1.02078457,0.04719006,0.01274288,0.01274278,0.00728679,0.00582683,0.00543964,0.00543962,0.00290772,0.00108258] mymp = mp.UMP2(myhf).run() > noons, natorbs = mcscf.addons.make_natural_orbitals(mymp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcscf/test/test_addons.py:249: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mcscf/addons.py:327: in make_natural_orbitals rdm1 = method_obj.make_rdm1(ao_repr=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/ump2.py:266: in make_rdm1 return uccsd_rdm._make_rdm1(mp, d1, with_frozen=with_frozen, ao_repr=ao_repr) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd_rdm.py:437: in _make_rdm1 dm1a = lib.einsum('pi,ij,qj->pq', mo_a, dm1a, mo_a) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,ij,qj->pq' tensors = [array([[-0.69518127, 0.69473368, -0.16908481, -0.18493255, -0. , 0. , -0.05889934, -0. , -0. ...414, 0. , 0. , 1.32315367, 0. , 0. , -0.72779217, 0.18144185, 1.07199345]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ij,pi->jp', ['qj', 'jp']), ((1, 0), 'jp,qj->pq', ['pq'])] contraction = ((1, 0), 'ij,pi->jp', ['qj', 'jp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________ KnownValues.test_ss_s0_ethylene_zero_init_veloc ________________ self = def test_ss_s0_ethylene_zero_init_veloc(self): driver = md.NVE(casscf_scanner, dt=5, steps=10) > driver.kernel() pyscf/md/test/test_velocverlet.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/md/integrators.py:307: in kernel return kernel(self, verbose=log) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/md/integrators.py:103: in kernel for iteration, frame in enumerate(integrator): ^^^^^^^^^^^^^^^^^^^^^ pyscf/md/integrators.py:360: in __next__ current_frame = self._next() ^^^^^^^^^^^^ pyscf/md/integrators.py:464: in _next next_epot, next_accel = self._compute_accel() ^^^^^^^^^^^^^^^^^^^^^ pyscf/md/integrators.py:481: in _compute_accel e_tot, grad = self.scanner(self.mol) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.00000217, 0.00009361, 0.0010108 , 0.00010683, 0.00230706, 0.00131642, -0.00000141, -0.00003056, -0.0...0.01095665], [-0.00030528, -0.00047374], [ 0.01347588, 0.01166587], [-0.00047053, 0.00134125]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_fock_response ________________________ self = def test_fock_response(self): nmo = mf.mo_coeff.shape[1] nocc = numpy.count_nonzero(mf.mo_occ > 0) eri = mf.mol.ao2mo(mo_coeffs=mf.mo_coeff, intor='int2e', aosym=1).reshape((nmo,)*4) # test Fock response of a fully dimensioned density matrix dmfull = numpy.random.random((nmo, nmo)) > Rvo = fock_response_rhf(self.mf, dmfull) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:148: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:743: in fock_response_rhf dmao = lib.einsum('xp,pq,yq->xy', mo_coeff, dm, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70069598, 0.70055352, -0.19976736, 0.15270697, -0. , 0.01319626, 0. , 0. , 0. ...4 , 0. , 0. , -0.47498646, 0.41216157, -0.03739739, -0.51110057, -0.16183004]], shape=(48, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_memory ____________________________ self = def test_memory(self): # Dummy class to set a very low memory limit. class fakeDFMP2(DFMP2): _mem_kb = 0 @property def max_memory(self): return lib.current_memory()[0] + 1e-3 * self._mem_kb @max_memory.setter def max_memory(self, val): pass with fakeDFMP2(self.mf) as pt: E, natocc_ur, natocc_re = None, None, None pt.cphf_tol = 1e-12 # Try very low amounts of memory (in kB) until there is no failure. # Assume it should certainly work before 1 MB is reached. for m in range(20, 1000, 20): pt._mem_kb = m try: E = pt.kernel() except MemoryError: pass else: break for m in range(4, 1000, 4): pt._mem_kb = m try: natocc_ur = pt.make_natorbs()[0] except MemoryError: pass else: break for m in range(20, 1000, 20): pt._mem_kb = m try: > natocc_re = pt.make_natorbs(relaxed=True)[0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:256: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:195: in make_natorbs dm = self.make_rdm1(relaxed=relaxed, ao_repr=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:167: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:465: in make_rdm1 Lvo -= fock_response_rhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:743: in fock_response_rhf dmao = lib.einsum('xp,pq,yq->xy', mo_coeff, dm, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70069598, 0.70055352, -0.19976736, 0.15270697, -0. , 0.01319626, 0. , 0. , 0. ...4 , 0. , 0. , -0.47498646, 0.41216157, -0.03739739, -0.51110057, -0.16183004]], shape=(48, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_natorbs_relaxed _______________________ self = def test_natorbs_relaxed(self): mol = self.mf.mol with DFMP2(self.mf) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:178: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:195: in make_natorbs dm = self.make_rdm1(relaxed=relaxed, ao_repr=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:167: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:465: in make_rdm1 Lvo -= fock_response_rhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:743: in fock_response_rhf dmao = lib.einsum('xp,pq,yq->xy', mo_coeff, dm, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70069598, 0.70055352, -0.19976736, 0.15270697, -0. , 0.01319626, 0. , 0. , 0. ...4 , 0. , 0. , -0.47498646, 0.41216157, -0.03739739, -0.51110057, -0.16183004]], shape=(48, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_natorbs_relaxed_fc ______________________ self = def test_natorbs_relaxed_fc(self): mol = self.mf.mol with DFMP2(self.mf, frozen=2) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:193: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:195: in make_natorbs dm = self.make_rdm1(relaxed=relaxed, ao_repr=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:167: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:465: in make_rdm1 Lvo -= fock_response_rhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:743: in fock_response_rhf dmao = lib.einsum('xp,pq,yq->xy', mo_coeff, dm, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70069598, 0.70055352, -0.19976736, 0.15270697, -0. , 0.01319626, 0. , 0. , 0. ...4 , 0. , 0. , -0.47498646, 0.41216157, -0.03739739, -0.51110057, -0.16183004]], shape=(48, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_natorbs_relaxed_fclist ____________________ self = def test_natorbs_relaxed_fclist(self): for arr in self.mf.mo_coeff.T, self.mf.mo_occ, self.mf.mo_energy: arr[[0, 2]] = arr[[2, 0]] arr[[1, 6]] = arr[[6, 1]] mol = self.mf.mol with DFMP2(self.mf, frozen=[2, 6]) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:211: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:195: in make_natorbs dm = self.make_rdm1(relaxed=relaxed, ao_repr=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:167: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:465: in make_rdm1 Lvo -= fock_response_rhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:743: in fock_response_rhf dmao = lib.einsum('xp,pq,yq->xy', mo_coeff, dm, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[-0.19976736, 0. , 0.70069598, 0.15270697, -0. , 0.01319626, 0.70055352, 0. , 0. ...4 , 0. , 0. , -0.47498646, 0.41216157, -0.03739739, -0.51110057, -0.16183004]], shape=(48, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_scs_natorbs_relaxed _____________________ self = def test_scs_natorbs_relaxed(self): mol = self.mf.mol with SCSMP2(self.mf) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:289: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:195: in make_natorbs dm = self.make_rdm1(relaxed=relaxed, ao_repr=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:167: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:465: in make_rdm1 Lvo -= fock_response_rhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:743: in fock_response_rhf dmao = lib.einsum('xp,pq,yq->xy', mo_coeff, dm, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70069598, 0.70055352, -0.19976736, 0.15270697, -0. , 0.01319626, 0. , 0. , 0. ...4 , 0. , 0. , -0.47498646, 0.41216157, -0.03739739, -0.51110057, -0.16183004]], shape=(48, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_solve_cphf __________________________ self = def test_solve_cphf(self): nmo = mf.mo_coeff.shape[1] nocc = numpy.count_nonzero(self.mf.mo_occ > 0) nvirt = nmo - nocc # test if the CPHF solution is valid Lai = numpy.random.random((nvirt, nocc)) logger = lib.logger.new_logger(self.mf) > zai = solve_cphf_rhf(self.mf, Lai, max_cycle=50, tol=1e-12, logger=logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfmp2_native.py:167: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfmp2_native.py:775: in solve_cphf_rhf zvo = cphf.solve(fvind, mf.mo_energy, mf.mo_occ, Lvo, pyscf/scf/cphf.py:44: in solve return solve_nos1(fvind, mo_energy, mo_occ, h1, pyscf/scf/cphf.py:79: in solve_nos1 mo1 = lib.krylov(vind_vo, mo1base.reshape(-1, nvir*nocc), pyscf/lib/linalg_helper.py:1310: in krylov axt = aop(x1) ^^^^^^^ pyscf/scf/cphf.py:74: in vind_vo v = fvind(mo1).reshape(-1, nvir, nocc) ^^^^^^^^^^ pyscf/mp/dfmp2_native.py:773: in fvind return fock_response_rhf(mf, z.reshape(Lvo.shape), full=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfmp2_native.py:745: in fock_response_rhf dmao = lib.einsum('xa,ai,yi->xy', Ca, dm, Ci) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xa,ai,yi->xy' tensors = [array([[ 0. , -0.07321029, 0. , -0.09325645, -0. , -0.05745504, 0.08902076, 0.08421266, -0. ... ], [-0.00009394, 0.00082012, 0.00944404, 0.00719751, -0.00952685, -0.00140468, -0.00916875, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ai,xa->ix', ['yi', 'ix']), ((1, 0), 'ix,yi->xy', ['xy'])] contraction = ((1, 0), 'ai,xa->ix', ['yi', 'ix']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_memory ____________________________ self = def test_memory(self): # Dummy class to set a very low memory limit. class fakeDFUMP2(DFUMP2): _mem_kb = 0 @property def max_memory(self): return lib.current_memory()[0] + 1e-3 * self._mem_kb @max_memory.setter def max_memory(self, val): pass with fakeDFUMP2(self.mf) as pt: E, natocc_ur, natocc_re = None, None, None pt.cphf_tol = 1e-12 # Try very low amounts of memory (in kB) until there is no failure. # Assume it should certainly work before 1 MB is reached. for m in range(8, 1000, 8): pt._mem_kb = m try: E = pt.kernel() except MemoryError: pass else: break for m in range(4, 1000, 4): pt._mem_kb = m try: > natocc_ur = pt.make_natorbs()[0] ^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:233: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:200: in make_natorbs Sab = lib.einsum('xp,xy,yq->pq', self.mo_coeff[0, :, :], SAO, self.mo_coeff[1, :, :]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,xy,yq->pq' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.1267544 , 0.6803526 , 0.36196665, -0.62607497, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xy,xp->py', ['yq', 'py']), ((1, 0), 'py,yq->pq', ['pq'])] contraction = ((1, 0), 'xy,xp->py', ['yq', 'py']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_natorbs ___________________________ self = def test_natorbs(self): mol = self.mf.mol with DFUMP2(self.mf) as pt: > natocc, natorb = pt.make_natorbs() ^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:89: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:200: in make_natorbs Sab = lib.einsum('xp,xy,yq->pq', self.mo_coeff[0, :, :], SAO, self.mo_coeff[1, :, :]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,xy,yq->pq' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.1267544 , 0.6803526 , 0.36196665, -0.62607497, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xy,xp->py', ['yq', 'py']), ((1, 0), 'py,yq->pq', ['pq'])] contraction = ((1, 0), 'xy,xp->py', ['yq', 'py']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_natorbs_fc __________________________ self = def test_natorbs_fc(self): mol = self.mf.mol with DFUMP2(self.mf, frozen=2) as pt: > natocc, natorb = pt.make_natorbs() ^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:105: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:200: in make_natorbs Sab = lib.einsum('xp,xy,yq->pq', self.mo_coeff[0, :, :], SAO, self.mo_coeff[1, :, :]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,xy,yq->pq' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.1267544 , 0.6803526 , 0.36196665, -0.62607497, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xy,xp->py', ['yq', 'py']), ((1, 0), 'py,yq->pq', ['pq'])] contraction = ((1, 0), 'xy,xp->py', ['yq', 'py']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_natorbs_fclist ________________________ self = def test_natorbs_fclist(self): self.mf.mo_coeff[0, :, [1, 3]] = self.mf.mo_coeff[0, :, [3, 1]] self.mf.mo_energy[0, [1, 3]] = self.mf.mo_energy[0, [3, 1]] self.mf.mo_coeff[1, :, [0, 4]] = self.mf.mo_coeff[1, :, [4, 0]] self.mf.mo_energy[1, [0, 4]] = self.mf.mo_energy[1, [4, 0]] with DFUMP2(self.mf, frozen=[[0, 3], [1, 4]]) as pt: # also check the density matrix rdm1 = pt.make_rdm1() self.assertAlmostEqual(rdm1[0, 0, 0], 1.0, delta=1.0e-12) self.assertAlmostEqual(rdm1[0, 3, 3], 1.0, delta=1.0e-12) self.assertAlmostEqual(rdm1[1, 1, 1], 1.0, delta=1.0e-12) self.assertAlmostEqual(rdm1[1, 4, 4], 1.0, delta=1.0e-12) # now calculate the natural orbitals > natocc, natorb = pt.make_natorbs() ^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:133: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:200: in make_natorbs Sab = lib.einsum('xp,xy,yq->pq', self.mo_coeff[0, :, :], SAO, self.mo_coeff[1, :, :]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,xy,yq->pq' tensors = [array([[ 0.70029104, 0.22409936, 0.2118673 , 0.6999525 , 0. , 0. , 0.06702464, 0. , -0. ... , -0.1267544 , 0.6803526 , 0.36196665, -0.62607497, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xy,xp->py', ['yq', 'py']), ((1, 0), 'py,yq->pq', ['pq'])] contraction = ((1, 0), 'xy,xp->py', ['yq', 'py']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_natorbs_relaxed _______________________ self = def test_natorbs_relaxed(self): mol = self.mf.mol with DFUMP2(self.mf) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:152: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:192: in make_natorbs dm = self.make_rdm1(ao_repr=False, relaxed=relaxed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:171: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:399: in make_rdm1 Lvo_a, Lvo_b = fock_response_uhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:597: in fock_response_uhf dmao[s, :, :] = lib.einsum('xp,pq,yq->xy', mo_coeff[s], dm[s], mo_coeff[s]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.22022121, 0.65608609, 0.44653003, -0.56885909, 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_natorbs_relaxed_fc ______________________ self = def test_natorbs_relaxed_fc(self): mol = self.mf.mol with DFUMP2(self.mf, frozen=2) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:169: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:192: in make_natorbs dm = self.make_rdm1(ao_repr=False, relaxed=relaxed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:171: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:399: in make_rdm1 Lvo_a, Lvo_b = fock_response_uhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:597: in fock_response_uhf dmao[s, :, :] = lib.einsum('xp,pq,yq->xy', mo_coeff[s], dm[s], mo_coeff[s]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.22022121, 0.65608609, 0.44653003, -0.56885909, 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_natorbs_relaxed_fclist ____________________ self = def test_natorbs_relaxed_fclist(self): self.mf.mo_coeff[0, :, [0, 5]] = self.mf.mo_coeff[0, :, [5, 0]] self.mf.mo_energy[0, [0, 5]] = self.mf.mo_energy[0, [5, 0]] self.mf.mo_coeff[1, :, [1, 4]] = self.mf.mo_coeff[1, :, [4, 1]] self.mf.mo_energy[1, [1, 4]] = self.mf.mo_energy[1, [4, 1]] mol = self.mf.mol with DFUMP2(self.mf, frozen=[[1, 5], [0, 4]]) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:192: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:192: in make_natorbs dm = self.make_rdm1(ao_repr=False, relaxed=relaxed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:171: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:399: in make_rdm1 Lvo_a, Lvo_b = fock_response_uhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:597: in fock_response_uhf dmao[s, :, :] = lib.einsum('xp,pq,yq->xy', mo_coeff[s], dm[s], mo_coeff[s]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0. , 0.6999525 , 0.2118673 , 0.22409936, 0. , 0.70029104, 0.06702464, 0. , -0. ... , -0.22022121, 0.65608609, 0.44653003, -0.56885909, 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_scs_natorbs _________________________ self = def test_scs_natorbs(self): mol = self.mf.mol with SCSUMP2(self.mf) as pt: > natocc, natorb = pt.make_natorbs() ^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:263: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:200: in make_natorbs Sab = lib.einsum('xp,xy,yq->pq', self.mo_coeff[0, :, :], SAO, self.mo_coeff[1, :, :]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,xy,yq->pq' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.1267544 , 0.6803526 , 0.36196665, -0.62607497, 0. , 0. , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xy,xp->py', ['yq', 'py']), ((1, 0), 'py,yq->pq', ['pq'])] contraction = ((1, 0), 'xy,xp->py', ['yq', 'py']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_scs_natorbs_relaxed _____________________ self = def test_scs_natorbs_relaxed(self): mol = self.mf.mol with SCSUMP2(self.mf) as pt: pt.cphf_tol = 1e-12 > natocc, natorb = pt.make_natorbs(relaxed=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_dfump2_native.py:277: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/dfump2_native.py:192: in make_natorbs dm = self.make_rdm1(ao_repr=False, relaxed=relaxed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:171: in make_rdm1 rdm1_mo = make_rdm1(self, relaxed, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:399: in make_rdm1 Lvo_a, Lvo_b = fock_response_uhf(mp2._scf, rdm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/dfump2_native.py:597: in fock_response_uhf dmao[s, :, :] = lib.einsum('xp,pq,yq->xy', mo_coeff[s], dm[s], mo_coeff[s]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xp,pq,yq->xy' tensors = [array([[ 0.70029104, 0.6999525 , 0.2118673 , 0.22409936, 0. , 0. , 0.06702464, 0. , -0. ... , -0.22022121, 0.65608609, 0.44653003, -0.56885909, 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,xp->qx', ['yq', 'qx']), ((1, 0), 'qx,yq->xy', ['xy'])] contraction = ((1, 0), 'pq,xp->qx', ['yq', 'qx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_mp2_dm ____________________________ self = def test_mp2_dm(self): nocc = mol.nelectron//2 nmo = mf.mo_energy.size nvir = nmo - nocc co = mf.mo_coeff[:,:nocc] cv = mf.mo_coeff[:,nocc:] g = ao2mo.incore.general(mf._eri, (co,cv,co,cv)).ravel() eia = mf.mo_energy[:nocc,None] - mf.mo_energy[nocc:] t2ref0 = g/(eia.reshape(-1,1)+eia.reshape(-1)).ravel() t2ref0 = t2ref0.reshape(nocc,nvir,nocc,nvir).transpose(0,2,3,1) pt = mp.mp2.MP2(mf) emp2, t2 = pt.kernel() t2s = numpy.zeros((nocc*2,nocc*2,nvir*2,nvir*2)) t2s[ ::2, ::2, ::2, ::2] = t2ref0 - t2ref0.transpose(0,1,3,2) t2s[1::2,1::2,1::2,1::2] = t2ref0 - t2ref0.transpose(0,1,3,2) t2s[ ::2,1::2,1::2, ::2] = t2ref0 t2s[1::2, ::2, ::2,1::2] = t2ref0 t2s[ ::2,1::2, ::2,1::2] = -t2ref0.transpose(0,1,3,2) t2s[1::2, ::2,1::2, ::2] = -t2ref0.transpose(0,1,3,2) dm1occ =-.5 * numpy.einsum('ikab,jkab->ij', t2s, t2s) dm1vir = .5 * numpy.einsum('ijac,ijbc->ab', t2s, t2s) dm1ref = numpy.zeros((nmo,nmo)) dm1ref[:nocc,:nocc] = dm1occ[ ::2, ::2]+dm1occ[1::2,1::2] dm1ref[nocc:,nocc:] = dm1vir[ ::2, ::2]+dm1vir[1::2,1::2] for i in range(nocc): dm1ref[i,i] += 2 dm1refao = reduce(numpy.dot, (mf.mo_coeff, dm1ref, mf.mo_coeff.T)) > rdm1 = mp.mp2.make_rdm1(pt, t2ref0, ao_repr=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mp/test/test_mp2.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/mp/mp2.py:171: in make_rdm1 return ccsd_rdm._make_rdm1(mp, (doo, dov, dvo, dvv), with_frozen=with_frozen, pyscf/cc/ccsd_rdm.py:275: in _make_rdm1 dm1 = lib.einsum('pi,ij,qj->pq', mo, dm1, mo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,ij,qj->pq' tensors = [array([[ 1.00089835, -0.00818269, 0. , 0.00217106, 0. , -0.05204657, 0. , 0. , -0.06...043, 0.69344802, 0.55440149, 0.5376666 , 0. , 0. , -0.31550343, 0.49272073, 0.49430114]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ij,pi->jp', ['qj', 'jp']), ((1, 0), 'jp,qj->pq', ['pq'])] contraction = ((1, 0), 'ij,pi->jp', ['qj', 'jp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_h2_cms2ftlsda22_631g ___________________ self = def test_nac_h2_cms2ftlsda22_631g(self): # z_orb: yes # z_ci: yes # z_is: no > mc_grad = diatomic('H', 'H', 1.3, '6-31G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_cmspdft.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/test/test_cmspdft.py:73: in diatomic mc.kernel(mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[1.99764075, 0. ], [0. , 1.88438256]], [[0. , 0.14946626], [...00000001], [-0.00000001, 1. ]]), array([[ 1. , 0.00000001], [-0.00000001, 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_h2_cms2ftlsda22_sto3g __________________ self = def test_nac_h2_cms2ftlsda22_sto3g(self): # z_orb: no # z_ci: yes # z_is: no > mc_grad = diatomic('H', 'H', 1.3, 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_cmspdft.py:92: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/test/test_cmspdft.py:73: in diatomic mc.kernel(mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.31567201, 0. ], [0. , 2.3243598 ]], [[0. , 0.20340799], [...00000001], [-0.00000001, 1. ]]), array([[ 1. , 0.00000001], [-0.00000001, 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_h2_cms3ftlsda22_631g ___________________ self = def test_nac_h2_cms3ftlsda22_631g(self): # z_orb: yes # z_ci: no # z_is: no > mc_grad = diatomic('H', 'H', 1.3, '6-31G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_cmspdft.py:152: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/test/test_cmspdft.py:73: in diatomic mc.kernel(mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.98414506, -0. , 0.04610065], [-0. , 1.89275964, 0. ], [ 0.0461...000001, -0.33191416], [-0.00000001, 1. , 0.00000001], [ 0.33191416, -0.00000001, 0.9433096 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_h2_cms3ftlsda22_sto3g __________________ self = def test_nac_h2_cms3ftlsda22_sto3g(self): # z_orb: no # z_ci: no # z_is: no > mc_grad = diatomic('H', 'H', 1.3, 'STO-3G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_cmspdft.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/test/test_cmspdft.py:73: in diatomic mc.kernel(mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 2.31567201, 0. , 0.00543069], [ 0. , 2.3243598 , -0. ], [ 0.0054...000001, 0.49079075], [-0.00000001, 1. , -0.00000001], [-0.49079075, 0. , 0.87127747]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_nac_lih_cms2ftlsda22_sto3g __________________ self = def test_nac_lih_cms2ftlsda22_sto3g(self): # z_orb: yes # z_ci: yes # z_is: yes > mc_grad = diatomic('Li', 'H', 1.5, 'STO-3G', 2, 2, 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_cmspdft.py:172: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/test/test_cmspdft.py:73: in diatomic mc.kernel(mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[2.0950961 , 0.18299995], [0.18299995, 1.56156628]], [[0.18299995, 0.03646712], [...46896178], [ 0.46896178, 0.88321846]]), array([[ 0.88321846, -0.46896178], [ 0.46896178, 0.88321846]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________ KnownValues.test_nac_lih_cms3ftlsda22_sto3g __________________ self = def test_nac_lih_cms3ftlsda22_sto3g(self): # z_orb: yes # z_ci: no # z_is: yes > mc_grad = diatomic('Li', 'H', 2.5, 'STO-3G', 2, 2, 3) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_cmspdft.py:191: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/test/test_cmspdft.py:73: in diatomic mc.kernel(mo) pyscf/mcpdft/mspdft.py:370: in kernel diab_conv, self.ci = self.diabatize (ci=self.ci, ci0=ci0, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:429: in diabatize return self._diabatize (self, ci=ci, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/mcpdft/mspdft.py:188: in si_newton f, df, d2f = f_update (u) ^^^^^^^^^^^^ pyscf/mcpdft/cmspdft.py:99: in Qaa_update w1 = ao2mo.incore.full (w0, u, compact=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:64: in full return general(eri_ao, (mo_coeff,)*4, verbose, compact) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/ao2mo/incore.py:125: in general return lib.einsum('pqrs,pi,qj,rk,sl->ijkl', eri_ao.reshape([nao]*4), _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pqrs,pi,qj,rk,sl->ijkl' tensors = [array([[[[ 1.54728175, 0.21101855, 0.00746439], [ 0.21101855, 1.58973398, -0.08792682], [ 0.0074...015201, -0.12033195], [-0.14761862, 0.94371574, 0.29598876], [ 0.16984202, -0.2706341 , 0.94758159]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']), ((3, 0), 'iqrs,qj->ijrs', ['rk', 'sl', 'ijrs']), ((2, 0), 'ijrs,rk->ijks', ['sl', 'ijks']), ((1, 0), 'ijks,sl->ijkl', ['ijkl'])] contraction = ((1, 0), 'pi,pqrs->iqrs', ['qj', 'rk', 'sl', 'iqrs']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_nac_h2_sa2caasf22_631g ____________________ self = def test_nac_h2_sa2caasf22_631g(self): # z_orb: yes # z_ci: yes # z_is: no mc_grad = diatomic('H', 'H', 1.3, '6-31G', 2, 2, 2) # OpenMolcas v23.02 - PC de_ref = np.array([[2.63335709207419E-01,2.63335709207420E-01], [-4.13635186565710E-16,4.47060252146777E-16 ]]) for i in range(2): with self.subTest(use_etfs=bool(i)): > de = mc_grad.kernel(state=(0, 1), use_etfs=bool(i))[:, 0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_sacasscf.py:111: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/sacasscf.py:244: in kernel nac = sacasscf_grad.Gradients.kernel (self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/sacasscf.py:215: in get_ham_response nac = grad_elec_active (fcasscf_grad, mo_coeff=mo, ci=ci[ket], pyscf/nac/sacasscf.py:55: in grad_elec_active de = mc_grad.grad_elec (mo_coeff=mo_coeff, ci=ci, atmlst=atmlst, pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.07470617, 0.43053559, 0.48575543, -0. , 0.20051228, -0.07470617, -0.20051228, -0. , -0.4...0.21506701], [ 0.3878307 , 0.90834244], [ 0.25191663, -0.21506701], [ 0.3878307 , -0.90834244]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_h2_sa2casscf22_sto3g ___________________ self = def test_nac_h2_sa2casscf22_sto3g(self): # z_orb: no # z_ci: yes # z_is: no mc_grad = diatomic('H', 'H', 1.3, 'STO-3G', 2, 2, 2) # OpenMolcas v23.02 - PC de_ref = np.array([[2.24611972496341E-01, 2.24611972496341E-01], [3.91518173397213E-18, -3.91518173397213E-18]]) for i in range(2): with self.subTest(use_etfs=bool(i)): > de = mc_grad.kernel(state=(0, 1), use_etfs=bool(i))[:, 0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_sacasscf.py:75: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/sacasscf.py:244: in kernel nac = sacasscf_grad.Gradients.kernel (self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/sacasscf.py:215: in get_ham_response nac = grad_elec_active (fcasscf_grad, mo_coeff=mo, ci=ci[ket], pyscf/nac/sacasscf.py:55: in grad_elec_active de = mc_grad.grad_elec (mo_coeff=mo_coeff, ci=ci, atmlst=atmlst, pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.72249772, 0. , -0.72249772], [ 0.10630775, 0.80256829, 0.10630775]], [[ 0.10630...0723613]]]), array([[0.61106028, 0.86977288]]), array([[ 0.61106028, 0.86977288], [ 0.61106028, -0.86977288]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_nac_h2_sa3casscf22_631g ___________________ self = def test_nac_h2_sa3casscf22_631g(self): # z_orb: yes # z_ci: no # z_is: no mc_grad = diatomic('H', 'H', 1.3, '6-31G', 2, 2, 3) # OpenMolcas v23.02 - PC de_ref = np.array([[-2.61263051047980E-01,-2.61263051047980E-01], [-5.77124316768522E-17,2.47338992900795E-17 ]]) for i in range(2): with self.subTest(use_etfs=bool(i)): > de = mc_grad.kernel(state=(0, 1), use_etfs=bool(i))[:, 0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_sacasscf.py:130: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/sacasscf.py:244: in kernel nac = sacasscf_grad.Gradients.kernel (self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/sacasscf.py:215: in get_ham_response nac = grad_elec_active (fcasscf_grad, mo_coeff=mo, ci=ci[ket], pyscf/nac/sacasscf.py:55: in grad_elec_active de = mc_grad.grad_elec (mo_coeff=mo_coeff, ci=ci, atmlst=atmlst, pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[-0.01985904, -0.10106412, -0.11178384, -0. , -0.0365278 , 0.01985904, 0.0365278 , 0. , 0.1...0.2428503 ], [-0.86533082, 0.39459786], [ 0.24979135, 0.2428503 ], [ 0.86533082, 0.39459786]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_h2_sa3casscf22_sto3g ___________________ self = def test_nac_h2_sa3casscf22_sto3g(self): # z_orb: no # z_ci: no # z_is: no mc_grad = diatomic('H', 'H', 1.3, 'STO-3G', 2, 2, 3) # OpenMolcas v23.02 - PC de_ref = np.array([[2.24611972496341E-01,2.24611972496341E-01 ], [3.91518173397213E-18, -3.91518173397213E-18]]) for i in range(2): with self.subTest(use_etfs=bool(i)): > de = mc_grad.kernel(state=(0, 1), use_etfs=bool(i))[:, 0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_sacasscf.py:93: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/sacasscf.py:244: in kernel nac = sacasscf_grad.Gradients.kernel (self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/sacasscf.py:215: in get_ham_response nac = grad_elec_active (fcasscf_grad, mo_coeff=mo, ci=ci[ket], pyscf/nac/sacasscf.py:55: in grad_elec_active de = mc_grad.grad_elec (mo_coeff=mo_coeff, ci=ci, atmlst=atmlst, pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.02498557, 0.59566226, 0.13281661], [ 0.41626769, 0.53786833, -0.27377622]], [[ 0.41626...480782 ]]]), array([[1.04297242, 0.20520248]]), array([[ 1.04297242, 0.20520248], [-0.54668302, 0.91161242]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_lih_cms3ftlda22_sto3g __________________ self = def test_nac_lih_cms3ftlda22_sto3g(self): # z_orb: yes # z_ci: no # z_is: yes mc_grad = diatomic('Li', 'H', 2.5, 'STO-3G', 2, 2, 3) # OpenMolcas v23.02 - PC de_ref = np.array([[2.68015835251472E-01, -6.48474666167559E-02], [1.24870721811750E-01, -1.24870721811750E-01]]) for i in range(2): with self.subTest(use_etfs=bool(i)): > de = mc_grad.kernel(state=(0, 1), use_etfs=bool(i))[:, 0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_sacasscf.py:165: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/sacasscf.py:244: in kernel nac = sacasscf_grad.Gradients.kernel (self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/sacasscf.py:215: in get_ham_response nac = grad_elec_active (fcasscf_grad, mo_coeff=mo, ci=ci[ket], pyscf/nac/sacasscf.py:55: in grad_elec_active de = mc_grad.grad_elec (mo_coeff=mo_coeff, ci=ci, atmlst=atmlst, pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.01521983, -0.10620536, 0.18506684, -0.0570329 , 0.20324229, 0.03199508, 0. , -0. , -0. ...0.39094189], [-0. , 0. ], [ 0. , -0. ], [ 0.04884439, 0.82273254]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_nac_lih_sa2casscf22_sto3g __________________ self = def test_nac_lih_sa2casscf22_sto3g(self): # z_orb: yes # z_ci: yes # z_is: yes mc_grad = diatomic('Li', 'H', 1.5, 'STO-3G', 2, 2, 2) # OpenMolcas v23.02 - PC de_ref = np.array([[1.83701729060390E-01, -6.91462064586138E-02], [9.14842536971979E-02, -9.14842536971979E-02]]) for i in range(2): with self.subTest(use_etfs=bool(i)): > de = mc_grad.kernel(state=(0, 1), use_etfs=bool(i))[:, 0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/test/test_sacasscf.py:147: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/nac/sacasscf.py:244: in kernel nac = sacasscf_grad.Gradients.kernel (self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/sacasscf.py:586: in kernel return lagrange.Gradients.kernel ( pyscf/grad/lagrange.py:158: in kernel ham_response = self.get_ham_response (**kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/nac/sacasscf.py:215: in get_ham_response nac = grad_elec_active (fcasscf_grad, mo_coeff=mo, ci=ci[ket], pyscf/nac/sacasscf.py:55: in grad_elec_active de = mc_grad.grad_elec (mo_coeff=mo_coeff, ci=ci, atmlst=atmlst, pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.04411311, -0.28927037, 0.43671456, 0.10573437, -0.1351899 , -0.23476812, -0. , 0. , -0. ...0.57511412], [ 0. , 0. ], [-0. , 0. ], [ 0.64059413, -0.06857374]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']), ((1, 0), 'jpw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->jpw', ['qj', 'jpw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_ea_adc3_supercell_vs_k ____________________ self = def test_ea_adc3_supercell_vs_k(self): myadc.method = 'adc(3)' > e1,v1,p1,x1 = myadc.kernel(nroots=3) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/adc/test/test_k_vs_supercell_ea.py:98: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/adc/radc.py:390: in kernel e_exc, v_exc, spec_fac, x, adc_es = self.ea_adc(nroots=nroots, guess=guess, eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc.py:416: in ea_adc e_exc, v_exc, spec_fac, x = adc_es.kernel(nroots, guess, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/adc/radc.py:64: in kernel imds = adc.get_imds(eris) ^^^^^^^^^^^^^^^^^^ pyscf/adc/radc_ea.py:259: in get_imds temp[a:b] -= lib.einsum('mldf,mled,aebf->ab',t2_1, t2_1, vvvv, optimize=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'mldf,mled,aebf->ab' tensors = [array([[[[-0.02017038, 0. , -0. , 0. ], [ 0. , -0.01658407, 0. , -0. ... 0. , 0. , 0.04584872, -0.00000001], [-0. , 0. , -0.00000001, 0.02176406]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mled,mldf->ef', ['aebf', 'ef']), ((1, 0), 'ef,aebf->ab', ['ab'])] contraction = ((1, 0), 'mled,mldf->ef', ['aebf', 'ef']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_he_112_diag _________________________ self = def test_he_112_diag(self): kpts = cell.make_kpts([1,1,2]) kmf = pbcscf.KGHF(cell, kpts, exxdiv=None) Escf = kmf.scf() cc = kccsd.KGCCSD(kmf) > Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_kgccsd_diag.py:96: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+..., 0. -0.j, -0. +0.j], [ 0. -0.j, -0.00000001+0.j, -0. +0.j, -0.00992141-0.j]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_he_131_diag _________________________ self = def test_he_131_diag(self): kpts = cell.make_kpts([1,3,1]) kmf = pbcscf.KGHF(cell, kpts, exxdiv=None) Escf = kmf.scf() cc = kccsd.KGCCSD(kmf) > Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_kgccsd_diag.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+..., -0. -0.j, -0. -0.j], [-0. +0.j, -0.00000001+0.j, 0. +0.j, -0.00661427-0.j]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_supercell_vs_kpt _______________________ self = def test_supercell_vs_kpt(self): # Running HF and CCSD with 1x1x2 Monkhorst-Pack k-point mesh kmf = pbcscf.KGHF(cell, kpts=cell.make_kpts(KGCCSD_TEST_NMP), exxdiv=None) kmf.kernel() mycc = pbcc.KGCCSD(kmf) mycc.conv_tol = 1e-12 mycc.conv_tol_normt = 1e-10 > ecc2, t1, t2 = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_kgccsd_diag.py:128: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+..., -0. +0.j, -0. +0.j], [-0. -0.j, -0.00000001+0.j, 0. -0.j, -0.00992141+0.j]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_eomea_l_matvec ________________________ self = def test_eomea_l_matvec(self): np.random.seed(2) # Running HF and CCSD with 1x1x2 Monkhorst-Pack k-point mesh kmf = pbcscf.KRHF(cell, kpts=cell.make_kpts([1, 1, 3]), exxdiv=None) nmo = cell.nao_nr() kmf.mo_occ = np.zeros((3, nmo)) kmf.mo_occ[:, :2] = 2 kmf.mo_energy = np.arange(nmo) + np.random.random((3, nmo)) * .3 kmf.mo_energy[kmf.mo_occ == 0] += 2 kmf.mo_coeff = (np.random.random((3, nmo, nmo)) + np.random.random((3, nmo, nmo)) * 1j - .5 - .5j) mycc = pbcc.KRCCSD(kmf) t1, t2 = rand_t1_t2(kmf, mycc) mycc.t1 = t1 mycc.t2 = t2 eris = mycc.ao2mo() eom = EOMEA(mycc) > imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:528: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/eom_kccsd_rhf.py:815: in make_imds imds.make_ea() pyscf/pbc/cc/eom_kccsd_rhf.py:1595: in make_ea self._make_shared_1e() pyscf/pbc/cc/eom_kccsd_rhf.py:1522: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:86: in Loo Lki = cc_Foo(t1,t2,eris,kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.00281668+0.0001208j , 0.00349808+0.0050177j ], [ 0.00349808+0.0050177j , -0.00124074+0.010289j...array([[-0.082978 -0.29554775j, 0.22032449+0.37811744j], [-0.49988563-0.47261241j, -0.19766743+0.17046751j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_eomea_matvec _________________________ self = def test_eomea_matvec(self): np.random.seed(2) # Running HF and CCSD with 1x1x2 Monkhorst-Pack k-point mesh kmf = pbcscf.KRHF(cell, kpts=cell.make_kpts([1, 1, 3]), exxdiv=None) nmo = cell.nao_nr() kmf.mo_occ = np.zeros((3, nmo)) kmf.mo_occ[:, :2] = 2 kmf.mo_energy = np.arange(nmo) + np.random.random((3, nmo)) * .3 kmf.mo_energy[kmf.mo_occ == 0] += 2 kmf.mo_coeff = (np.random.random((3, nmo, nmo)) + np.random.random((3, nmo, nmo)) * 1j - .5 - .5j) mycc = pbcc.KRCCSD(kmf) t1, t2 = rand_t1_t2(kmf, mycc) mycc.t1 = t1 mycc.t2 = t2 eris = mycc.ao2mo() eom = EOMEA(mycc) > imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:475: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/eom_kccsd_rhf.py:815: in make_imds imds.make_ea() pyscf/pbc/cc/eom_kccsd_rhf.py:1595: in make_ea self._make_shared_1e() pyscf/pbc/cc/eom_kccsd_rhf.py:1522: in _make_shared_1e self.Loo = imd.Loo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:86: in Loo Lki = cc_Foo(t1,t2,eris,kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.00281668+0.0001208j , 0.00349808+0.0050177j ], [ 0.00349808+0.0050177j , -0.00124074+0.010289j...array([[-0.082978 -0.29554775j, 0.22032449+0.37811744j], [-0.49988563-0.47261241j, -0.19766743+0.17046751j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_n3_diffuse __________________________ self = def test_n3_diffuse(self): nk = (1, 1, 2) ehf_bench = -6.1870676561720721 ecc_bench = -0.06764836939412185 cc = pbcc.kccsd_rhf.RCCSD(kmf) cc.conv_tol = 1e-9 eris = cc.ao2mo() > ecc, t1, t2 = cc.kernel(eris=eris) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.03150926-0.00000004j, -0.00000002-0.j , -0. -0.j , -0.00009076-0.j ], ... [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_n3_diffuse_Ta ________________________ self = def test_n3_diffuse_Ta(self): nk = (1, 1, 2) ehf_bench = -6.1870676561720721 ecc_bench = -0.06764836939412185 cc = pbcc.kccsd_rhf.RCCSD(kmf) cc.conv_tol = 1e-8 eris = cc.ao2mo() eris.mo_energy = [eris.fock[ikpt].diagonal().real for ikpt in range(cc.nkpts)] > ecc, t1, t2 = cc.kernel(eris=eris) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:209: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.03150926-0.00000004j, -0.00000002-0.j , -0. -0.j , -0.00009076-0.j ], ... [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________ KnownValues.test_n3_diffuse_Ta_against_so ___________________ self = def test_n3_diffuse_Ta_against_so(self): ehf_bench = -6.1870676561720721 ecc_bench = -0.06764836939412185 cc = pbcc.kccsd_rhf.RCCSD(kmf) cc.conv_tol = 1e-10 eris = cc.ao2mo() eris.mo_energy = [eris.fock[ikpt].diagonal().real for ikpt in range(cc.nkpts)] > ecc, t1, t2 = cc.kernel(eris=eris) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:237: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.03150926-0.00000004j, -0.00000002-0.j , -0. -0.j , -0.00009076-0.j ], ... [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_n3_diffuse_frozen ______________________ self = def test_n3_diffuse_frozen(self): nk = (1, 1, 2) ehf_bench = -6.1870676561720721 ecc_bench = -0.0442506265840587 cc = pbcc.kccsd_rhf.RCCSD(kmf, frozen=[[0],[0,1]]) cc.conv_tol = 1e-10 eris = cc.ao2mo() > ecc, t1, t2 = cc.kernel(eris=eris) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:181: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.0211641 +0.00005718j, 0.01009451+0.00052897j, -0.00000002+0.j , -0.00257379-0.00000696j], ...([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_n3_ee ____________________________ self = def test_n3_ee(self): n = 15 cell_n3 = make_test_cell.test_cell_n3([n]*3) kmf_n3 = pbcscf.KRHF(cell_n3, cell_n3.make_kpts([2,1,1]), exxdiv=None) kmf_n3.kernel() kmf_n3_ewald = pbcscf.KRHF(cell_n3, cell_n3.make_kpts([2,1,1]), exxdiv='ewald') kmf_n3_ewald.kernel() ehf_bench = [-8.651923514149, -10.530905169078] ecc_bench = [-0.155298299344, -0.093617975270] ekrhf = kmf_n3.e_tot self.assertAlmostEqual(ekrhf, ehf_bench[0], 3) ekrhf = kmf_n3_ewald.e_tot self.assertAlmostEqual(ekrhf, ehf_bench[1], 3) mycc = pbcc.KRCCSD(kmf_n3) > ekrcc, t1, t2 = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_krccsd.py:287: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.02897239-0.00000108j, 0.00000024-0.j , 0. -0.j , 0.00077127-0.00000001j], ... [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_eomea_matvec _________________________ self = def test_eomea_matvec(self): cell = gto.Cell() cell.atom=''' He 0.000000000000 0.000000000000 0.000000000000 He 1.685068664391 1.685068664391 1.685068664391 ''' cell.basis = [[0, (1., 1.)], [0, (.5, 1.)]] cell.a = ''' 0.000000000, 3.370137329, 3.370137329 3.370137329, 0.000000000, 3.370137329 3.370137329, 3.370137329, 0.000000000''' cell.unit = 'B' cell.mesh = [13]*3 cell.precision = 1e-10 cell.build() np.random.seed(2) kmf = pbcscf.KUHF(cell, kpts=cell.make_kpts([1,1,3]), exxdiv=None) nmo = cell.nao_nr() kmf.mo_occ = np.zeros((2,3,nmo)) kmf.mo_occ[0,:,:3] = 1 kmf.mo_occ[1,:,:1] = 1 kmf.mo_energy = np.arange(nmo) + np.random.random((2,3,nmo)) * .3 kmf.mo_energy[kmf.mo_occ == 0] += 2 mo = (np.random.random((2,3,nmo,nmo)) + np.random.random((2,3,nmo,nmo))*1j - .5-.5j) s = kmf.get_ovlp() kmf.mo_coeff = np.empty_like(mo) nkpts = len(kmf.kpts) for k in range(nkpts): kmf.mo_coeff[0,k] = lo.orth.vec_lowdin(mo[0,k], s[k]) kmf.mo_coeff[1,k] = lo.orth.vec_lowdin(mo[1,k], s[k]) def rand_t1_t2(mycc): nkpts = mycc.nkpts nocca, noccb = mycc.nocc nmoa, nmob = mycc.nmo nvira, nvirb = nmoa - nocca, nmob - noccb np.random.seed(1) t1a = (np.random.random((nkpts,nocca,nvira)) + np.random.random((nkpts,nocca,nvira))*1j - .5-.5j) t1b = (np.random.random((nkpts,noccb,nvirb)) + np.random.random((nkpts,noccb,nvirb))*1j - .5-.5j) t2aa = (np.random.random((nkpts,nkpts,nkpts,nocca,nocca,nvira,nvira)) + np.random.random((nkpts,nkpts,nkpts,nocca,nocca,nvira,nvira))*1j - .5-.5j) kconserv = kpts_helper.get_kconserv(kmf.cell, kmf.kpts) t2aa = t2aa - t2aa.transpose(1,0,2,4,3,5,6) tmp = t2aa.copy() for ki, kj, kk in kpts_helper.loop_kkk(nkpts): kl = kconserv[ki, kk, kj] t2aa[ki,kj,kk] = t2aa[ki,kj,kk] - tmp[ki,kj,kl].transpose(0,1,3,2) t2ab = (np.random.random((nkpts,nkpts,nkpts,nocca,noccb,nvira,nvirb)) + np.random.random((nkpts,nkpts,nkpts,nocca,noccb,nvira,nvirb))*1j - .5-.5j) t2bb = (np.random.random((nkpts,nkpts,nkpts,noccb,noccb,nvirb,nvirb)) + np.random.random((nkpts,nkpts,nkpts,noccb,noccb,nvirb,nvirb))*1j - .5-.5j) t2bb = t2bb - t2bb.transpose(1,0,2,4,3,5,6) tmp = t2bb.copy() for ki, kj, kk in kpts_helper.loop_kkk(nkpts): kl = kconserv[ki, kk, kj] t2bb[ki,kj,kk] = t2bb[ki,kj,kk] - tmp[ki,kj,kl].transpose(0,1,3,2) t1 = (t1a, t1b) t2 = (t2aa, t2ab, t2bb) return t1, t2 mycc = pbcc.KUCCSD(kmf) t1, t2 = rand_t1_t2(mycc) mycc.t1 = t1 mycc.t2 = t2 eris = mycc.ao2mo() eom = EOMEA(mycc) > imds = eom.make_imds(eris) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_kuccsd.py:167: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/eom_kccsd_uhf.py:1036: in make_imds imds.make_ea() pyscf/pbc/cc/eom_kccsd_uhf.py:1112: in make_ea self.Wvvvo, self.WvvVO, self.WVVvo, self.WVVVO = kintermediates_uhf.Wvvvo(self._cc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_uhf.py:795: in Wvvvo Wvvvv, WvvVV, WVVVV = get_Wvvvv(cc, t1, t2, eris, ka, kb, ke) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_uhf.py:367: in get_Wvvvv vvvv += einsum('mcnf,ma,nb->acbf', eris.ovov[ka,kc,kb], t1a[ka], t1a[kb]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'mcnf,ma,nb->acbf' tensors = [array([[[[ 0.00177037+0.01232812j], [-0.01205267-0.01709868j], [ 0.01408047+0.00707302j]]], ...0.1852195j ]]), array([[-0.082978 +0.03881673j], [ 0.22032449-0.08080549j], [-0.49988563+0.1852195j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ma,mcnf->acfn', ['nb', 'acfn']), ((1, 0), 'acfn,nb->acbf', ['acbf'])] contraction = ((1, 0), 'ma,mcnf->acfn', ['nb', 'acfn']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_n3_diffuse __________________________ self = def test_n3_diffuse(self): self.assertAlmostEqual(kmf.e_tot, -6.1870676561721227, 6) mycc = pbcc.KUCCSD(kmf) mycc.conv_tol = 1e-7 mycc.conv_tol_normt = 1e-7 > ecc2, t1, t2 = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_kuccsd.py:32: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00864392-0.00000001j, 0. -0.j , 0. +0.j , 0.00002369-0.j ], ... [[0., 1.], [1., 0.]]], [[[0., 1.], [1., 0.]], [[1., 0.], [0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->wxyzai', ['xyzw', 'wxyzai']), ((1, 0), 'wxyzai,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->wxyzai', ['xyzw', 'wxyzai']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_n3_diffuse_frozen ______________________ self = def test_n3_diffuse_frozen(self): ehf2 = kmf.e_tot self.assertAlmostEqual(ehf2, -6.1870676561725695, 6) mycc = pbcc.KUCCSD(kmf, frozen=([[0,],[0,1]],[[0],[0,1]])) mycc.conv_tol = 1e-7 mycc.conv_tol_normt = 1e-7 > ecc2, t1, t2 = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_eom_kuccsd.py:66: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.01758051+0.00006584j, -0.00833113+0.00044528j, 0.00000001+0.j , 0.00185231-0.00000694j], ... [[0., 1.], [1., 0.]]], [[[0., 1.], [1., 0.]], [[1., 0.], [0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->wxyzia', ['xyzw', 'wxyzia']), ((1, 0), 'wxyzia,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->wxyzia', ['xyzw', 'wxyzia']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_he_112_ea_diag ________________________ self = def test_he_112_ea_diag(self): kpts = cell.make_kpts([1,1,2]) kmf = pbcscf.KUHF(cell, kpts, exxdiv=None) Escf = kmf.scf() > self._test_ea_diag(kmf) pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:119: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:66: in _test_ea_diag Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00747362+0.j, -0. +0.j], [-0. +0.j, -0.00185859+0.j]], [[ 0. ... [[0., 1.], [1., 0.]]], [[[0., 1.], [1., 0.]], [[1., 0.], [0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']), ((1, 0), 'aiwxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_he_112_ea_diag_shift _____________________ self = def test_he_112_ea_diag_shift(self): kpts = cell.make_kpts([1,1,2]) kmf = pbcscf.KUHF(cell, kpts, exxdiv=None) Escf = kmf.scf() > self._test_ea_diag(kmf,kshift=1) pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:125: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:66: in _test_ea_diag Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00747362+0.j, -0. +0.j], [-0. +0.j, -0.00185859+0.j]], [[ 0. ... [[0., 1.], [1., 0.]]], [[[0., 1.], [1., 0.]], [[1., 0.], [0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']), ((1, 0), 'aiwxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_he_112_ip_diag ________________________ self = def test_he_112_ip_diag(self): kpts = cell.make_kpts([1,1,2]) kmf = pbcscf.KUHF(cell, kpts, exxdiv=None) Escf = kmf.scf() > self._test_ip_diag(kmf) pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:40: in _test_ip_diag Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00747362+0.j, -0. +0.j], [-0. +0.j, -0.00185859+0.j]], [[ 0. ... [[0., 1.], [1., 0.]]], [[[0., 1.], [1., 0.]], [[1., 0.], [0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']), ((1, 0), 'aiwxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_he_112_ip_diag_shift _____________________ self = def test_he_112_ip_diag_shift(self): kpts = cell.make_kpts([1,1,2]) kmf = pbcscf.KUHF(cell, kpts, exxdiv=None) Escf = kmf.scf() > self._test_ip_diag(kmf,kshift=1) pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:40: in _test_ip_diag Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00747362+0.j, -0. +0.j], [-0. +0.j, -0.00185859+0.j]], [[ 0. ... [[0., 1.], [1., 0.]]], [[[0., 1.], [1., 0.]], [[1., 0.], [0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']), ((1, 0), 'aiwxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_he_131_ea_diag ________________________ self = def test_he_131_ea_diag(self): kpts = cell.make_kpts([1,3,1]) kmf = pbcscf.KUHF(cell, kpts, exxdiv=None) Escf = kmf.scf() > self._test_ea_diag(kmf) pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:137: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:66: in _test_ea_diag Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00499116+0.j , -0. +0.j ], [-0. +0.j , -0.00125175+0.j... [0., 0., 1.], [0., 1., 0.]], [[0., 1., 0.], [1., 0., 0.], [0., 0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']), ((1, 0), 'aiwxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_he_131_ip_diag ________________________ self = def test_he_131_ip_diag(self): kpts = cell.make_kpts([1,3,1]) kmf = pbcscf.KUHF(cell, kpts, exxdiv=None) Escf = kmf.scf() > self._test_ip_diag(kmf) pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:113: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_eom_kuccsd_diag.py:40: in _test_ip_diag Ecc = cc.kernel()[0] ^^^^^^^^^^^ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[-0.00499116+0.j , -0. +0.j ], [-0. +0.j , -0.00125175+0.j... [0., 0., 1.], [0., 1., 0.]], [[0., 1., 0.], [1., 0., 0.], [0., 0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']), ((1, 0), 'aiwxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->aiwxyz', ['xyzw', 'aiwxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_111_n0 ____________________________ self = def test_111_n0(self): L = 10.0 n = 11 cell = make_test_cell.test_cell_n0(L,[n]*3) nk = (1, 1, 1) hf_111 = -0.73491491306419987 cc_111 = -1.1580008204825658e-05 > escf, ecc = run_kcell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:204: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_kgccsd.py:192: in run_kcell ecc, t1, t2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j]]), array([[0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j]]), array([[[[-0....-0.j, -0. -0.j]], [[-0. -0.j, -0. -0.j], [-0. -0.j, -0.05421805-0.j]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_111_n1 ____________________________ self = def test_111_n1(self): L = 7.0 n = 9 cell = make_test_cell.test_cell_n1(L,[n]*3) nk = (1, 1, 1) hf_111 = -0.73506011036963814 cc_111 = -0.023265431169472835 > escf, ecc = run_kcell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:215: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_kgccsd.py:192: in run_kcell ecc, t1, t2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... -0.j, -0. -0.j], [-0. -0.j, -0. -0.j], [-0. -0.j, -0.03608783-0.j]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->ijmb', ['ma', 'ijmb']), ((1, 0), 'ijmb,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->ijmb', ['ma', 'ijmb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_111_n3 ____________________________ self = def test_111_n3(self): n = 11 cell = make_test_cell.test_cell_n3([n]*3) nk = (1, 1, 1) hf_111 = -7.4117951240232118 cc_111 = -0.19468901057053406 > escf, ecc = run_kcell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:225: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_kgccsd.py:192: in run_kcell ecc, t1, t2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0....j, 0. -0.j, -0. -0.j, -0. -0.j, -0. -0.j, -0.00557415-0.j]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_211_n3 ____________________________ self = def test_211_n3(self): cell = make_test_cell.test_cell_n3_diffuse(precision=1e-9) nk = (2, 1, 1) abs_kpts = cell.make_kpts(nk, wrap_around=True) # GHF calculation kmf = pbcscf.KGHF(cell, abs_kpts, exxdiv=None) kmf.conv_tol = 1e-14 escf = kmf.scf() self.assertAlmostEqual(escf, -6.1870676561726574, 6) # GCCSD calculation cc = pbcc.kccsd.CCSD(kmf) cc.conv_tol = 1e-8 > ecc, t1, t2 = cc.kernel() ^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:255: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... , -0.00000001-0.j , -0.00057209-0.00000001j, 0.01294329-0.j ]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_h4_fcc_k2 __________________________ self = def test_h4_fcc_k2(self): '''Metallic hydrogen fcc lattice. Checks versus a corresponding supercell calculation. NOTE: different versions of the davidson may converge to a different solution for the k-point IP/EA eom. If you're getting the wrong root, check to see if it's contained in the supercell set of eigenvalues.''' cell = pbcgto.Cell() cell.atom = [['H', (0.000000000, 0.000000000, 0.000000000)], ['H', (0.000000000, 0.500000000, 0.250000000)], ['H', (0.500000000, 0.500000000, 0.500000000)], ['H', (0.500000000, 0.000000000, 0.750000000)]] cell.unit = 'Bohr' cell.a = [[1.,0.,0.],[0.,1.,0],[0,0,2.2]] cell.verbose = 7 cell.spin = 0 cell.charge = 0 cell.basis = [[0, [1.0, 1]],] cell.pseudo = 'gth-pade' cell.output = '/dev/null' cell.max_memory = 1000 for i in range(len(cell.atom)): cell.atom[i][1] = tuple(np.dot(np.array(cell.atom[i][1]),np.array(cell.a))) cell.build() nmp = [2, 1, 1] kmf = pbcscf.KRHF(cell) kmf.kpts = cell.make_kpts(nmp, scaled_center=[0.0,0.0,0.0]) e = kmf.kernel() #mymp = pbmp.KMP2(kmf) #ekmp2, _ = mymp.kernel() #print("KMP2 corr energy (per cell) = ", ekmp2) mycc = pbcc.KGCCSD(kmf) > ekccsd, t1, t2 = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:677: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], ... -0.j, 0. +0.j, -0. -0.j, 0. -0.j, -0. -0.j, 0.19437526-0.j]]]], shape=(6, 6, 6, 6))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_h4_fcc_k2_frozen _______________________ self = def test_h4_fcc_k2_frozen(self): '''Metallic hydrogen fcc lattice with frozen lowest lying occupied and highest lying virtual orbitals. Checks versus a corresponding supercell calculation. NOTE: different versions of the davidson may converge to a different solution for the k-point IP/EA eom. If you're getting the wrong root, check to see if it's contained in the supercell set of eigenvalues.''' cell = pbcgto.Cell() cell.atom = [['H', (0.000000000, 0.000000000, 0.000000000)], ['H', (0.000000000, 0.500000000, 0.250000000)], ['H', (0.500000000, 0.500000000, 0.500000000)], ['H', (0.500000000, 0.000000000, 0.750000000)]] cell.unit = 'Bohr' cell.a = [[1.,0.,0.],[0.,1.,0],[0,0,2.2]] cell.verbose = 7 cell.spin = 0 cell.charge = 0 cell.basis = [[0, [1.0, 1]],] cell.pseudo = 'gth-pade' cell.output = '/dev/null' cell.max_memory = 1000 for i in range(len(cell.atom)): cell.atom[i][1] = tuple(np.dot(np.array(cell.atom[i][1]),np.array(cell.a))) cell.build() nmp = [2, 1, 1] kmf = pbcscf.KRHF(cell) kmf.kpts = cell.make_kpts(nmp, scaled_center=[0.0,0.0,0.0]) e = kmf.kernel() #mymp = pbmp.KMP2(kmf) #ekmp2, _ = mymp.kernel() #print("KMP2 corr energy (per cell) = ", ekmp2) # By not applying a level-shift, one gets a different initial CCSD answer. # One can check however that the t1/t2 from level-shifting are a solution # of the CCSD equations done without level-shifting. frozen = [[0, 1, 6, 7], []] mycc = pbcc.KGCCSD(kmf, frozen=frozen) > ekccsd, t1, t2 = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:765: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], ...j, -0.-0.j, -0.-0.j], [-0.-0.j, -0.-0.j, -0.-0.j, -0.-0.j], [-0.-0.j, -0.-0.j, -0.-0.j, -0.-0.j]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->ijmb', ['ma', 'ijmb']), ((1, 0), 'ijmb,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->ijmb', ['ma', 'ijmb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rand_ccsd __________________________ self = def test_rand_ccsd(self): '''Single (eom-)ccsd iteration with random t1/t2.''' kmf = pbcscf.addons.convert_to_ghf(rand_kmf) # Round to make this insensitive to small changes between PySCF versions mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore rand_cc = pbcc.KGCCSD(kmf) eris = rand_cc.ao2mo(rand_cc.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal() for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:409: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[-0.082978 -0.21222466j, 0.22032449-0.36997143j, -0.49988563-0.48063304j, -0.19766743+0.17883553j], [... ], [-0. -0.j , 0.00207246-0.00162131j, -0. -0.j , 0.00320465+0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen0 ______________________ self = def test_rand_ccsd_frozen0(self): '''Single (eom-)ccsd iteration with random t1/t2 and lowest lying orbital at multiple k-points frozen.''' kmf = pbcscf.addons.convert_to_ghf(rand_kmf) # Round to make this insensitive to small changes between PySCF versions mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore # frozen = 1 rand_cc = pbcc.KGCCSD(kmf, frozen=1) eris = rand_cc.ao2mo(rand_cc.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal() for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:449: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[-0.082978 +0.18650093j, 0.22032449+0.33462567j, -0.49988563-0.48171172j, -0.19766743+0.25014431j], [... , -0. -0.j ], [ 0.00207246-0.00162131j, -0. -0.j , 0.00320465+0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->ijmb', ['ma', 'ijmb']), ((1, 0), 'ijmb,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->ijmb', ['ma', 'ijmb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen1 ______________________ self = def test_rand_ccsd_frozen1(self): '''Single (eom-)ccsd iteration with random t1/t2 and single frozen occupied orbital.''' kmf = pbcscf.addons.convert_to_ghf(rand_kmf) # Round to make this insensitive to small changes between PySCF versions mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore frozen = [[0,],[],[]] rand_cc = pbcc.KGCCSD(kmf, frozen=frozen) eris = rand_cc.ao2mo(rand_cc.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal() for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) # Manually zero'ing out the frozen elements of the t1/t2 # N.B. the 0'th element frozen means we are freezing the 1'th # element in the current padding scheme t1[0, 1] = 0.0 t2[0, :, :, 1, :] = 0.0 t2[:, 0, :, :, 1] = 0.0 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:506: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[-0.082978 -0.21222466j, 0.22032449-0.36997143j, -0.49988563-0.48063304j, -0.19766743+0.17883553j], [... ], [-0. -0.j , -0. -0.j , -0. -0.j , -0. -0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen2 ______________________ self = def test_rand_ccsd_frozen2(self): '''Single (eom-)ccsd iteration with random t1/t2 and full occupied frozen at a single k-point.''' kmf = pbcscf.addons.convert_to_ghf(rand_kmf) # Round to make this insensitive to small changes between PySCF versions mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore frozen = [[],[0,1,2,3],[]] rand_cc = pbcc.KGCCSD(kmf, frozen=frozen) eris = rand_cc.ao2mo(rand_cc.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal() for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) # Manually zero'ing out the frozen elements of the t1/t2 # N.B. the 0'th element frozen means we are freezing the 1'th # element in the current padding scheme t1[1, [0,1,2,3]] = 0.0 t2[1, :, :, [0,1,2,3], :] = 0.0 t2[:, 1, :, :, [0,1,2,3]] = 0.0 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:552: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[-0.082978 -0.21222466j, 0.22032449-0.36997143j, -0.49988563-0.48063304j, -0.19766743+0.17883553j], [... ], [-0. -0.j , 0.00207246-0.00162131j, -0. -0.j , 0.00320465+0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen3 ______________________ self = def test_rand_ccsd_frozen3(self): '''Single (eom-)ccsd iteration with random t1/t2 and single frozen virtual orbital.''' kconserv = kpts_helper.get_kconserv(rand_kmf.cell, rand_kmf.kpts) kmf = pbcscf.addons.convert_to_ghf(rand_kmf) # Round to make this insensitive to small changes between PySCF versions mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore frozen = [[],[],[5]] # freezing one virtual rand_cc = pbcc.KGCCSD(kmf, frozen=frozen) eris = rand_cc.ao2mo(rand_cc.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal() for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) # Manually zero'ing out the frozen elements of the t1/t2 t1[2, :, 0] = 0.0 for ki in range(rand_cc.nkpts): for kj in range(rand_cc.nkpts): for ka in range(rand_cc.nkpts): kb = kconserv[ki, ka, kj] if ka == 2: t2[ki, kj, ka, :, :, 0] = 0.0 if kb == 2: t2[ki, kj, ka, :, :, :, 0] = 0.0 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kgccsd.py:604: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[-0.082978 -0.21222466j, 0.22032449-0.36997143j, -0.49988563-0.48063304j, -0.19766743+0.17883553j], [... ], [-0. -0.j , 0.00207246-0.00162131j, -0. -0.j , 0.00320465+0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_ccsd_t_non_hf_frozen _____________________ self = def test_ccsd_t_non_hf_frozen(self): '''Tests ccsd and ccsd_t for non-Hartree-Fock references with frozen orbitals using supercell vs k-point calculation.''' n = 15 cell = make_test_cell.test_cell_n3([n]*3) #import sys #cell.stdout = sys.stdout #cell.verbose = 7 nk = [2, 1, 1] kpts = cell.make_kpts(nk) kpts -= kpts[0] kks = pbcdft.KRKS(cell, kpts=kpts) ekks = kks.kernel() khf = pbcscf.KRHF(cell) khf.__dict__.update(kks.__dict__) mycc = pbcc.KRCCSD(khf, frozen=1) eris = mycc.ao2mo() > ekcc, t1, t2 = mycc.kernel(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:504: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.0650787 -0.j, -0.000639 -0.j, 0. -0.j, -0.00556981+0.j], [-0.000639 +0.j, 0.01434536...([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_frozen_n3 __________________________ self = def test_frozen_n3(self): mesh = 12 cell = make_test_cell.test_cell_n3([mesh]*3) nk = (1, 1, 2) ehf_bench = -8.648503065380389 ecc_bench = -0.100045112503651 abs_kpts = cell.make_kpts(nk, with_gamma_point=True) # RHF calculation kmf = pbcscf.KRHF(cell, abs_kpts, exxdiv=None) kmf.conv_tol = 1e-9 ehf = kmf.scf() # KRCCSD calculation, equivalent to running supercell # calculation with frozen=[0,1,2] (if done with larger mesh) cc = pbcc.kccsd_rhf.RCCSD(kmf, frozen=[[0],[0,1]]) cc.diis_start_cycle = 1 > ecc, t1, t2 = cc.kernel() ^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:223: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.01463554-0.01340389j, 0.01112936-0.01049205j, -0.00000068-0.00000012j, 0.00388173-0.00356656j], ...([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_h4_fcc_k2 __________________________ self = def test_h4_fcc_k2(self): '''Metallic hydrogen fcc lattice. Checks versus a corresponding supercell calculation. NOTE: different versions of the davidson may converge to a different solution for the k-point IP/EA eom. If you're getting the wrong root, check to see if it's contained in the supercell set of eigenvalues.''' cell = pbcgto.Cell() cell.atom = [['H', (0.000000000, 0.000000000, 0.000000000)], ['H', (0.000000000, 0.500000000, 0.250000000)], ['H', (0.500000000, 0.500000000, 0.500000000)], ['H', (0.500000000, 0.000000000, 0.750000000)]] cell.unit = 'Bohr' cell.a = [[1.,0.,0.],[0.,1.,0],[0,0,2.2]] cell.verbose = 7 cell.spin = 0 cell.charge = 0 cell.basis = [[0, [1.0, 1]],] cell.pseudo = 'gth-pade' cell.output = '/dev/null' #cell.max_memory = 1000 for i in range(len(cell.atom)): cell.atom[i][1] = tuple(np.dot(np.array(cell.atom[i][1]),np.array(cell.a))) cell.build() nmp = [2, 1, 1] kmf = pbcscf.KRHF(cell) kmf.kpts = cell.make_kpts(nmp, scaled_center=[0.0,0.0,0.0]) e = kmf.kernel() mycc = pbcc.KCCSD(kmf) > ekccsd, _, _ = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:1001: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0. +0.j, 0. +0.j, 0. +0.j], [ 0. +0.j, 0. +0.j, 0. ...0.+0.j, 0.+0.j]]), array([[0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_h4_fcc_k2_frozen _______________________ self = def test_h4_fcc_k2_frozen(self): '''Metallic hydrogen fcc lattice with frozen lowest lying occupied and highest lying virtual orbitals. Checks versus a corresponding supercell calculation. NOTE: different versions of the davidson may converge to a different solution for the k-point IP/EA eom. If you're getting the wrong root, check to see if it's contained in the supercell set of eigenvalues.''' cell = pbcgto.Cell() cell.atom = [['H', (0.000000000, 0.000000000, 0.000000000)], ['H', (0.000000000, 0.500000000, 0.250000000)], ['H', (0.500000000, 0.500000000, 0.500000000)], ['H', (0.500000000, 0.000000000, 0.750000000)]] cell.unit = 'Bohr' cell.a = [[1.,0.,0.],[0.,1.,0],[0,0,2.2]] cell.verbose = 7 cell.spin = 0 cell.charge = 0 cell.basis = [[0, [1.0, 1]],] cell.pseudo = 'gth-pade' cell.output = '/dev/null' #cell.max_memory = 1000 for i in range(len(cell.atom)): cell.atom[i][1] = tuple(np.dot(np.array(cell.atom[i][1]),np.array(cell.a))) cell.build() nmp = [2, 1, 1] kmf = pbcscf.KRHF(cell) kmf.kpts = cell.make_kpts(nmp, scaled_center=[0.0,0.0,0.0]) e = kmf.kernel() frozen = [[0, 3], []] mycc = pbcc.KCCSD(kmf, frozen=frozen) > ekccsd, _, _ = mycc.kernel() ^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:1074: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j]], [[...0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j]]), array([[0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rand_ccsd __________________________ self = def test_rand_ccsd(self): '''Single (eom-)ccsd iteration with random t1/t2.''' kmf = rand_kmf.copy() mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore rand_cc = pbcc.KRCCSD(kmf) eris = rand_cc.ao2mo(kmf.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal().real for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) rand_cc.t1, rand_cc.t2, rand_cc.eris = t1, t2, eris t1, t2 = rand_cc.t1, rand_cc.t2 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:764: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.00281668+0.0001208j , 0.00349808+0.0050177j ], [ 0.00349808+0.0050177j , -0.00124074+0.010289j...array([[-0.082978 -0.29554775j, 0.22032449+0.37811744j], [-0.49988563-0.47261241j, -0.19766743+0.17046751j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen0 ______________________ self = def test_rand_ccsd_frozen0(self): '''Single (eom-)ccsd iteration with random t1/t2 and lowest lying orbital at multiple k-points frozen.''' kmf = rand_kmf.copy() mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore rand_cc = pbcc.KRCCSD(kmf, frozen=1) eris = rand_cc.ao2mo(kmf.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal().real for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:794: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[-0.00218323-0.00205632j, 0.00020738-0.00684358j], [ 0.00020738-0.00684358j, 0.01267165-0.0087230...ray([[-0.082978 -0.31373979j, 0.22032449-0.15443927j]]), array([[-0.082978 -0.31373979j, 0.22032449-0.15443927j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ic,klcd->ikld', ['ld', 'ikld']), ((1, 0), 'ikld,ld->ki', ['ki'])] contraction = ((1, 0), 'ic,klcd->ikld', ['ld', 'ikld']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen1 ______________________ self = def test_rand_ccsd_frozen1(self): '''Single (eom-)ccsd iteration with random t1/t2 and single frozen occupied orbital.''' kmf = rand_kmf.copy() mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore frozen = [[0,],[],[]] rand_cc = pbcc.KRCCSD(kmf, frozen=frozen) eris = rand_cc.ao2mo(kmf.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal().real for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) # Manually zero'ing out the frozen elements of the t1/t2 # N.B. the 0'th element frozen means we are freezing the 1'th # element in the current padding scheme t1[0, 1] = 0.0 t2[0, :, :, 1, :] = 0.0 t2[:, 0, :, :, 1] = 0.0 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[-0.00218323-0.00205632j, 0.00020738-0.00684358j], [ 0.00020738-0.00684358j, 0.01267165-0.0087230...array([[-0.082978 -0.29554775j, 0.22032449+0.37811744j], [ 0. +0.j , 0. +0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen2 ______________________ self = def test_rand_ccsd_frozen2(self): '''Single (eom-)ccsd iteration with random t1/t2 and full occupied frozen at a single k-point.''' kmf = rand_kmf.copy() mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore frozen = [[],[0,1],[]] rand_cc = pbcc.KRCCSD(kmf, frozen=frozen) eris = rand_cc.ao2mo(kmf.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal().real for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) # Manually zero'ing out the frozen elements of the t1/t2 # N.B. the 0'th element frozen means we are freezing the 1'th # element in the current padding scheme t1[1, [0,1]] = 0.0 t2[1, :, :, [0,1], :] = 0.0 t2[:, 1, :, :, [0,1]] = 0.0 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:885: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.00281668+0.0001208j , 0.00349808+0.0050177j ], [ 0.00349808+0.0050177j , -0.00124074+0.010289j...array([[-0.082978 -0.29554775j, 0.22032449+0.37811744j], [-0.49988563-0.47261241j, -0.19766743+0.17046751j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_rand_ccsd_frozen3 ______________________ self = def test_rand_ccsd_frozen3(self): '''Single (eom-)ccsd iteration with random t1/t2 and single frozen virtual orbital.''' kmf = rand_kmf.copy() mat_veff = kmf.get_veff().round(4) mat_hcore = kmf.get_hcore().round(4) kmf.get_veff = lambda *x: mat_veff kmf.get_hcore = lambda *x: mat_hcore kconserv = kpts_helper.get_kconserv(kmf.cell, kmf.kpts) frozen = [[],[],[3]] # freezing one virtual rand_cc = pbcc.KRCCSD(kmf, frozen=frozen) eris = rand_cc.ao2mo(kmf.mo_coeff) eris.mo_energy = [eris.fock[k].diagonal().real for k in range(rand_cc.nkpts)] t1, t2 = rand_t1_t2(kmf, rand_cc) # Manually zero'ing out the frozen elements of the t1/t2 t1[2, :, 0] = 0.0 for ki in range(rand_cc.nkpts): for kj in range(rand_cc.nkpts): for ka in range(rand_cc.nkpts): kb = kconserv[ki, ka, kj] if ka == 2: t2[ki, kj, ka, :, :, 0] = 0.0 if kb == 2: t2[ki, kj, ka, :, :, :, 0] = 0.0 > Ht1, Ht2 = rand_cc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:934: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.00281668+0.0001208j , 0.00349808+0.0050177j ], [ 0.00349808+0.0050177j , -0.00124074+0.010289j...array([[-0.082978 -0.29554775j, 0.22032449+0.37811744j], [-0.49988563-0.47261241j, -0.19766743+0.17046751j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_rccsd_t_hf_against_so ____________________ self = def test_rccsd_t_hf_against_so(self): '''Tests restricted ccsd and ccsd_t for Hartree-Fock references against the general spin-orbital implementation.''' n = 15 cell = make_test_cell.test_cell_n3([n]*3) #import sys #cell.stdout = sys.stdout #cell.verbose = 7 nk = [2, 1, 1] kpts = cell.make_kpts(nk) kpts -= kpts[0] kks = pbcscf.KRHF(cell, kpts=kpts) ekks = kks.kernel() self.assertAlmostEqual(ekks, -10.530978858287662, 5) khf = pbcscf.KRHF(cell) khf.__dict__.update(kks.__dict__) mycc = pbcc.KGCCSD(khf, frozen=None) eris = mycc.ao2mo() > ekgcc, t1, t2 = mycc.kernel(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:623: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/gccsd.py:139: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:394: in ccsd e_corr, self.t1, self.t2 = ccsd.CCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd.py:173: in update_amps tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ie,ma,mbej->ijab' tensors = [array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0... , 0. -0.j , -0. -0.j , -0.00029349+0.j ]]]], shape=(8, 8, 8, 8))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']), ((1, 0), 'bijm,ma->ijab', ['ijab'])] contraction = ((2, 0), 'mbej,ie->bijm', ['ma', 'bijm']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_single_kpt __________________________ self = def test_single_kpt(self): cell = pbcgto.Cell() cell.atom = ''' H 0 0 0 H 1 0 0 H 0 1 0 H 0 1 1 ''' cell.a = np.eye(3)*2 cell.basis = [[0, [1.2, 1]], [1, [1.0, 1]]] cell.verbose = 0 cell.build() kpts = cell.get_abs_kpts([.5,.5,.5]).reshape(1,3) mf = pbcscf.KRHF(cell, kpts=kpts).run(conv_tol=1e-9) kcc = pbcc.kccsd_rhf.RCCSD(mf) kcc.level_shift = .05 > e0 = kcc.kernel()[0] ^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd.py:198: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_rhf.py:601: in kernel return self.ccsd(t1, t2, eris, mbpt2=mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:623: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_rhf.py:71: in update_amps Foo = imdk.cc_Foo(t1, t2, eris, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kintermediates_rhf.py:51: in cc_Foo Fki[ki] += einsum('klcd,ic,ld->ki',Soovv,t1[ki],t1[kl]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'klcd,ic,ld->ki' tensors = [array([[[[ 0.04816196-0.j , -0.00000036+0.j , 0.0000001 -0.j , -0.01025719+0.j , -0.0000... [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,klcd->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,klcd->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_111_n0 ____________________________ self = def test_111_n0(self): L = 10.0 n = 11 cell = make_test_cell.test_cell_n0(L,[n]*3) nk = (1, 1, 1) hf_111 = -0.73491491306419987 cc_111 = -1.1580008204825658e-05 > escf,ecc=run_cell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd_gamma.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_krccsd_gamma.py:49: in run_cell ecc, t1, it2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/ccsd.py:33: in ccsd return rccsd.RCCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[0.0131256]]]]), array([[-0.]]), array([[-0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ic,kcld->dikl', ['ld', 'dikl']), ((1, 0), 'dikl,ld->ki', ['ki'])] contraction = ((1, 0), 'ic,kcld->dikl', ['ld', 'dikl']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_111_n1 ____________________________ self = def test_111_n1(self): L = 7.0 n = 9 cell = make_test_cell.test_cell_n1(L,[n]*3) nk = (1, 1, 1) hf_111 = -0.73506011036963814 cc_111 = -0.023265431169472835 > escf,ecc=run_cell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd_gamma.py:72: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_krccsd_gamma.py:49: in run_cell ecc, t1, it2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/ccsd.py:33: in ccsd return rccsd.RCCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.07153345, 0. , -0. , 0. ]], [[ 0. , 0.07153345, -0. , 0....[ 0. , 0. , -0. , 0.01638805]]]]), array([[ 0., 0., -0., 0.]]), array([[ 0., 0., -0., 0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ic,kcld->ikld', ['ld', 'ikld']), ((1, 0), 'ikld,ld->ki', ['ki'])] contraction = ((1, 0), 'ic,kcld->ikld', ['ld', 'ikld']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_111_n3 ____________________________ self = def test_111_n3(self): L = 10.0 n = 11 cell = make_test_cell.test_cell_n3([n]*3) nk = (1, 1, 1) hf_111 = -7.4117951240232118 cc_111 = -0.19468901057053406 > escf,ecc=run_cell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd_gamma.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_krccsd_gamma.py:49: in run_cell ecc, t1, it2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/ccsd.py:33: in ccsd return rccsd.RCCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.05794962, -0. , -0. , -0.0000398 ], [ 0.01979099, 0. , 0. , 0.05... [ 0. , 0. , -0.00000001, 0. ], [ 0. , 0.00000001, 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->ck', ['ic', 'ck']), ((1, 0), 'ck,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->ck', ['ic', 'ck']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_311_n1 ____________________________ self = def test_311_n1(self): L = 7.0 n = 9 cell = make_test_cell.test_cell_n1(L,[n]*3) nk = (3, 1, 1) hf_311 = -0.92687629918229486 cc_311 = -0.042702177586414237 > escf,ecc=run_cell(cell,n,nk) ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_krccsd_gamma.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_krccsd_gamma.py:49: in run_cell ecc, t1, it2 = cc.kernel() ^^^^^^^^^^^ pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/ccsd.py:33: in ccsd return rccsd.RCCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.03913443, 0. , -0. , 0. , 0. , -0. , -0. , -0. , -0....., 0., 0., -0., 0., -0., -0., -0., -0., -0.], [ 0., 0., -0., 0., -0., 0., -0., 0., -0., 0., -0., 0.]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_kuccsd_rdm_slow _______________________ self = def test_kuccsd_rdm_slow(self): a0 = 3.0 nmp = [3,1,1] vec = [[ 3.0/2.0*a0,np.sqrt(3.0)/2.0*a0, 0], [-3.0/2.0*a0,np.sqrt(3.0)/2.0*a0, 0], [ 0, 0,a0]] bas = [[0, [2., 1.]], [0, [.4, 1.]]] pos = [['H',(-a0/2.0,0,0)], ['H',( a0/2.0,0,0)]] cell = gto.M(unit='B',a=vec,atom=pos,basis=bas,verbose=4,output='/dev/null') kpts = cell.make_kpts(nmp) kmf = scf.KUHF(cell,kpts,exxdiv=None).density_fit() dm = kmf.get_init_guess() aoind = cell.aoslice_by_atom() idx0, idx1 = aoind dm[0,:,idx0[2]:idx0[3], idx0[2]:idx0[3]] = 0 dm[0,:,idx1[2]:idx1[3], idx1[2]:idx1[3]] = dm[0,:,idx1[2]:idx1[3], idx1[2]:idx1[3]] * 2 dm[1,:,idx0[2]:idx0[3], idx0[2]:idx0[3]] = dm[1,:,idx0[2]:idx0[3], idx0[2]:idx0[3]] * 2 dm[1,:,idx1[2]:idx1[3], idx1[2]:idx1[3]] = 0 ehf = kmf.kernel(dm) kcc = kmf.CCSD() > ecc, t1, t2 = kcc.kernel() ^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kuccsd.py:391: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[ 0.02167534+0.j , -0.0009079 -0.j , 0.00123809-0.j ], [-0.0009079 +0.j... [0., 0., 1.], [0., 1., 0.]], [[0., 1., 0.], [1., 0., 0.], [0., 0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->iawxyz', ['xyzw', 'iawxyz']), ((1, 0), 'iawxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->iawxyz', ['xyzw', 'iawxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_update_amps _________________________ self = def test_update_amps(self): np.random.seed(2) # Running HF and CCSD with 1x1x2 Monkhorst-Pack k-point mesh kmf = scf.KUHF(cell, kpts=cell.make_kpts([1,1,3]), exxdiv=None) nmo = cell.nao_nr() kmf.mo_occ = np.zeros((2,3,nmo)) kmf.mo_occ[0,:,:3] = 1 kmf.mo_occ[1,:,:1] = 1 kmf.mo_energy = np.arange(nmo) + np.random.random((2,3,nmo)) * .3 kmf.mo_energy[kmf.mo_occ == 0] += 2 mo = (np.random.random((2,3,nmo,nmo)) + np.random.random((2,3,nmo,nmo))*1j - .5-.5j) s = kmf.get_ovlp() kmf.mo_coeff = np.empty_like(mo) nkpts = len(kmf.kpts) for k in range(nkpts): kmf.mo_coeff[0,k] = lo.orth.vec_lowdin(mo[0,k], s[k]) kmf.mo_coeff[1,k] = lo.orth.vec_lowdin(mo[1,k], s[k]) mycc = kccsd_uhf.KUCCSD(kmf) eris = mycc.ao2mo() np.random.seed(1) nocc = mycc.nocc nvir = nmo - nocc[0], nmo - nocc[1] t1, t2 = rand_t1_t2(cell, kmf.kpts, nocc, nvir) > Ht1, Ht2 = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kuccsd.py:151: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/kccsd_uhf.py:119: in update_amps Ht1b -= einsum('yxwnmea,xzymine,xyzw->zia', t2ab, eris.OOov, P) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'yxwnmea,xzymine,xyzw->zia' tensors = [array([[[[[[[ 0.47598907-0.48590771j, 0.40156258+0.2159457j , 0.09560793+0.06449832j]]], [[[-0.46757367... [0., 0., 1.], [0., 1., 0.]], [[0., 1., 0.], [1., 0., 0.], [0., 0., 1.]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xzymine,yxwnmea->iawxyz', ['xyzw', 'iawxyz']), ((1, 0), 'iawxyz,xyzw->zia', ['zia'])] contraction = ((1, 0), 'xzymine,yxwnmea->iawxyz', ['xyzw', 'iawxyz']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ test_kuccsd_openshell _____________________________ def test_kuccsd_openshell(): cell = gto.M( unit = 'B', a = [[ 0., 6.74027466, 6.74027466], [ 6.74027466, 0., 6.74027466], [ 6.74027466, 6.74027466, 0. ]], mesh = [13]*3, atom = '''H 0 0 0 H 1.68506866 1.68506866 1.68506866 H 3.37013733 3.37013733 3.37013733''', basis = [[0, (1., 1.)], [0, (.5, 1.)]], verbose = 1, charge = 0, spin = 1, ) nmp = [3,1,1] # cell spin multiplied by nkpts cell.spin = cell.spin*3 # treating 3*1*1 supercell at gamma point supcell = super_cell(cell,nmp) umf = scf.UHF(supcell,exxdiv=None) umf.conv_tol = 1e-11 ehf = umf.kernel() ucc = cc.UCCSD(umf) ucc.conv_tol = 1e-12 > ecc, t1, t2 = ucc.kernel() ^^^^^^^^^^^^ pyscf/pbc/cc/test/test_kuccsd_openshell.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/cc/uccsd.py:597: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/ccsd.py:72: in ccsd return uccsd.UCCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:613: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:56: in kernel eccsd = mycc.energy(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/uccsd.py:363: in energy e += 0.5*lib.einsum('ia,jb,iajb',t1a, t1a, eris_ovov) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ia,jb,iajb' tensors = [array([[-0., -0., 0., -0., 0., -0., 0., -0., 0., -0., -0., 0.], [ 0., -0., -0., -0., 0., -0., -0., -0., ... , 0. , -0.00486322, 0.0033916 , -0. , 0. , 0.0034918 ]]]], shape=(6, 12, 6, 12))] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'iajb,ia->jb', ['jb', 'jb']), ((1, 0), 'jb,jb->', [''])] contraction = ((2, 0), 'iajb,ia->jb', ['jb', 'jb']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_water ____________________________ self = def test_water(self): atom = ''' O 0.00000 0.00000 0.11779 H 0.00000 0.75545 -0.47116 H 0.00000 -0.75545 -0.47116 ''' basis = 'gth-dzvp' pseudo = 'gth-hf-rev' a = np.eye(3) * 30 cell = gto.M(atom=atom, basis=basis, a=a, pseudo=pseudo) > eccsd_gamma, et_gamma = run_cell(cell, [0,0,0]) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/test/test_rccsd_t_shift.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/cc/test/test_rccsd_t_shift.py:34: in run_cell mcc.kernel(eris=eris) pyscf/cc/rccsd.py:171: in kernel return self.ccsd(t1, t2, eris, mbpt2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/cc/ccsd.py:33: in ccsd return rccsd.RCCSD.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:188: in ccsd return ccsd.CCSDBase.ccsd(self, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1098: in ccsd kernel(self, eris, t1, t2, max_cycle=self.max_cycle, pyscf/cc/ccsd.py:70: in kernel t1new, t2new = mycc.update_amps(t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rccsd.py:54: in update_amps Foo = imd.cc_Foo(t1,t2,eris) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/rintermediates.py:35: in cc_Foo Fki += 2*lib.einsum('kcld,ic,ld->ki', eris_ovov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kcld,ic,ld->ki' tensors = [array([[[[ 0.04054949, -0. , 0. , 0.0194989 , -0. , 0.02928249, 0. , -0.0237685 , 0....-0. , -0. , 0. , 0. , 0.00000002, 0. , 0. , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'ld,kcld->kc', ['ic', 'kc']), ((1, 0), 'kc,ic->ki', ['ki'])] contraction = ((2, 0), 'ld,kcld->kc', ['ic', 'kc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_convert_from _________________________ self = def test_convert_from(self): kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kumf = pscf.KUKS(cell, kpts=kpts) kumf.xc = 'lda' > kumf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:304: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_get_bands __________________________ self = def test_get_bands(self): kpts = cell.make_kpts(nk, space_group_symmetry=True, time_reversal_symmetry=True) kumf = pscf.KUKS(cell, kpts=kpts) kumf.xc = 'lda' kumf.chkfile = 'test_get_bands_ksymm.chk' > kumf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:326: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_gga_df ____________________________ self = def test_gga_df(self): kpts0 = He.make_kpts(nk, with_gamma_point=False) kmf0 = krks.KRKS(He, kpts=kpts0).density_fit() kmf0.xc = 'pbe' kmf0.kernel() kpts = He.make_kpts(nk, with_gamma_point=False, space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(He, kpts=kpts).density_fit() kmf.xc = 'pbe' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:179: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([1.]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821728]]]), array([[[1. +0.j, 0.71555734-0.j], [0.71555734-0.j, 1.00158213-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_gga_df_newton ________________________ self = def test_gga_df_newton(self): kpts0 = He.make_kpts(nk, with_gamma_point=False) kmf0 = krks.KRKS(He, kpts=kpts0).density_fit() kmf0.xc = 'pbe' kmf0 = kmf0.newton() kmf0.kernel() kpts = He.make_kpts(nk, with_gamma_point=False, space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(He, kpts=kpts).density_fit() kmf.xc = 'pbe' kmf = kmf.newton() > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:193: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/soscf/newton_ah.py:749: in kernel kernel(self, mo_coeff, mo_occ, dm0, conv_tol=self.conv_tol, pyscf/soscf/newton_ah.py:500: in kernel dm = mf.get_init_guess(mf._scf.mol, mf.init_guess) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([1.]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821728]]]), array([[[1. +0.j, 0.71555734-0.j], [0.71555734-0.j, 1.00158213-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_krks_gamma_center ______________________ self = def test_krks_gamma_center(self): kpts0 = cell.make_kpts(nk, with_gamma_point=True) kmf0 = krks.KRKS(cell, kpts=kpts0) kmf0.xc = 'lda' kmf0.kernel() rho0 = kmf0.get_rho() kpts = cell.make_kpts(nk, with_gamma_point=True,space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(cell, kpts=kpts) kmf.xc = 'lda' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. ... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_krks_monkhorst ________________________ self = def test_krks_monkhorst(self): kpts0 = cell.make_kpts(nk, with_gamma_point=False) kmf0 = krks.KRKS(cell, kpts=kpts0) kmf0.xc = 'lda' kmf0.kernel() kpts = cell.make_kpts(nk, with_gamma_point=False,space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(cell, kpts=kpts) kmf.xc = 'lda' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:99: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.5, 0.5]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. , 0...2747j, -0. -0.j , 0. -0.j , -0. -0.j , 0.59011677-0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_krks_multigrid_newton ____________________ self = def test_krks_multigrid_newton(self): kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) > kmf = pscf.KRKS(cell, kpts=kpts).multigrid_numint().newton().run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_krks_ksym.py:348: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/soscf/newton_ah.py:749: in kernel kernel(self, mo_coeff, mo_occ, dm0, conv_tol=self.conv_tol, pyscf/soscf/newton_ah.py:500: in kernel dm = mf.get_init_guess(mf._scf.mol, mf.init_guess) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. ... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_krks_symorb _________________________ self = def test_krks_symorb(self): cell1 = cell.copy() cell1.build(symmorphic=True) kpts = cell1.make_kpts([2,2,2], with_gamma_point=True,space_group_symmetry=True) > kmf = pscf.KRKS(cell1, kpts=kpts).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_krks_ksym.py:134: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.125, 0.375, 0.5 ]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. ...5517248 +0.j, -0.5517248 +0.j, -0.28660136+0.j, 0. +0.j, 0.53428118-0.j, 0.53428118-0.j, 1.07004424-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_kuks_gamma_center ______________________ self = def test_kuks_gamma_center(self): kpts0 = cell.make_kpts(nk, with_gamma_point=True) kumf0 = kuks.KUKS(cell, kpts=kpts0) kumf0.xc = 'lda' kumf0.kernel() rho0 = kumf0.get_rho() kpts = cell.make_kpts(nk, with_gamma_point=True,space_group_symmetry=True,time_reversal_symmetry=True) kumf = pscf.KUKS(cell, kpts=kpts) kumf.xc = 'lda' > kumf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:112: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_kuks_monkhorst ________________________ self = def test_kuks_monkhorst(self): kpts0 = cell.make_kpts(nk, with_gamma_point=False) kumf0 = kuks.KUKS(cell, kpts=kpts0) kumf0.xc = 'lda' kumf0.kernel() kpts = cell.make_kpts(nk, with_gamma_point=False,space_group_symmetry=True,time_reversal_symmetry=True) kumf = pscf.KUKS(cell, kpts=kpts) kumf.xc = 'lda' > kumf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:127: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.5, 0.5]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0. ...2747j, -0. -0.j , 0. -0.j , -0. -0.j , 0.59011677-0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->kx', ['k', 'kx']), ((1, 0), 'kx,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->kx', ['k', 'kx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_kuks_multigrid_newton ____________________ self = def test_kuks_multigrid_newton(self): kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) > kmf = pscf.KUKS(cell, kpts=kpts).multigrid_numint().newton().run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_krks_ksym.py:354: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/soscf/newton_ah.py:749: in kernel kernel(self, mo_coeff, mo_occ, dm0, conv_tol=self.conv_tol, pyscf/soscf/newton_ah.py:500: in kernel dm = mf.get_init_guess(mf._scf.mol, mf.init_guess) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_lda_df ____________________________ self = def test_lda_df(self): kpts0 = He.make_kpts(nk, with_gamma_point=False) kmf0 = krks.KRKS(He, kpts=kpts0).density_fit() kmf0.xc = 'lda' kmf0.kernel() kpts = He.make_kpts(nk, with_gamma_point=False, space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(He, kpts=kpts).density_fit() kmf.xc = 'lda' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:167: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([1.]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821728]]]), array([[[1. +0.j, 0.71555734-0.j], [0.71555734-0.j, 1.00158213-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_multigrid __________________________ self = def test_multigrid(self): kmf0 = krks.KRKS(cell, kpts=cell.make_kpts(nk)) kmf0.xc = 'lda' kmf0._numint = multigrid.MultiGridNumInt(cell) kmf0.kernel() rho0 = kmf0.get_rho() kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(cell, kpts=kpts) kmf.xc = 'lda' kmf._numint = multigrid.MultiGridNumInt(cell) > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:238: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. ... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_multigrid_kuks ________________________ self = def test_multigrid_kuks(self): kmf0 = pscf.KUKS(cell, kpts=cell.make_kpts(nk)) kmf0.xc = 'lda' kmf0._numint = multigrid.MultiGridNumInt(cell) kmf0.kernel() rho0 = kmf0.get_rho() kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KUKS(cell, kpts=kpts) kmf.xc = 'lda' kmf._numint = multigrid.MultiGridNumInt(cell) > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:262: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_rsh _____________________________ self = def test_rsh(self): kpts0 = He.make_kpts(nk, with_gamma_point=False) kmf0 = krks.KRKS(He, kpts=kpts0) kmf0.xc = 'camb3lyp' kmf0.kernel() kpts = He.make_kpts(nk, with_gamma_point=False, space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(He, kpts=kpts) kmf.xc = 'camb3lyp' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:151: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([1.]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821728]]]), array([[[1. +0.j, 0.71555734-0.j], [0.71555734-0.j, 1.00158213-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_rsh_df ____________________________ self = def test_rsh_df(self): kpts0 = He.make_kpts(nk, with_gamma_point=False) kmf0 = krks.KRKS(He, kpts=kpts0).density_fit() kmf0.xc = 'camb3lyp' kmf0.kernel() kpts = He.make_kpts(nk, with_gamma_point=False, space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(He, kpts=kpts).density_fit() kmf.xc = 'camb3lyp' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:205: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([1.]), NPArrayWithTag([[[0.00822224, 0.11676583], [0.11676583, 1.65821728]]]), array([[[1. +0.j, 0.71555734-0.j], [0.71555734-0.j, 1.00158213-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_to_rhf ____________________________ self = def test_to_rhf(self): kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kumf = pscf.KUKS(cell, kpts=kpts) kumf.xc = 'lda' > kumf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:292: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_to_uhf ____________________________ self = def test_to_uhf(self): kpts = cell.make_kpts(nk,space_group_symmetry=True,time_reversal_symmetry=True) kmf = pscf.KRKS(cell, kpts=kpts) kmf.xc = 'lda' > kmf.kernel() pyscf/pbc/dft/test/test_krks_ksym.py:279: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. ... -0.j, -0.54903114+0.j, 0. -0.j, 0. -0.j, -0. -0.j, 0. -0.j, 0.71268193-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_KRKSpU_ksymm _________________________ self = def test_KRKSpU_ksymm(self): cell1 = cell.copy() cell1.basis = 'gth-szv' cell1.mesh = [16,]*3 cell1.build() U_idx = ["1 C 2p"] U_val = [5.0] kmesh = [2, 2, 1] kpts0 = cell1.make_kpts(kmesh, wrap_around=True) mf0 = pdft.KRKSpU(cell1, kpts0, U_idx=U_idx, U_val=U_val, C_ao_lo='minao') e0 = mf0.kernel() kpts = cell1.make_kpts(kmesh, wrap_around=True, space_group_symmetry=True, time_reversal_symmetry=True) assert kpts.nkpts_ibz == 3 mf = pdft.KRKSpU(cell1, kpts, U_idx=U_idx, U_val=U_val, C_ao_lo='minao') > e1 = mf.kernel() ^^^^^^^^^^^ pyscf/pbc/dft/test/test_krkspu.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[ 2. , 0. , 0. , 0. , -0. , 0. ... +0.j, -0. -0.j, 0. -0.j, -0. -0.j, -0. +0.j, 0. +0.j, 1.62233716-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_kuks_as_kuhf _________________________ self = def test_kuks_as_kuhf(self): cell = pbcgto.Cell() cell.atom = "He 0 0 0; He 1 1 1" cell.basis = [[0, [1, 1]], [0, [.5, 1]]] cell.spin = 2 cell.a = np.eye(3) * 3 cell.build() kmesh = [3, 1, 1] kpts = cell.make_kpts(kmesh, time_reversal_symmetry=True) mf = pbcdft.KUKS(cell, kpts, xc="hf") mf.max_cycle = 1 > mf.kernel() pyscf/pbc/dft/test/test_kuks.py:129: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.33333333, 0.66666667]), array([[[[ 0.2692501 , 0.24320838, -0.05072588, 0.01813939], [ 0.24320838... ], [0.02683389-0.00066294j, 0.07574433-0.00466527j, 0.91551317-0.j , 1.00097187-0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->kx', ['k', 'kx']), ((1, 0), 'kx,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->kx', ['k', 'kx']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_KUKSpU_ksymm _________________________ self = def test_KUKSpU_ksymm(self): cell1 = cell.copy() cell1.basis = 'gth-szv' cell1.mesh = [16,]*3 cell1.build() U_idx = ["1 C 2p"] U_val = [5.0] kmesh = [2, 2, 1] kpts0 = cell1.make_kpts(kmesh, wrap_around=True) mf0 = pdft.KUKSpU(cell1, kpts0, U_idx=U_idx, U_val=U_val, C_ao_lo='minao') e0 = mf0.kernel() kpts = cell1.make_kpts(kmesh, wrap_around=True, space_group_symmetry=True, time_reversal_symmetry=True) assert kpts.nkpts_ibz == 3 mf = pdft.KUKSpU(cell1, kpts, U_idx=U_idx, U_val=U_val, C_ao_lo='minao') > e1 = mf.kernel() ^^^^^^^^^^^ pyscf/pbc/dft/test/test_kukspu.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf_ksymm.py:169: in get_init_guess ne = lib.einsum('k,xkij,kji->x', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,xkij,kji->x' tensors = [array([0.25, 0.5 , 0.25]), array([[[[ 1. , 0. , 0. , 0. , -0. , 0. , 0... +0.j, -0. -0.j, 0. -0.j, -0. -0.j, -0. +0.j, 0. +0.j, 1.62233716-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,xkij->xk', ['k', 'xk']), ((1, 0), 'xk,k->x', ['x'])] contraction = ((2, 1), 'kji,xkij->xk', ['k', 'xk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_eval_rhoG_nonorth_gga ____________________ self = def test_eval_rhoG_nonorth_gga(self): mydf = multigrid.MultiGridNumInt(cell_nonorth) > rhoG = multigrid._eval_rhoG(mydf, dm, hermi=1, kpts=kpts, deriv=1, rhog_high_order=True) pyscf/pbc/dft/test/test_multigrid.py:278: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:653: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 2.31413406, 0.2111437 , 0.2541592 , 0.20315739, 0.06980685,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_eval_rhoG_orth_gga ______________________ self = def test_eval_rhoG_orth_gga(self): mydf = multigrid.MultiGridNumInt(cell_orth) > rhoG = multigrid._eval_rhoG(mydf, dm, hermi=1, kpts=kpts, deriv=1, rhog_high_order=True) pyscf/pbc/dft/test/test_multigrid.py:265: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:653: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 2.31413406, 0.2111437 , 0.2541592 , 0.20315739, 0.06980685,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_eval_rhoG_orth_kpts _____________________ self = def test_eval_rhoG_orth_kpts(self): numpy.random.seed(9) dm = numpy.random.random(dm1.shape) + numpy.random.random(dm1.shape) * 1j mydf = multigrid.MultiGridNumInt(cell_orth) > rhoG = multigrid._eval_rhoG(mydf, dm, hermi=0, kpts=kpts, deriv=0, rhog_high_order=True) pyscf/pbc/dft/test/test_multigrid.py:251: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:639: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[0.01037415+0.03584792j, 0.50187459+0.39023337j, 0.08405965+0.83797882j, 0.34549864+0.78137289j, 0.01037415+... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_gen_rhf_response _______________________ self = def test_gen_rhf_response(self): numpy.random.seed(9) nkpts = len(kpts) nao = cell_he.nao mo = numpy.random.rand(nkpts, nao, 4) mo_occ = np.ones((nkpts, 4)) dm0 = np.einsum('kpi,kqi->kpq', mo, mo) dm1 = numpy.random.random(dm0.shape) dm1 = dm1 + dm1.transpose(0,2,1) dm1[1] = dm1[0] mydf = df.FFTDF(cell_he) ni = dft.numint.KNumInt() mf = dft.KRKS(cell_he) mf._numint = multigrid.MultiGridNumInt(cell_he) mf.kpts = kpts mf.xc = 'lda,' ref = dft.numint.nr_rks_fxc(ni, cell_he, mydf.grids, mf.xc, dm0, dm1, hermi=1, kpts=kpts) vj = mydf.get_jk(dm1, with_k=False, kpts=kpts)[0] ref += vj > v = mf.gen_response(mo, mo_occ, hermi=1)(dm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:312: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/krks.py:155: in gen_response rho0, vxc, fxc = ni.cache_xc_kernel(cell, mf.grids, mf.xc, mo_coeff, pyscf/pbc/dft/multigrid/multigrid.py:1927: in cache_xc_kernel return cache_xc_kernel(self, xc_code, mo_coeff, mo_occ, spin, kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1420: in cache_xc_kernel return cache_xc_kernel1(mydf, xc_code, dm, spin, kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[0.51568723, 0.35185177, 0.37452944, 0.45256322, 0.70962459, 1.03137446, 0.70370354], [0.35185177, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_gen_uhf_response _______________________ self = def test_gen_uhf_response(self): numpy.random.seed(9) nkpts = len(kpts) nao = cell_he.nao mo = numpy.random.rand(2, nao, 4) mo_occ = np.ones((2, 4)) dm0 = np.einsum('spi,sqi->spq', mo, mo) dm1 = numpy.random.random(dm0.shape) dm1 = dm1 + dm1.transpose(0,2,1) mydf = df.FFTDF(cell_he) ni = dft.numint.NumInt() mf = dft.UKS(cell_he) mf._numint = multigrid.MultiGridNumInt(cell_he) mf.xc = 'lda,' ref = dft.numint.nr_uks_fxc(ni, cell_he, mydf.grids, mf.xc, dm0, dm1, hermi=1) vj = mydf.get_jk(dm1, with_k=False)[0] ref += vj[0] + vj[1] > v = mf.gen_response(mo, mo_occ, hermi=1)(dm1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:440: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/uks.py:112: in gen_response rho0, vxc, fxc = ni.cache_xc_kernel(cell, mf.grids, mf.xc, pyscf/pbc/dft/multigrid/multigrid.py:1927: in cache_xc_kernel return cache_xc_kernel(self, xc_code, mo_coeff, mo_occ, spin, kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1420: in cache_xc_kernel return cache_xc_kernel1(mydf, xc_code, dm, spin, kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[0.51568723, 0.35185177, 0.37452944, 0.45256322, 0.70962459, 1.03137446, 0.70370354], [0.35185177, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_multigrid_krks ________________________ self = def test_multigrid_krks(self): mf = dft.KRKS(cell_he) mf.xc = 'lda,' ref = mf.get_veff(cell_he, dm_he, kpts=kpts) mf._numint = multigrid.MultiGridNumInt(cell_he) > out = mf.get_veff(cell_he, dm_he, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:157: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/krks.py:71: in get_veff n, exc, vxc = ni.nr_rks(cell, ks.grids, ks.xc, dm, 0, hermi, pyscf/pbc/dft/multigrid/multigrid.py:1893: in nr_rks return nr_rks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1106: in nr_rks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_multigrid_kroks _______________________ self = def test_multigrid_kroks(self): mf = dft.KROKS(cell_he) mf.xc = 'lda,' nao = cell_he.nao mo = dm_he mo_occ = numpy.ones((2,nao)) dm1 = numpy.einsum('kpi,ki,kqi->kpq', mo, mo_occ, mo) dm1 = lib.tag_array(numpy.array([dm1,dm1]), mo_coeff=mo, mo_occ=mo_occ*2) ref = mf.get_veff(cell_he, dm1, kpts=kpts) mf._numint = multigrid.MultiGridNumInt(cell_he) > out = mf.get_veff(cell_he, dm1, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:174: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/kroks.py:40: in get_veff return kuks.get_veff(ks, cell, dm, dm_last, vhf_last, hermi, kpts, kpts_band) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/kuks.py:57: in get_veff n, exc, vxc = ni.nr_uks(cell, ks.grids, ks.xc, dm, 0, hermi, pyscf/pbc/dft/multigrid/multigrid.py:1900: in nr_uks return nr_uks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1217: in nr_uks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.25839657, 0.60302297, 0.24180657, 0.57807485, 0.53683223, 2.51679314, 1.20604595], [0.60302297, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_multigrid_kuks ________________________ self = def test_multigrid_kuks(self): mf = dft.KUKS(cell_he) mf.xc = 'lda,' ref = mf.get_veff(cell_he, numpy.array((dm_he,dm_he)), kpts=kpts) mf._numint = multigrid.MultiGridNumInt(cell_he) > out = mf.get_veff(cell_he, (dm_he,dm_he), kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:146: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/kuks.py:57: in get_veff n, exc, vxc = ni.nr_uks(cell, ks.grids, ks.xc, dm, 0, hermi, pyscf/pbc/dft/multigrid/multigrid.py:1900: in nr_uks return nr_uks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1217: in nr_uks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_multigrid_rks ________________________ self = def test_multigrid_rks(self): mf = dft.RKS(cell_he) mf.xc = 'lda,' ref = mf.get_veff(cell_he, dm_he[0]) mf._numint = multigrid.MultiGridNumInt(cell_he) > out = mf.get_veff(cell_he, dm_he[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:196: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/rks.py:76: in get_veff n, exc, vxc = ni.nr_rks(cell, ks.grids, ks.xc, dm, 0, hermi, pyscf/pbc/dft/multigrid/multigrid.py:1893: in nr_rks return nr_rks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1106: in nr_rks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_multigrid_roks ________________________ self = def test_multigrid_roks(self): mf = dft.ROKS(cell_he) mf.xc = 'lda,' mo = dm_he[0] nao = cell_he.nao mo_occ = numpy.ones(nao) dm1 = numpy.einsum('pi,i,qi->pq', mo, mo_occ, mo) dm1 = lib.tag_array(numpy.array([dm1,dm1]), mo_coeff=mo, mo_occ=mo_occ*2) ref = mf.get_veff(cell_he, dm1) mf._numint = multigrid.MultiGridNumInt(cell_he) > out = mf.get_veff(cell_he, dm1) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:213: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/roks.py:40: in get_veff return uks.get_veff(ks, cell, dm, dm_last, vhf_last, hermi, kpt, kpts_band) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/uks.py:65: in get_veff n, exc, vxc = ni.nr_uks(cell, ks.grids, ks.xc, dm, 0, hermi, pyscf/pbc/dft/multigrid/multigrid.py:1900: in nr_uks return nr_uks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1217: in nr_uks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.25839657, 0.60302297, 0.24180657, 0.57807485, 0.53683223, 2.51679314, 1.20604595], [0.60302297, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_multigrid_uks ________________________ self = def test_multigrid_uks(self): mf = dft.UKS(cell_he) mf.xc = 'lda,' ref = mf.get_veff(cell_he, numpy.array((dm_he[0],dm_he[0]))) mf._numint = multigrid.MultiGridNumInt(cell_he) > out = mf.get_veff(cell_he, (dm_he[0], dm_he[0])) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:185: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/uks.py:65: in get_veff n, exc, vxc = ni.nr_uks(cell, ks.grids, ks.xc, dm, 0, hermi, pyscf/pbc/dft/multigrid/multigrid.py:1900: in nr_uks return nr_uks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1217: in nr_uks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_nonorth_get_j ________________________ self = def test_nonorth_get_j(self): ref = df.FFTDF(cell_nonorth).get_jk(dm, with_k=False)[0] > out = multigrid.MultiGridNumInt(cell_nonorth).get_j(dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:126: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1870: in get_j vj = get_j_kpts(self, dm, hermi, kpts.reshape(-1,3), kpts_band) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:534: in get_j_kpts rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv=0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 4.62826812, 0.42228741, 0.50831841, 0.40631477, 0.13961371,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_nonorth_get_j_kpts ______________________ self = def test_nonorth_get_j_kpts(self): ref = df.FFTDF(cell_nonorth).get_jk(dm, kpts=kpts, with_k=False)[0] > out = multigrid.MultiGridNumInt(cell_nonorth).get_j(dm, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:120: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1870: in get_j vj = get_j_kpts(self, dm, hermi, kpts.reshape(-1,3), kpts_band) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:534: in get_j_kpts rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv=0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 4.62826812, 0.42228741, 0.50831841, 0.40631477, 0.13961371,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_nonorth_get_pp ________________________ self = def test_nonorth_get_pp(self): ref = df.FFTDF(cell_nonorth).get_pp() > out = multigrid.MultiGridNumInt(cell_nonorth).get_pp() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:93: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:415: in get_pp vpp = _get_j_pass2(mydf, vpplocG, hermi, kpts)[0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:925: in _get_j_pass2 vp = lib.einsum('nkpq,pi,qj->nkij', vp, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkpq,pi,qj->nkij' tensors = [[array([[[-4.17819942, -0.01026509, -2.71729285, -1.31515049, -0.06450385, -0.06237348, -0.05937251, -0.02117523, -0.... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkpq->knpj', ['pi', 'knpj']), ((1, 0), 'knpj,pi->nkij', ['nkij'])] contraction = ((2, 0), 'qj,nkpq->knpj', ['pi', 'knpj']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_nr_rks_fxc __________________________ self = def test_nr_rks_fxc(self): numpy.random.seed(9) dm1 = numpy.random.random(dm_he.shape) + numpy.random.random(dm_he.shape)*1j dm1 = dm1 + dm1.transpose(0,2,1) mydf = df.FFTDF(cell_he) ni = dft.numint.NumInt() mg_df = multigrid.MultiGridNumInt(cell_he) xc = 'lda,' ref = dft.numint.nr_rks_fxc(ni, cell_he, mydf.grids, xc, dm_he[0], dm1, hermi=1) > v = multigrid.nr_rks_fxc(mg_df, xc, dm_he[0], dm1, hermi=1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:337: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1290: in nr_rks_fxc fxc = cache_xc_kernel1(mydf, xc_code, dm0, spin=0, kpts=kpts)[2] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_nr_rks_fxc_hermi0 ______________________ self = def test_nr_rks_fxc_hermi0(self): numpy.random.seed(9) dm1 = numpy.random.random(dm_he.shape) + numpy.random.random(dm_he.shape)*1j mydf = df.FFTDF(cell_he) ni = dft.numint.NumInt() mg_df = multigrid.MultiGridNumInt(cell_he) xc = 'lda,' ref = dft.numint.nr_rks_fxc(ni, cell_he, mydf.grids, xc, dm_he[0], dm1, hermi=0) > v = multigrid.nr_rks_fxc(mg_df, xc, dm_he[0], dm1, hermi=0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:359: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1290: in nr_rks_fxc fxc = cache_xc_kernel1(mydf, xc_code, dm0, spin=0, kpts=kpts)[2] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_nr_rks_fxc_st ________________________ self = def test_nr_rks_fxc_st(self): numpy.random.seed(9) nkpts = len(kpts) nao = cell_he.nao mo = numpy.random.rand(nkpts, nao, 4) mo_occ = np.ones((nkpts, 4)) dm0 = np.einsum('kpi,kqi->kpq', mo, mo) dm1 = numpy.random.rand(3,nkpts,nao,nao) + numpy.random.rand(3,nkpts,nao,nao)*1j dm1 = dm1 + dm1.transpose(0,1,3,2).conj() mydf = df.FFTDF(cell_he) ni = dft.numint.KNumInt() mf = dft.KRKS(cell_he) mf._numint = multigrid.MultiGridNumInt(cell_he) mf.kpts = kpts mf.xc = 'lda,' ref = dft.numint.nr_rks_fxc_st(ni, cell_he, mydf.grids, mf.xc, dm0, dm1, singlet=True, kpts=kpts) > v = multigrid.nr_rks_fxc_st(mf._numint, mf.xc, dm0, dm1, singlet=True, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:390: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1338: in nr_rks_fxc_st fxc = cache_xc_kernel1(mydf, xc_code, dm0, spin=1, kpts=kpts)[2] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[0.51568723, 0.35185177, 0.37452944, 0.45256322, 0.70962459, 1.03137446, 0.70370354], [0.35185177, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_nr_uks_fxc __________________________ self = def test_nr_uks_fxc(self): numpy.random.seed(9) nkpts = len(kpts) nao = cell_he.nao dm1 = numpy.random.rand(3,nkpts,nao,nao) + numpy.random.rand(3,nkpts,nao,nao)*1j dm1 = dm1 + dm1.transpose(0,1,3,2).conj() mydf = df.FFTDF(cell_he) ni = dft.numint.KNumInt() mg_df = multigrid.MultiGridNumInt(cell_he) xc = 'lda,' ref = dft.numint.nr_uks_fxc(ni, cell_he, mydf.grids, xc, (dm_he, dm_he), (dm1, dm1), hermi=1, kpts=kpts) > v = multigrid.nr_uks_fxc(mg_df, xc, (dm_he, dm_he), (dm1, dm1), hermi=1, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:467: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1366: in nr_uks_fxc fxc = cache_xc_kernel1(mydf, xc_code, dm0, spin=1, kpts=kpts)[2] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_orth_get_j_kpts _______________________ self = def test_orth_get_j_kpts(self): ref = df.FFTDF(cell_orth).get_jk(dm, kpts=kpts, with_k=False)[0] > out = multigrid.MultiGridNumInt(cell_orth).get_j(dm, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:111: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1870: in get_j vj = get_j_kpts(self, dm, hermi, kpts.reshape(-1,3), kpts_band) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:534: in get_j_kpts rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv=0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 4.62826812, 0.42228741, 0.50831841, 0.40631477, 0.13961371,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_orth_get_nuc_kpts ______________________ self = def test_orth_get_nuc_kpts(self): ref = df.FFTDF(cell_orth).get_nuc(kpts) > out = multigrid.MultiGridNumInt(cell_orth).get_nuc(kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:105: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:386: in get_nuc vne = _get_j_pass2(mydf, vneG, hermi, kpts)[0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:925: in _get_j_pass2 vp = lib.einsum('nkpq,pi,qj->nkij', vp, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkpq,pi,qj->nkij' tensors = [[array([[[-1.99814774-0.j , 0.00000672+0.00007322j, -0.95055077-0.00001364j, 0.00084115+0.04594705j, 0.0008... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkpq->nkpj', ['pi', 'nkpj']), ((1, 0), 'nkpj,pi->nkij', ['nkij'])] contraction = ((2, 0), 'qj,nkpq->nkpj', ['pi', 'nkpj']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_orth_get_pp _________________________ self = def test_orth_get_pp(self): ref = df.FFTDF(cell_orth).get_pp() > out = multigrid.MultiGridNumInt(cell_orth).get_pp() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:415: in get_pp vpp = _get_j_pass2(mydf, vpplocG, hermi, kpts)[0] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:925: in _get_j_pass2 vp = lib.einsum('nkpq,pi,qj->nkij', vp, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkpq,pi,qj->nkij' tensors = [[array([[[-1.64982395, 0.00113339, -0.84773583, 0.00077755, 0.00077755, 0.00077755, -0.13554875, -0.00504269, -0.... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkpq->knpj', ['pi', 'knpj']), ((1, 0), 'knpj,pi->nkij', ['nkij'])] contraction = ((2, 0), 'qj,nkpq->knpj', ['pi', 'knpj']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_orth_rks_gga_kpts ______________________ self = def test_orth_rks_gga_kpts(self): xc = 'b88,' mydf = df.FFTDF(cell_orth) ni = dft.numint.KNumInt() n, exc0, ref = ni.nr_rks(cell_orth, mydf.grids, xc, dm, hermi=1, kpts=kpts) ref += mydf.get_jk(dm, hermi=1, with_k=False, kpts=kpts)[0] mydf = multigrid.MultiGridNumInt(cell_orth) > n, exc1, vxc = multigrid.nr_rks(mydf, xc, dm, hermi=1, kpts=kpts, with_j=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:226: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1106: in nr_rks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 4.62826812, 0.42228741, 0.50831841, 0.40631477, 0.13961371,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_orth_rks_lda_kpts ______________________ self = def test_orth_rks_lda_kpts(self): xc = 'lda,' mydf = df.FFTDF(cell_orth) ni = dft.numint.KNumInt() n, exc0, ref = ni.nr_rks(cell_orth, mydf.grids, xc, dm, 1, kpts=kpts) mydf = multigrid.MultiGridNumInt(cell_orth) > n, exc1, vxc = multigrid.nr_rks(mydf, xc, dm, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:136: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1106: in nr_rks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 4.62826812, 0.42228741, 0.50831841, 0.40631477, 0.13961371,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_orth_uks_fxc_hermi0 _____________________ self = def test_orth_uks_fxc_hermi0(self): numpy.random.seed(9) dm1 = numpy.random.random(dm_he.shape) + numpy.random.random(dm_he.shape)*1j mydf = df.FFTDF(cell_he) ni = dft.numint.KNumInt() mg_df = multigrid.MultiGridNumInt(cell_he) xc = 'lda,' ref = dft.numint.nr_uks_fxc(ni, cell_he, mydf.grids, xc, (dm_he, dm_he), (dm1, dm1), hermi=0, kpts=kpts) > v = multigrid.nr_uks_fxc(mg_df, xc, (dm_he, dm_he), (dm1, dm1), hermi=0, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:490: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1366: in nr_uks_fxc fxc = cache_xc_kernel1(mydf, xc_code, dm0, spin=1, kpts=kpts)[2] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:1452: in cache_xc_kernel1 rhoG = _eval_rhoG(mydf, dm, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.05607367, 0.23406027, 0.06466022, 0.2003034 , 0.20980554, 2.11214735, 0.46812053], [0.23406027, ...0. , 0. ], [0. , 0. , 0. , 0. , 0. , 0.09155105, 0.91551048]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_orth_uks_gga_kpts ______________________ self = def test_orth_uks_gga_kpts(self): xc = 'b88,' mydf = df.FFTDF(cell_orth) ni = dft.numint.KNumInt() dms = numpy.array([dm, dm]) n, exc0, ref = ni.nr_uks(cell_orth, mydf.grids, xc, dms, hermi=1, kpts=kpts) vj = mydf.get_jk(dms, hermi=1, with_k=False, kpts=kpts)[0] ref += vj[0] + vj[1] ni = multigrid.MultiGridNumInt(cell_orth) > n, exc1, vxc = ni.nr_uks(cell_orth, None, xc, dms, hermi=1, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:241: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1900: in nr_uks return nr_uks(self, xc_code, dm_kpts, hermi, kpts, kpts_band, pyscf/pbc/dft/multigrid/multigrid.py:1217: in nr_uks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[2.31413406, 0.2111437 , 0.06278667, 0.06503742, 4.62826812, 0.42228741, 0.50831841, 0.40631477, 0.13961371,... 0. , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']), ((1, 0), 'kniq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->kniq', ['pi', 'kniq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_rcut_vs_ke_cut ________________________ self = def test_rcut_vs_ke_cut(self): xc = 'lda,' with lib.temporary_env(multigrid, TASKS_TYPE='rcut'): mg_df = multigrid.MultiGridNumInt(cell_orth) > n1, exc1, v1 = multigrid.nr_rks(mg_df, xc, dm1, kpts=kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/test/test_multigrid.py:507: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/dft/multigrid/multigrid.py:1106: in nr_rks rhoG = _eval_rhoG(mydf, dm_kpts, hermi, kpts, deriv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/dft/multigrid/multigrid.py:632: in _eval_rhoG pgto_dms = lib.einsum('nkij,pi,qj->nkpq', dms_ht, h_coeff, t_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'nkij,pi,qj->nkpq' tensors = [array([[[[1.15706703, 0.17079506, 0.09884737, 0.1693123 , 0.0159291 , 0.10104922, 0.0130573 , 0.08562447, 0.01930618,... , 0. , 0. , 0. , 0. , -0.40580393, 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']), ((1, 0), 'nkiq,pi->nkpq', ['nkpq'])] contraction = ((2, 0), 'qj,nkij->nkiq', ['pi', 'nkiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_gw ______________________________ self = def test_gw(self): cell = gto.Cell() cell.build(a = ''' 0.000000 1.783500 1.783500 1.783500 0.000000 1.783500 1.783500 1.783500 0.000000 ''', atom = 'H 1.337625 1.337625 1.337625; H 2.229375 2.229375 2.229375', verbose = 4, output = '/dev/null', basis=[[0, [2., 1.]], [0, [.5, 1.]]]) kpts = cell.make_kpts([3,1,1],scaled_center=[0,0,0]) kmf = dft.KRKS(cell, kpts).density_fit().run() gw = krgw_ac.KRGWAC(kmf) gw.linearized = True gw.ac = 'pade' # without finite size corrections gw.fc = False nocc = gw.nocc gw.kernel(kptlist=[0,1,2],orbs=range(0,nocc+3)) self.assertAlmostEqual(gw.mo_energy[0][nocc-1], -0.257088388010083, 6) self.assertAlmostEqual(gw.mo_energy[0][nocc] , 0.7377021147675703, 6) self.assertAlmostEqual(gw.mo_energy[1][nocc-1], -0.121872186953884, 6) self.assertAlmostEqual(gw.mo_energy[1][nocc] , 0.570710170186033 , 6) # with finite size corrections gw.linearized = False gw.fc = True > gw.kernel(kptlist=[0,1,2],orbs=range(0,nocc+3)) pyscf/pbc/gw/test/test_krgw.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/gw/krgw_ac.py:638: in kernel kernel(self, mo_energy, mo_coeff, orbs=orbs, pyscf/pbc/gw/krgw_ac.py:100: in kernel sigmaI, omega = get_sigma_diag(gw, orbs, kptlist, freqs, wts, iw_cutoff=5.) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/gw/krgw_ac.py:255: in get_sigma_diag qij = get_qij(gw, q_abs[0], mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/gw/krgw_ac.py:417: in get_qij ao_ao_grad = einsum('g,mg,xgn->xmn',weights,ao.T.conj(),ao_grad) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'g,mg,xgn->xmn' tensors = [array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], shape=(42064,)), array([...19701, -0.00003109, -0.01970582], [-0.50256118, -0.11635281, -0.00000202, -0.00243253]]], shape=(3, 42064, 4))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mg,g->mg', ['xgn', 'mg']), ((1, 0), 'mg,xgn->xmn', ['xmn'])] contraction = ((1, 0), 'mg,g->mg', ['xgn', 'mg']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_gwac_pade __________________________ self = def test_gwac_pade(self): gw = kugw_ac.KUGWAC(kmf) gw.linearized = False gw.ac = 'pade' gw.fc = False nocca, noccb = gw.nocc gw.kernel(kptlist=[0,1,2], orbs=range(0, nocca+3)) self.assertAlmostEqual(gw.mo_energy[0][0][nocca-1], -0.28012813, 5) self.assertAlmostEqual(gw.mo_energy[0][0][nocca], 0.13748876, 5) self.assertAlmostEqual(gw.mo_energy[0][1][nocca-1], -0.29515851, 5) self.assertAlmostEqual(gw.mo_energy[0][1][nocca], 0.14128011, 5) self.assertAlmostEqual(gw.mo_energy[1][0][noccb-1], -0.33991721, 5) self.assertAlmostEqual(gw.mo_energy[1][0][noccb], 0.10578847, 5) self.assertAlmostEqual(gw.mo_energy[1][1][noccb-1], -0.33547973, 5) self.assertAlmostEqual(gw.mo_energy[1][1][noccb], 0.08053408, 5) gw.fc = True nocca, noccb = gw.nocc > gw.kernel(kptlist=[0,1,2], orbs=range(0,nocca+3)) pyscf/pbc/gw/test/test_kugw.py:55: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/gw/kugw_ac.py:707: in kernel kernel(self, mo_energy, mo_coeff, orbs=orbs, pyscf/pbc/gw/kugw_ac.py:103: in kernel sigmaI, omega = get_sigma_diag(gw, orbs, kptlist, freqs, wts, iw_cutoff=5.) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/gw/kugw_ac.py:279: in get_sigma_diag qij = get_qij(gw, q_abs[0], mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/gw/kugw_ac.py:478: in get_qij ao_ao_grad = einsum('g,mg,xgn->xmn',weights,ao.T.conj(),ao_grad) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'g,mg,xgn->xmn' tensors = [array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], shape=(44721,)), array([...03056, -0.00001941, 0.00243396, -0.00435455, -0.00000553, -0.00000227, -0.00000446]]], shape=(3, 44721, 15))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'mg,g->mg', ['xgn', 'mg']), ((1, 0), 'mg,xgn->xmn', ['xmn'])] contraction = ((1, 0), 'mg,g->mg', ['xgn', 'mg']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ksymm ____________________________ self = def test_ksymm(self): def run_k(cell, kmesh): kpts = cell.make_kpts(kmesh, space_group_symmetry=True) mf = pbcscf.KRHF(cell, kpts).density_fit(auxbasis=make_auxbasis(cell)) mf.conv_tol = 1e-10 mf.kernel() pt = pyscf.pbc.mp.kmp2_ksymm.KMP2(mf).run() return pt cell = build_cell(space_group_symmetry=True) > pt = run_k(cell, (1,1,1)) ^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/mp/test/test_scs.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/mp/test/test_scs.py:78: in run_k mf.kernel() :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([1.]), NPArrayWithTag([[[ 2.00465184, 0.03432216, 0.02200809, 0. , 0. , 0. , 0. ... , 0. , -0. , -0. , 0. , -0. , 0. , 0. , 1.00906169]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_krhf_smearing ________________________ self = def test_krhf_smearing(self): mf = pscf.KRHF(cell, cell.make_kpts([2,1,1])) nkpts = len(mf.kpts) pscf.addons.smearing_(mf, 0.1, 'fermi') mo_energy_kpts = numpy.array([numpy.arange(nao)*.2+numpy.cos(i+.5)*.1 for i in range(nkpts)]) > occ = mf.get_occ(mo_energy_kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_addons.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/addons.py:180: in get_occ logger.info(self, ' sigma = %g Optimized mu = %.12g entropy = %.12g', pyscf/lib/logger.py:135: in info flush(rec, msg, *args) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rec = msg = ' sigma = %g Optimized mu = %.12g entropy = %.12g' args = (0.1, array([0.34741599]), np.float64(3.0828197480266506)) def flush(rec, msg, *args): > rec.stdout.write(msg%args) ^^^^^^^^ E TypeError: only 0-dimensional arrays can be converted to Python scalars pyscf/lib/logger.py:114: TypeError ________________________ KnownValues.test_kuhf_smearing ________________________ self = def test_kuhf_smearing(self): mf = pscf.KUHF(cell, cell.make_kpts([2,1,1])) nkpts = len(mf.kpts) pscf.addons.smearing_(mf, 0.1, 'fermi') mo_energy_kpts = numpy.array([numpy.arange(nao)*.2+numpy.cos(i+.5)*.1 for i in range(nkpts)]) mo_energy_kpts = numpy.array([mo_energy_kpts, mo_energy_kpts+numpy.cos(mo_energy_kpts)*.02]) > occ = mf.get_occ(mo_energy_kpts) ^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_addons.py:77: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/addons.py:180: in get_occ logger.info(self, ' sigma = %g Optimized mu = %.12g entropy = %.12g', pyscf/lib/logger.py:135: in info flush(rec, msg, *args) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rec = msg = ' sigma = %g Optimized mu = %.12g entropy = %.12g' args = (0.1, array([0.3567294]), np.float64(3.0901695040750425)) def flush(rec, msg, *args): > rec.stdout.write(msg%args) ^^^^^^^^ E TypeError: only 0-dimensional arrays can be converted to Python scalars pyscf/lib/logger.py:114: TypeError ________________________ KnownValues.test_rhf_smearing _________________________ self = def test_rhf_smearing(self): mf = pscf.RHF(cell) pscf.addons.smearing_(mf, 0.1, 'fermi') mo_energy = numpy.arange(nao)*.2+numpy.cos(.5)*.1 > mf.get_occ(mo_energy) pyscf/pbc/scf/test/test_addons.py:111: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/scf/addons.py:226: in get_occ logger.info(self, ' sigma = %g Optimized mu = %.12g entropy = %.12g', pyscf/lib/logger.py:135: in info flush(rec, msg, *args) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rec = msg = ' sigma = %g Optimized mu = %.12g entropy = %.12g' args = (0.1, array([0.387758]), np.float64(3.0922723199786404)) def flush(rec, msg, *args): > rec.stdout.write(msg%args) ^^^^^^^^ E TypeError: only 0-dimensional arrays can be converted to Python scalars pyscf/lib/logger.py:114: TypeError ________________________ KnownValues.test_uhf_smearing _________________________ self = def test_uhf_smearing(self): mf = pscf.UHF(cell) pscf.addons.smearing_(mf, 0.1, 'fermi') mo_energy = numpy.arange(nao)*.2+numpy.cos(.5)*.1 mo_energy = numpy.array([mo_energy, mo_energy+numpy.cos(mo_energy)*.02]) > mf.get_occ(mo_energy) pyscf/pbc/scf/test/test_addons.py:126: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/scf/addons.py:226: in get_occ logger.info(self, ' sigma = %g Optimized mu = %.12g entropy = %.12g', pyscf/lib/logger.py:135: in info flush(rec, msg, *args) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rec = msg = ' sigma = %g Optimized mu = %.12g entropy = %.12g' args = (0.1, array([0.39693]), np.float64(3.100738790542102)) def flush(rec, msg, *args): > rec.stdout.write(msg%args) ^^^^^^^^ E TypeError: only 0-dimensional arrays can be converted to Python scalars pyscf/lib/logger.py:114: TypeError ___________________________ KnownValues.test_analyze ___________________________ self = def test_analyze(self): > rpop, rchg = kmf.analyze()[0] ^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_khf.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/khf.py:276: in analyze pop, chg = mf.mulliken_meta(mf.cell, dm, s=ovlp_ao, verbose=verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:833: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.731998+0.j , 0. -0.j , -0. +0.j , 0. +0.j , 0.502855+0.j , 0...., 0.043604+0.014995j, -0.012256+0.085073j, -0.097176-0.j , 0.097176-0.j , 0.511496+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KPTvsSUPCELL_noshift.test_kghf ________________________ self = def test_kghf(self): spin0 = 2 kmesh = [3,1,1] spin = int(np.prod(kmesh)) * spin0 cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KGHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/kghf.py:271: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/kghf.py:169: in mulliken_meta dm_aa, dm_bb = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kghf.py:150: in _make_rdm1_meta dm_aa = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts[:,:nao,:nao], c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146059-0.j , 0. +0.j , 0. -0.j , -0. +0.j , 0...., 0.006841-0.000093j, -0.014818+0.000081j, -0.11723 -0.000058j, 0.066307+0.001304j, 0.544546+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KPTvsSUPCELL_noshift.test_krhf ________________________ self = def test_krhf(self): kmesh = [3,1,1] cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KRHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:48: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/khf.py:833: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146059-0.j , 0. +0.j , 0. -0.j , -0. +0.j , 0...., 0.006841-0.000093j, -0.014818+0.000081j, -0.11723 -0.000058j, 0.066307+0.001304j, 0.544546+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KPTvsSUPCELL_noshift.test_krohf ________________________ self = def test_krohf(self): spin0 = 2 kmesh = [3,1,1] spin = int(np.prod(kmesh)) * spin0 cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KROHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:99: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/krohf.py:368: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/krohf.py:218: in mulliken_meta return khf.mulliken_meta(cell, dm, kpts, verbose, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146059-0.j , 0. +0.j , 0. -0.j , -0. +0.j , 0...., 0.006841-0.000093j, -0.014818+0.000081j, -0.11723 -0.000058j, 0.066307+0.001304j, 0.544546+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KPTvsSUPCELL_noshift.test_kuhf ________________________ self = def test_kuhf(self): spin0 = 2 kmesh = [3,1,1] spin = int(np.prod(kmesh)) * spin0 cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KUHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/kuhf.py:555: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/kuhf.py:245: in mulliken_meta dm_a, dm_b = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf.py:229: in _make_rdm1_meta dm_a = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts[0], c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146059-0.j , 0. +0.j , 0. -0.j , -0. +0.j , 0...., 0.006841-0.000093j, -0.014818+0.000081j, -0.11723 -0.000058j, 0.066307+0.001304j, 0.544546+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KPTvsSUPCELL_shift.test_kghf _________________________ self = def test_kghf(self): spin0 = 2 kmesh = [3,1,1] spin = int(np.prod(kmesh)) * spin0 cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KGHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/kghf.py:271: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/kghf.py:169: in mulliken_meta dm_aa, dm_bb = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kghf.py:150: in _make_rdm1_meta dm_aa = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts[:,:nao,:nao], c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146058-0.j , 0. -0.j , 0. +0.j , -0. -0.j , 0...., 0.00647 +0.00068j , -0.015071+0.000255j, -0.118479+0.002057j, 0.062709+0.00885j , 0.544887+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KPTvsSUPCELL_shift.test_krhf _________________________ self = def test_krhf(self): kmesh = [3,1,1] cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KRHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:48: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/khf.py:833: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146058-0.j , 0. -0.j , 0. +0.j , -0. -0.j , 0...., 0.00647 +0.00068j , -0.015071+0.000255j, -0.118479+0.002057j, 0.062709+0.00885j , 0.544887+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KPTvsSUPCELL_shift.test_krohf _________________________ self = def test_krohf(self): spin0 = 2 kmesh = [3,1,1] spin = int(np.prod(kmesh)) * spin0 cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KROHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:99: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/krohf.py:368: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/krohf.py:218: in mulliken_meta return khf.mulliken_meta(cell, dm, kpts, verbose, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146058-0.j , 0. -0.j , 0. +0.j , -0. -0.j , 0...., 0.00647 +0.00068j , -0.015071+0.000255j, -0.118479+0.002057j, 0.062709+0.00885j , 0.544887+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KPTvsSUPCELL_shift.test_kuhf _________________________ self = def test_kuhf(self): spin0 = 2 kmesh = [3,1,1] spin = int(np.prod(kmesh)) * spin0 cell, scell, kpts = self.make_cell_supcell_kpts(kmesh) kmf = scf.KUHF(cell, kpts=kpts).density_fit() kdm = kmf.init_guess_by_1e() > kchg = kmf.mulliken_meta(cell, kdm, kpts, verbose=0)[1] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_mulliken_meta.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/kuhf.py:555: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/kuhf.py:245: in mulliken_meta dm_a, dm_b = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf.py:229: in _make_rdm1_meta dm_a = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts[0], c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.577269-0.j , 0.146058-0.j , 0. -0.j , 0. +0.j , -0. -0.j , 0...., 0.00647 +0.00068j , -0.015071+0.000255j, -0.118479+0.002057j, 0.062709+0.00885j , 0.544887+0.j ]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']), ((1, 0), 'kaq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->kaq', ['kbq', 'kaq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_analyze ___________________________ self = def test_analyze(self): > pop, chg = kmf.analyze()[0] ^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_rohf.py:122: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/khf.py:276: in analyze pop, chg = mf.mulliken_meta(mf.cell, dm, s=ovlp_ao, verbose=verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/krohf.py:368: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/krohf.py:218: in mulliken_meta return khf.mulliken_meta(cell, dm, kpts, verbose, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.433569+0.j, 0.447343+0.j, -0.012719+0.j, 0.151384+0.j], [-0.246379-0.j, 0.172058+0.j, -0.03395... 0.118117+0.j, 0.430461+0.j, 0.45103 +0.j], [-0.013708-0.j, 0.009573+0.j, -0.253994-0.j, 0.177376+0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->akq', ['kbq', 'akq']), ((1, 0), 'akq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->akq', ['kbq', 'akq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_krohf_kernel _________________________ self = def test_krohf_kernel(self): self.assertAlmostEqual(kmf.e_tot, -4.57655196508766, 8) > kmf.analyze() pyscf/pbc/scf/test/test_rohf.py:53: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/khf.py:276: in analyze pop, chg = mf.mulliken_meta(mf.cell, dm, s=ovlp_ao, verbose=verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/krohf.py:368: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/krohf.py:218: in mulliken_meta return khf.mulliken_meta(cell, dm, kpts, verbose, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:311: in mulliken_meta dm = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf.py:296: in _make_rdm1_meta dm = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts, c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.433569+0.j, 0.447343+0.j, -0.012719+0.j, 0.151384+0.j], [-0.246379-0.j, 0.172058+0.j, -0.03395... 0.118117+0.j, 0.430461+0.j, 0.45103 +0.j], [-0.013708-0.j, 0.009573+0.j, -0.253994-0.j, 0.177376+0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->akq', ['kbq', 'akq']), ((1, 0), 'akq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->akq', ['kbq', 'akq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_2d ______________________________ self = def test_2d(self): a = np.eye(3) * 2.5 a[2,2] = 7. cell1 = Cell().build( dimension = 2, a = a, atom = '''He 0.5 0.5 0.2''', basis = {'He': [[0, [4.0, 1, -.1], [1.1, .3, .5]],]}) kpts = cell1.make_kpts([3,1,1]) np.random.seed(1) dm = (np.random.rand(len(kpts), cell1.nao, cell1.nao) + np.random.rand(len(kpts), cell1.nao, cell1.nao) * 1j) dm = dm + dm.transpose(0,2,1).conj() kmesh = k2gamma.kpts_to_kmesh(cell1, kpts) phase = k2gamma.get_phase(cell1, kpts, kmesh)[1] dm = np.einsum('Rk,kuv,Sk->RSuv', phase.conj().T, dm, phase.T) dm = np.einsum('Rk,RSuv,Sk->kuv', phase, dm.real, phase.conj()) mf = cell1.KRHF(kpts=kpts) jref, kref = mf.get_jk(cell1, dm, kpts=kpts) ej = np.einsum('kij,kji->', jref, dm) ek = np.einsum('kij,kji->', kref, dm) * .5 jk_builder = rsjk.RangeSeparatedJKBuilder(cell1, kpts) > vj, vk = jk_builder.get_jk(dm, kpts=kpts, exxdiv=mf.exxdiv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_rsjk.py:216: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/rsjk.py:486: in get_jk vs = self._get_jk_sr(dms, hermi, kpts, kpts_band, pyscf/pbc/scf/rsjk.py:331: in _get_jk_sr sc_dm = lib.einsum('k,Sk,nkuv->nSuv', expLk[0]*weight, expLk.conj(), dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,Sk,nkuv->nSuv' tensors = [array([0.333333+0.j, 0.333333+0.j, 0.333333+0.j]), array([[ 1. -0.j , 1. -0.j , 1. -0.j ], [ ...0.j ]], [[0.543523-0.j , 0.618305+0.118267j], [0.618305-0.118267j, 1.03078 +0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']), ((1, 0), 'Sk,nkuv->nSuv', ['nSuv'])] contraction = ((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_get_jk ____________________________ self = def test_get_jk(self): cell = Cell().build( a = np.eye(3)*1.8, atom = '''He 0. 0. 0. He 0.4917 0.4917 0.4917''', basis = {'He': [[0, [2.5, 1]]]}, precision = 1e-9, ) kpts = cell.make_kpts([3,1,1]) np.random.seed(1) dm = (np.random.rand(len(kpts), cell.nao, cell.nao) + np.random.rand(len(kpts), cell.nao, cell.nao) * 1j) dm = dm + dm.transpose(0,2,1).conj() kmesh = k2gamma.kpts_to_kmesh(cell, kpts) phase = k2gamma.get_phase(cell, kpts, kmesh)[1] dm = np.einsum('Rk,kuv,Sk->RSuv', phase.conj().T, dm, phase.T) dm = np.einsum('Rk,RSuv,Sk->kuv', phase, dm.real, phase.conj()) mf = cell.KRHF(kpts=kpts) jref, kref = mf.get_jk(cell, dm, kpts=kpts) ej = np.einsum('kij,kji->', jref, dm) ek = np.einsum('kij,kji->', kref, dm) * .5 jk_builder = rsjk.RangeSeparatedJKBuilder(cell, kpts) jk_builder.allow_drv_nodddd = False > vj, vk = jk_builder.get_jk(dm, kpts=kpts, exxdiv=mf.exxdiv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_rsjk.py:51: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/rsjk.py:486: in get_jk vs = self._get_jk_sr(dms, hermi, kpts, kpts_band, pyscf/pbc/scf/rsjk.py:331: in _get_jk_sr sc_dm = lib.einsum('k,Sk,nkuv->nSuv', expLk[0]*weight, expLk.conj(), dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,Sk,nkuv->nSuv' tensors = [array([0.333333+0.j, 0.333333+0.j, 0.333333+0.j]), array([[ 1. -0.j , 1. -0.j , 1. -0.j ], [ ...0.j ]], [[0.543523-0.j , 0.618305+0.118267j], [0.618305-0.118267j, 1.03078 +0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']), ((1, 0), 'Sk,nkuv->nSuv', ['nSuv'])] contraction = ((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_get_jk_fft_dd_block _____________________ self = def test_get_jk_fft_dd_block(self): cell1 = Cell().build( a = np.eye(3)*2.6, atom = '''He 0.4917 0.4917 0.4917''', basis = {'He': [[0, [4.8, 1, -.1], [1.1, .3, .5], [0.1, .2, .8]], [1, [0.8, 1]],]}) kpts = cell1.make_kpts([3,1,1]) np.random.seed(1) dm = (np.random.rand(len(kpts), cell1.nao, cell1.nao) + np.random.rand(len(kpts), cell1.nao, cell1.nao) * 1j) dm = dm + dm.transpose(0,2,1).conj() kmesh = k2gamma.kpts_to_kmesh(cell1, kpts) phase = k2gamma.get_phase(cell1, kpts, kmesh)[1] dm = np.einsum('Rk,kuv,Sk->RSuv', phase.conj().T, dm, phase.T) dm = np.einsum('Rk,RSuv,Sk->kuv', phase, dm.real, phase.conj()) mf = cell1.KRHF(kpts=kpts) jref, kref = mf.get_jk(cell1, dm, kpts=kpts) ej = np.einsum('kij,kji->', jref, dm) ek = np.einsum('kij,kji->', kref, dm) * .5 jk_builder = rsjk.RangeSeparatedJKBuilder(cell1, kpts) > vj, vk = jk_builder.get_jk(dm, kpts=kpts, exxdiv=mf.exxdiv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_rsjk.py:129: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/rsjk.py:486: in get_jk vs = self._get_jk_sr(dms, hermi, kpts, kpts_band, pyscf/pbc/scf/rsjk.py:331: in _get_jk_sr sc_dm = lib.einsum('k,Sk,nkuv->nSuv', expLk[0]*weight, expLk.conj(), dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,Sk,nkuv->nSuv' tensors = [array([0.333333+0.j, 0.333333+0.j, 0.333333+0.j]), array([[ 1. -0.j , 1. -0.j , 1. -0.j ], [ ...2j], [1.360506+0.358483j, 1.218853+0.198094j, 0.616494+0.001781j, 0.892474+0.196612j, 0.527705+0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']), ((1, 0), 'Sk,nkuv->nSuv', ['nSuv'])] contraction = ((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_get_jk_sr_without_dddd ____________________ self = def test_get_jk_sr_without_dddd(self): cell1 = Cell().build( a = np.eye(3)*2.6, atom = '''He 0.4917 0.4917 0.4917''', basis = {'He': [[0, [4.8, 1, -.1], [1.1, .3, .5], [0.1, .2, .8]],]}) kpts = cell1.make_kpts([3,1,1]) np.random.seed(1) dm = (np.random.rand(len(kpts), cell1.nao, cell1.nao) + np.random.rand(len(kpts), cell1.nao, cell1.nao) * 1j) dm = dm + dm.transpose(0,2,1).conj() kmesh = k2gamma.kpts_to_kmesh(cell1, kpts) phase = k2gamma.get_phase(cell1, kpts, kmesh)[1] dm = np.einsum('Rk,kuv,Sk->RSuv', phase.conj().T, dm, phase.T) dm = np.einsum('Rk,RSuv,Sk->kuv', phase, dm.real, phase.conj()) mf = cell1.KRHF(kpts=kpts) jref, kref = mf.get_jk(cell1, dm, kpts=kpts) ej = np.einsum('kij,kji->', jref, dm) ek = np.einsum('kij,kji->', kref, dm) * .5 jk_builder = rsjk.RangeSeparatedJKBuilder(cell1, kpts) jk_builder.exclude_dd_block = True > vj, vk = jk_builder.get_jk(dm, kpts=kpts, exxdiv=mf.exxdiv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/test/test_rsjk.py:174: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/rsjk.py:486: in get_jk vs = self._get_jk_sr(dms, hermi, kpts, kpts_band, pyscf/pbc/scf/rsjk.py:331: in _get_jk_sr sc_dm = lib.einsum('k,Sk,nkuv->nSuv', expLk[0]*weight, expLk.conj(), dm) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,Sk,nkuv->nSuv' tensors = [array([0.333333+0.j, 0.333333+0.j, 0.333333+0.j]), array([[ 1. -0.j , 1. -0.j , 1. -0.j ], [ ...0.j ]], [[0.543523-0.j , 0.618305+0.118267j], [0.618305-0.118267j, 1.03078 +0.j ]]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']), ((1, 0), 'Sk,nkuv->nSuv', ['nSuv'])] contraction = ((1, 0), 'Sk,k->Sk', ['nkuv', 'Sk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_kuhf_kernel _________________________ self = def test_kuhf_kernel(self): self.assertAlmostEqual(kmf.e_tot, -4.594854184081046, 8) e4 = super_cell(cell, [2,2,1]).KUHF().run().e_tot self.assertAlmostEqual(kmf.e_tot - e4/4, 0, 8) > kmf.analyze() pyscf/pbc/scf/test/test_uhf.py:54: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/khf.py:276: in analyze pop, chg = mf.mulliken_meta(mf.cell, dm, s=ovlp_ao, verbose=verbose) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf.py:555: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/kuhf.py:245: in mulliken_meta dm_a, dm_b = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf.py:229: in _make_rdm1_meta dm_a = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts[0], c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.433569+0.j, 0.447343+0.j, -0.012719+0.j, 0.151384+0.j], [-0.246379-0.j, 0.172058+0.j, -0.03395... 0.118117+0.j, 0.430461+0.j, 0.45103 +0.j], [-0.013708-0.j, 0.009573+0.j, -0.253994-0.j, 0.177376+0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->akq', ['kbq', 'akq']), ((1, 0), 'akq,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->akq', ['kbq', 'akq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Diamond.test_tda_singlet ___________________________ self = def test_tda_singlet(self): ref = [[10.9573977036], [11.0418311085]] > td = self.kernel(tdscf.KTDA, ref, np.arange(2)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krhf.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:66: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. -0.j , -0. -0.j , -0.328927-0.j , 0.57713 -0.j , 0.020616+0.j , 0. ... , -0.192514+0.j , 0.43123 -0.j , 0.046185-0.000017j, 0.608314+0.003976j, -0.011729-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ Diamond.test_tda_singlet_eomccs ________________________ self = def test_tda_singlet_eomccs(self): ''' Brute-force solution to the KTDA equation. Compared to the brute-force implementation of KTDA from EOM-EE-CCSD. ''' td = tdscf.KTDA(self.mf).set(kshift_lst=np.arange(len(self.mf.kpts))) ecis_k = [] for kshift in td.kshift_lst: > vind, hdiag = td.gen_vind(td._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krhf.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. -0.j , -0. -0.j , -0.328927-0.j , 0.57713 -0.j , 0.020616+0.j , 0. ... , -0.192514+0.j , 0.43123 -0.j , 0.046185-0.000017j, 0.608314+0.003976j, -0.011729-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Diamond.test_tda_triplet ___________________________ self = def test_tda_triplet(self): ref = [[6.4440137833], [7.4264899075]] > self.kernel(tdscf.KTDA, ref, np.arange(2), singlet=False) pyscf/pbc/tdscf/test/test_krhf.py:115: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:66: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. -0.j , -0. -0.j , -0.328927-0.j , 0.57713 -0.j , 0.020616+0.j , 0. ... , -0.192514+0.j , 0.43123 -0.j , 0.046185-0.000017j, 0.608314+0.003976j, -0.011729-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_tdhf_singlet ___________________________ self = def test_tdhf_singlet(self): # The first state can be obtained by solving nstates=9 #ref = [[10.60761946, 10.76654619, 10.76654619]] ref = [[10.76654619, 10.76654619]] > td = self.kernel(tdscf.KTDHF, ref, [0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krhf.py:121: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:66: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. -0.j , -0. -0.j , -0.328927-0.j , 0.57713 -0.j , 0.020616+0.j , 0. ... , -0.192514+0.j , 0.43123 -0.j , 0.046185-0.000017j, 0.608314+0.003976j, -0.011729-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_tdhf_triplet ___________________________ self = def test_tdhf_triplet(self): ref = [[5.9794378466]] > self.kernel(tdscf.KTDHF, ref, [0], singlet=False) pyscf/pbc/tdscf/test/test_krhf.py:139: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:66: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. -0.j , -0. -0.j , -0.328927-0.j , 0.57713 -0.j , 0.020616+0.j , 0. ... , -0.192514+0.j , 0.43123 -0.j , 0.046185-0.000017j, 0.608314+0.003976j, -0.011729-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ WaterBigBox.test_tda_singlet _________________________ self = def test_tda_singlet(self): > self.kernel(tdscf.KTDA, moltdscf.TDA) pyscf/pbc/tdscf/test/test_krhf.py:188: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:181: in kernel td = TD(self.mf).set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994131-0.j , -0.232768-0.j , -0. -0.j , -0.103394-0.j , -0. -0.j , -0.1... , -0.445521+0.00155j , -0.278684+0.j , -0. +0.j , -0.796143+0.j , 0.838219-0.004398j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ WaterBigBox.test_tda_triplet _________________________ self = def test_tda_triplet(self): > self.kernel(tdscf.KTDA, moltdscf.TDA, singlet=False) pyscf/pbc/tdscf/test/test_krhf.py:191: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:181: in kernel td = TD(self.mf).set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994131-0.j , -0.232768-0.j , -0. -0.j , -0.103394-0.j , -0. -0.j , -0.1... , -0.445521+0.00155j , -0.278684+0.j , -0. +0.j , -0.796143+0.j , 0.838219-0.004398j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ WaterBigBox.test_tdhf_singlet _________________________ self = def test_tdhf_singlet(self): > self.kernel(tdscf.KTDHF, moltdscf.TDHF) pyscf/pbc/tdscf/test/test_krhf.py:194: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:181: in kernel td = TD(self.mf).set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994131-0.j , -0.232768-0.j , -0. -0.j , -0.103394-0.j , -0. -0.j , -0.1... , -0.445521+0.00155j , -0.278684+0.j , -0. +0.j , -0.796143+0.j , 0.838219-0.004398j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ WaterBigBox.test_tdhf_triplet _________________________ self = def test_tdhf_triplet(self): > self.kernel(tdscf.KTDHF, moltdscf.TDHF, singlet=False) pyscf/pbc/tdscf/test/test_krhf.py:197: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krhf.py:181: in kernel td = TD(self.mf).set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994131-0.j , -0.232768-0.j , -0. -0.j , -0.103394-0.j , -0. -0.j , -0.1... , -0.445521+0.00155j , -0.278684+0.j , -0. +0.j , -0.796143+0.j , 0.838219-0.004398j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE.test_tda_singlet __________________________ self = def test_tda_singlet(self): ref = [[7.7172857896, 7.7173222336]] > td = self.kernel('TDA', ref) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krks.py:86: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:79: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:33: in kernel return krhf.TDA.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.080548+0.j, -0. -0.j, -0.000013-0.j, 0.659381+0.j, -0. +0.j, 0. +0.j, -0.025677+0.j, -0.7...385988-0.j, 0. +0.j, -0.549786-0.j, 0.047141-0.j, 0. -0.j, 0.610112-0.j, -0.431092+0.j, 0.014607+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE.test_tda_triplet __________________________ self = def test_tda_triplet(self): ref = [[5.7465112548, 5.7465526327]] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_krks.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:79: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:33: in kernel return krhf.TDA.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.080548+0.j, -0. -0.j, -0.000013-0.j, 0.659381+0.j, -0. +0.j, 0. +0.j, -0.025677+0.j, -0.7...385988-0.j, 0. +0.j, -0.549786-0.j, 0.047141-0.j, 0. -0.j, 0.610112-0.j, -0.431092+0.j, 0.014607+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE.test_tdhf_singlet _________________________ self = def test_tdhf_singlet(self): ref = [[7.58243026, 7.58246786]] > td = self.kernel('TDDFT', ref) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krks.py:98: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:79: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:42: in kernel return krhf.TDHF.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.080548+0.j, -0. -0.j, -0.000013-0.j, 0.659381+0.j, -0. +0.j, 0. +0.j, -0.025677+0.j, -0.7...385988-0.j, 0. +0.j, -0.549786-0.j, 0.047141-0.j, 0. -0.j, 0.610112-0.j, -0.431092+0.j, 0.014607+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE.test_tdhf_triplet _________________________ self = def test_tdhf_triplet(self): ref = [[5.56599665, 5.56603980]] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_krks.py:105: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:79: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:42: in kernel return krhf.TDHF.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.080548+0.j, -0. -0.j, -0.000013-0.j, 0.659381+0.j, -0. +0.j, 0. +0.j, -0.025677+0.j, -0.7...385988-0.j, 0. +0.j, -0.549786-0.j, 0.047141-0.j, 0. -0.j, 0.610112-0.j, -0.431092+0.j, 0.014607+0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE0.test_tda_singlet _________________________ self = def test_tda_singlet(self): ref = [[9.3936718451, 9.4874866060]] > td = self.kernel('TDA', ref) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krks.py:154: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:147: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:33: in kernel return krhf.TDA.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. +0.j , 0.000006-0.j , 0.044998-0.j , 0.662757-0.j , 0.022666+0.j , 0. ... , 0.026334+0.j , 0.431226-0.j , 0. -0.j , 0.610056+0.j , 0.012894+0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE0.test_tda_triplet _________________________ self = def test_tda_triplet(self): ref = [[6.6703797643, 6.6704110631]] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_krks.py:162: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:147: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:33: in kernel return krhf.TDA.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:337: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:257: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. +0.j , 0.000006-0.j , 0.044998-0.j , 0.662757-0.j , 0.022666+0.j , 0. ... , 0.026334+0.j , 0.431226-0.j , 0. -0.j , 0.610056+0.j , 0.012894+0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ DiamondPBE0.test_tdhf_singlet _________________________ self = def test_tdhf_singlet(self): ref = [[9.25192096, 9.32080304]] > td = self.kernel('TDDFT', ref, conv_tol=1e-6) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_krks.py:166: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:147: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:42: in kernel return krhf.TDHF.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. +0.j , 0.000006-0.j , 0.044998-0.j , 0.662757-0.j , 0.022666+0.j , 0. ... , 0.026334+0.j , 0.431226-0.j , 0. -0.j , 0.610056+0.j , 0.012894+0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ DiamondPBE0.test_tdhf_triplet _________________________ self = def test_tdhf_triplet(self): ref = [[6.3282716764, 6.3283051217]] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_krks.py:173: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_krks.py:147: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/krks.py:42: in kernel return krhf.TDHF.kernel(self, x0=x0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:490: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/krhf.py:385: in gen_vind e_ia = _get_e_ia(scf.addons.mo_energy_with_exxdiv_none(mf), mo_occ, kconserv) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:538: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. +0.j , 0.000006-0.j , 0.044998-0.j , 0.662757-0.j , 0.022666+0.j , 0. ... , 0.026334+0.j , 0.431226-0.j , 0. -0.j , 0.610056+0.j , 0.012894+0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ WaterBigBox.test_tda _____________________________ self = def test_tda(self): > self.kernel(tdscf.KTDA, moltdscf.TDA) pyscf/pbc/tdscf/test/test_kuhf.py:176: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_kuhf.py:168: in kernel td = TD(self.mf).set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/kuhf.py:345: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/kuhf.py:260: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:540: in mo_energy_with_exxdiv_none return [_get_moek(kC, kfao) for kC,kfao in zip(mo_coeff,fockao)] ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993976-0.j , -0.247548-0.j , 0. -0.j , -0. -0.j , -0.079161-0.j , -0.1... , -0.406008-0.008404j, -0. -0.j , -0.17891 -0.j , -0.835677+0.j , 0.857958+0.010791j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ WaterBigBox.test_tdhf _____________________________ self = def test_tdhf(self): > self.kernel(tdscf.KTDHF, moltdscf.TDHF) pyscf/pbc/tdscf/test/test_kuhf.py:179: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_kuhf.py:168: in kernel td = TD(self.mf).set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/kuhf.py:484: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/kuhf.py:392: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:540: in mo_energy_with_exxdiv_none return [_get_moek(kC, kfao) for kC,kfao in zip(mo_coeff,fockao)] ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993976-0.j , -0.247548-0.j , 0. -0.j , -0. -0.j , -0.079161-0.j , -0.1... , -0.406008-0.008404j, -0. -0.j , -0.17891 -0.j , -0.835677+0.j , 0.857958+0.010791j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ DiamondPBE.test_tda ______________________________ self = def test_tda(self): # same as lowest roots in DiamondPBE->test_tda_singlet/triplet in test_krks.py ref = [[5.7465112548, 5.7465526327]] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_kuks.py:68: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_kuks.py:61: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/kuks.py:27: in kernel kuhf.TDA.kernel(self, x0=x0) pyscf/pbc/tdscf/kuhf.py:345: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/kuhf.py:260: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:540: in mo_energy_with_exxdiv_none return [_get_moek(kC, kfao) for kC,kfao in zip(mo_coeff,fockao)] ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.080547+0.j, 0.00001 -0.j, -0. -0.j, 0.659381+0.j, 0.000001+0.j, 0. -0.j, 0.025676-0.j, 0.7...38587 -0.j, -0.549866+0.j, -0. -0.j, 0.047144-0.j, 0.610047+0.j, 0. -0.j, 0.431187-0.j, -0.014608-0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ DiamondPBE.test_tdhf _____________________________ self = def test_tdhf(self): # same as lowest roots in DiamondPBE->test_tdhf_singlet/triplet in test_krks.py ref = [[5.56602, 5.56602]] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_kuks.py:73: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_kuks.py:61: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/kuks.py:34: in kernel kuhf.TDHF.kernel(self, x0=x0) pyscf/pbc/tdscf/kuhf.py:484: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/kuhf.py:392: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:540: in mo_energy_with_exxdiv_none return [_get_moek(kC, kfao) for kC,kfao in zip(mo_coeff,fockao)] ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.080547+0.j, 0.00001 -0.j, -0. -0.j, 0.659381+0.j, 0.000001+0.j, 0. -0.j, 0.025676-0.j, 0.7...38587 -0.j, -0.549866+0.j, -0. -0.j, 0.047144-0.j, 0.610047+0.j, 0. -0.j, 0.431187-0.j, -0.014608-0.j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ DiamondPBE0.test_tda _____________________________ self = def test_tda(self): # same as lowest roots in DiamondPBE0->test_tda_singlet/triplet in test_krks.py ref = [[6.6703797643, 6.6704110631]] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_kuks.py:119: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_kuks.py:112: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/kuks.py:27: in kernel kuhf.TDA.kernel(self, x0=x0) pyscf/pbc/tdscf/kuhf.py:345: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/kuhf.py:260: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:540: in mo_energy_with_exxdiv_none return [_get_moek(kC, kfao) for kC,kfao in zip(mo_coeff,fockao)] ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.000003+0.j , 0. -0.j , 0.044996-0.j , 0.662757-0.j , -0.022665-0.j , 0.0... , 0.026337+0.j , -0.431172+0.j , 0.610096-0.j , 0. -0.j , -0.012895-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ DiamondPBE0.test_tdhf _____________________________ self = def test_tdhf(self): # same as lowest roots in DiamondPBE0->test_tdhf_singlet/triplet in test_krks.py ref = [[6.3282716764, 6.3283051217]] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_kuks.py:124: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_kuks.py:112: in kernel nstates=self.nstates, **kwargs).run() ^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/pbc/tdscf/kuks.py:34: in kernel kuhf.TDHF.kernel(self, x0=x0) pyscf/pbc/tdscf/kuhf.py:484: in kernel vind, hdiag = self.gen_vind(self._scf, kshift) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/kuhf.py:392: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:540: in mo_energy_with_exxdiv_none return [_get_moek(kC, kfao) for kC,kfao in zip(mo_coeff,fockao)] ^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.000003+0.j , 0. -0.j , 0.044996-0.j , 0.662757-0.j , -0.022665-0.j , 0.0... , 0.026337+0.j , -0.431172+0.j , 0.610096-0.j , 0. -0.j , -0.012895-0.j ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Diamond.test_tda_singlet ___________________________ self = def test_tda_singlet(self): ref = [9.6425852906, 9.6425852906] > self.kernel('TDA', ref) pyscf/pbc/tdscf/test/test_rhf.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:55: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , -0. , 0.664283, 0. , 0. , 0. , 0.758279], [ 0.365094, -....509789, -0. ], [-0.441257, -0.507806, 0.029981, -0. , 0.682563, 0.051008, 0.299663, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Diamond.test_tda_triplet ___________________________ self = def test_tda_triplet(self): ref = [4.7209460258, 5.6500725912] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_rhf.py:65: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:55: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , -0. , 0.664283, 0. , 0. , 0. , 0.758279], [ 0.365094, -....509789, -0. ], [-0.441257, -0.507806, 0.029981, -0. , 0.682563, 0.051008, 0.299663, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_tdhf_singlet ___________________________ self = def test_tdhf_singlet(self): ref = [9.2573219105, 9.2573219106] > td = self.kernel('TDHF', ref) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_rhf.py:69: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:55: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , -0. , 0.664283, 0. , 0. , 0. , 0.758279], [ 0.365094, -....509789, -0. ], [-0.441257, -0.507806, 0.029981, -0. , 0.682563, 0.051008, 0.299663, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_tdhf_triplet ___________________________ self = def test_tdhf_triplet(self): ref = [3.0396052214, 3.0396052214] > self.kernel('TDHF', ref, singlet=False) pyscf/pbc/tdscf/test/test_rhf.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:55: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , -0. , 0.664283, 0. , 0. , 0. , 0.758279], [ 0.365094, -....509789, -0. ], [-0.441257, -0.507806, 0.029981, -0. , 0.682563, 0.051008, 0.299663, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ DiamondShifted.test_tda_singlet ________________________ self = def test_tda_singlet(self): ref = [12.7166510188, 13.5460934688] > self.kernel('TDA', ref) pyscf/pbc/tdscf/test/test_rhf.py:123: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:117: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.220163-0.002964j, 0.054296-0.000911j, -0.09164 +0.000531j, 0.51572 -0.001694j, -0.121136+0.000804j, -0.0...1j, 0.06551 +0.281775j, 0.091815-0.132469j, 0.578177+0.206705j, 0.120365-0.349436j, 0.057279-0.051775j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ DiamondShifted.test_tda_triplet ________________________ self = def test_tda_triplet(self): ref = [8.7359078688, 9.2565904604] > self.kernel('TDA' , ref, singlet=False) pyscf/pbc/tdscf/test/test_rhf.py:127: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:117: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.220163-0.002964j, 0.054296-0.000911j, -0.09164 +0.000531j, 0.51572 -0.001694j, -0.121136+0.000804j, -0.0...1j, 0.06551 +0.281775j, 0.091815-0.132469j, 0.578177+0.206705j, 0.120365-0.349436j, 0.057279-0.051775j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ DiamondShifted.test_tdhf_singlet _______________________ self = def test_tdhf_singlet(self): ref = [12.6104811733, 13.4160717812] > td = self.kernel('TDHF', ref) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_rhf.py:131: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:117: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.220163-0.002964j, 0.054296-0.000911j, -0.09164 +0.000531j, 0.51572 -0.001694j, -0.121136+0.000804j, -0.0...1j, 0.06551 +0.281775j, 0.091815-0.132469j, 0.578177+0.206705j, 0.120365-0.349436j, 0.057279-0.051775j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ DiamondShifted.test_tdhf_triplet _______________________ self = def test_tdhf_triplet(self): ref = [3.8940277713, 7.9448161493] > self.kernel('TDHF', ref, singlet=False) pyscf/pbc/tdscf/test/test_rhf.py:143: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:117: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.220163-0.002964j, 0.054296-0.000911j, -0.09164 +0.000531j, 0.51572 -0.001694j, -0.121136+0.000804j, -0.0...1j, 0.06551 +0.281775j, 0.091815-0.132469j, 0.578177+0.206705j, 0.120365-0.349436j, 0.057279-0.051775j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ WaterBigBox.test_tda_singlet _________________________ self = def test_tda_singlet(self): > self.kernel('TDA') pyscf/pbc/tdscf/test/test_rhf.py:193: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:187: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994132, -0.232761, -0. , -0.103403, 0. , -0.132148, 0. ], [ 0.026546, 0.833517, .... , -0.796136, -0.838227], [-0.005965, 0.158745, -0.445531, -0.278687, 0. , -0.796136, 0.838227]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ WaterBigBox.test_tda_triplet _________________________ self = def test_tda_triplet(self): > self.kernel('TDA', singlet=False) pyscf/pbc/tdscf/test/test_rhf.py:196: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:187: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994132, -0.232761, -0. , -0.103403, 0. , -0.132148, 0. ], [ 0.026546, 0.833517, .... , -0.796136, -0.838227], [-0.005965, 0.158745, -0.445531, -0.278687, 0. , -0.796136, 0.838227]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ WaterBigBox.test_tdhf_singlet _________________________ self = def test_tdhf_singlet(self): > self.kernel('TDHF') pyscf/pbc/tdscf/test/test_rhf.py:199: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:187: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994132, -0.232761, -0. , -0.103403, 0. , -0.132148, 0. ], [ 0.026546, 0.833517, .... , -0.796136, -0.838227], [-0.005965, 0.158745, -0.445531, -0.278687, 0. , -0.796136, 0.838227]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ WaterBigBox.test_tdhf_triplet _________________________ self = def test_tdhf_triplet(self): > self.kernel('TDHF', singlet=False) pyscf/pbc/tdscf/test/test_rhf.py:202: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rhf.py:187: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.994132, -0.232761, -0. , -0.103403, 0. , -0.132148, 0. ], [ 0.026546, 0.833517, .... , -0.796136, -0.838227], [-0.005965, 0.158745, -0.445531, -0.278687, 0. , -0.796136, 0.838227]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_camb3lyp_tda ___________________________ self = def test_camb3lyp_tda(self): > self.check_rsh_tda('camb3lyp') pyscf/pbc/tdscf/test/test_rks.py:110: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:103: in check_rsh_tda td = mf.TDA().run(nstates=5, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , -0. , 0.664283, 0. , -0. , 0. , -0.758279], [-0.012226, ....699641, 0. ], [-0.05457 , 0.603842, 0.293036, 0. , 0.640558, -0.342567, -0.174999, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ Diamond.test_hse06_tda ____________________________ self = def test_hse06_tda(self): # reducing tol, as larger numerical uncertainties found in fxc when using libxc-7 > self.check_rsh_tda('hse06', place=3) pyscf/pbc/tdscf/test/test_rks.py:121: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:103: in check_rsh_tda td = mf.TDA().run(nstates=5, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0.000001, -0.000001, 0.664279, 0.000001, -0.000002, -0.000001, 0.758282], [ 0.464873, ....531661, 0. ], [-0.094875, 0.654823, 0.125237, 0.000002, -0.159733, 0.724307, 0.090275, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Diamond.test_tda_singlet ___________________________ self = def test_tda_singlet(self): ref = [14.68587442, 14.68589929] > td = self.kernel('TDA', ref) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_rks.py:79: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:73: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664279, 0. , -0. , 0. , 0.758282], [ 0.367301, ....552734, -0. ], [ 0.53799 , -0.11352 , 0.388792, -0.000002, 0.431388, 0.607789, -0.052747, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ Diamond.test_tda_triplet ___________________________ self = def test_tda_triplet(self): ref = [11.10049832, 11.59365532] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_rks.py:87: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:73: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664279, 0. , -0. , 0. , 0.758282], [ 0.367301, ....552734, -0. ], [ 0.53799 , -0.11352 , 0.388792, -0.000002, 0.431388, 0.607789, -0.052747, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_tddft_singlet __________________________ self = def test_tddft_singlet(self): ref = [14.42819773, 14.42822009] > td = self.kernel('TDDFT', ref) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_rks.py:91: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:73: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664279, 0. , -0. , 0. , 0.758282], [ 0.367301, ....552734, -0. ], [ 0.53799 , -0.11352 , 0.388792, -0.000002, 0.431388, 0.607789, -0.052747, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ Diamond.test_tddft_triplet __________________________ self = def test_tddft_triplet(self): ref = [ 9.09496456, 11.53650896] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_rks.py:98: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:73: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664279, 0. , -0. , 0. , 0.758282], [ 0.367301, ....552734, -0. ], [ 0.53799 , -0.11352 , 0.388792, -0.000002, 0.431388, 0.607789, -0.052747, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ Diamond.test_wb97_tda _____________________________ self = def test_wb97_tda(self): > self.check_rsh_tda('wb97') pyscf/pbc/tdscf/test/test_rks.py:113: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:103: in check_rsh_tda td = mf.TDA().run(nstates=5, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , 0. , 0.664264, 0. , -0. , 0. , 0.758296], [ 0.012964, -....731461, -0. ], [ 0.051745, -0.595773, -0.309577, 0. , 0.592131, -0.444735, -0.09947 , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ DiamondPBEShifted.test_tda_singlet ______________________ self = def test_tda_singlet(self): ref = [11.9664870288, 12.7605699008] > self.kernel('TDA', ref) pyscf/pbc/tdscf/test/test_rks.py:168: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:163: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.174906-0.002151j, -0.044347+0.000312j, -0.101352-0.000312j, 0.507042-0.001839j, -0.102313+0.001285j, -0.0...5j, 0.047552+0.257305j, 0.066907-0.158333j, 0.608934+0.144543j, 0.123697-0.314688j, 0.040709-0.064719j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ DiamondPBEShifted.test_tda_triplet ______________________ self = def test_tda_triplet(self): ref = [8.5705015296, 9.3030273411] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_rks.py:172: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:163: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.174906-0.002151j, -0.044347+0.000312j, -0.101352-0.000312j, 0.507042-0.001839j, -0.102313+0.001285j, -0.0...5j, 0.047552+0.257305j, 0.066907-0.158333j, 0.608934+0.144543j, 0.123697-0.314688j, 0.040709-0.064719j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ DiamondPBEShifted.test_tddft_singlet _____________________ self = def test_tddft_singlet(self): ref = [11.8322851619, 12.6207316217] > self.kernel('TDDFT', ref) pyscf/pbc/tdscf/test/test_rks.py:176: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:163: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.174906-0.002151j, -0.044347+0.000312j, -0.101352-0.000312j, 0.507042-0.001839j, -0.102313+0.001285j, -0.0...5j, 0.047552+0.257305j, 0.066907-0.158333j, 0.608934+0.144543j, 0.123697-0.314688j, 0.040709-0.064719j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ DiamondPBEShifted.test_tddft_triplet _____________________ self = def test_tddft_triplet(self): ref = [8.4227532516, 9.1695913993] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_rks.py:180: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:163: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.174906-0.002151j, -0.044347+0.000312j, -0.101352-0.000312j, 0.507042-0.001839j, -0.102313+0.001285j, -0.0...5j, 0.047552+0.257305j, 0.066907-0.158333j, 0.608934+0.144543j, 0.123697-0.314688j, 0.040709-0.064719j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ WaterBigBoxPBE.test_tda_singlet ________________________ self = def test_tda_singlet(self): > self.kernel('TDA') pyscf/pbc/tdscf/test/test_rks.py:237: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:230: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993236, -0.22512 , -0. , -0.128785, 0. , -0.129798, -0. ], [ 0.030728, 0.786464, .... , -0.792607, -0.839175], [-0.007491, 0.177689, -0.443743, -0.27727 , 0. , -0.792607, 0.839175]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ WaterBigBoxPBE.test_tda_triplet ________________________ self = def test_tda_triplet(self): > self.kernel('TDA', singlet=False) pyscf/pbc/tdscf/test/test_rks.py:240: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:230: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993236, -0.22512 , -0. , -0.128785, 0. , -0.129798, -0. ], [ 0.030728, 0.786464, .... , -0.792607, -0.839175], [-0.007491, 0.177689, -0.443743, -0.27727 , 0. , -0.792607, 0.839175]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ WaterBigBoxPBE.test_tddft_singlet _______________________ self = def test_tddft_singlet(self): > self.kernel('TDDFT') pyscf/pbc/tdscf/test/test_rks.py:243: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:230: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rks.py:123: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993236, -0.22512 , -0. , -0.128785, 0. , -0.129798, -0. ], [ 0.030728, 0.786464, .... , -0.792607, -0.839175], [-0.007491, 0.177689, -0.443743, -0.27727 , 0. , -0.792607, 0.839175]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ WaterBigBoxPBE.test_tddft_triplet _______________________ self = def test_tddft_triplet(self): > self.kernel('TDDFT', singlet=False) pyscf/pbc/tdscf/test/test_rks.py:246: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:230: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rks.py:123: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993236, -0.22512 , -0. , -0.128785, 0. , -0.129798, -0. ], [ 0.030728, 0.786464, .... , -0.792607, -0.839175], [-0.007491, 0.177689, -0.443743, -0.27727 , 0. , -0.792607, 0.839175]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE0.test_tda_singlet _________________________ self = def test_tda_singlet(self): ref = [9.62238067, 9.62238067] > td = self.kernel('TDA', ref) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_rks.py:292: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:286: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664276, -0. , 0. , -0.000001, 0.758285], [ 0.331431, ....431386, 0.000001], [ 0.545659, -0.067679, 0.388795, -0.000001, 0.606801, -0.063068, 0.431385, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondPBE0.test_tda_triplet _________________________ self = def test_tda_triplet(self): ref = [5.39995144, 5.39995144] > self.kernel('TDA', ref, singlet=False) pyscf/pbc/tdscf/test/test_rks.py:300: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:286: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664276, -0. , 0. , -0.000001, 0.758285], [ 0.331431, ....431386, 0.000001], [ 0.545659, -0.067679, 0.388795, -0.000001, 0.606801, -0.063068, 0.431385, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ DiamondPBE0.test_tddft_singlet ________________________ self = def test_tddft_singlet(self): ref = [9.26011401, 9.26011401] > td = self.kernel('TDDFT', ref) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_rks.py:304: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:286: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664276, -0. , 0. , -0.000001, 0.758285], [ 0.331431, ....431386, 0.000001], [ 0.545659, -0.067679, 0.388795, -0.000001, 0.606801, -0.063068, 0.431385, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ DiamondPBE0.test_tddft_triplet ________________________ self = def test_tddft_triplet(self): ref = [4.68905023, 4.81439580] > self.kernel('TDDFT', ref, singlet=False) pyscf/pbc/tdscf/test/test_rks.py:311: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:286: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664276, -0. , 0. , -0.000001, 0.758285], [ 0.331431, ....431386, 0.000001], [ 0.545659, -0.067679, 0.388795, -0.000001, 0.606801, -0.063068, 0.431385, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ WaterBigBoxPBE0.test_tda_singlet _______________________ self = def test_tda_singlet(self): > self.kernel('TDA') pyscf/pbc/tdscf/test/test_rks.py:368: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:361: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993473, -0.227675, -0. , -0.121503, 0. , -0.130551, -0. ], [ 0.029626, 0.801295, .... , -0.79417 , -0.839669], [-0.007085, 0.17173 , -0.442806, -0.276562, 0. , -0.79417 , 0.839669]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ WaterBigBoxPBE0.test_tda_triplet _______________________ self = def test_tda_triplet(self): > self.kernel('TDA', singlet=False) pyscf/pbc/tdscf/test/test_rks.py:371: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:361: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:955: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993473, -0.227675, -0. , -0.121503, 0. , -0.130551, -0. ], [ 0.029626, 0.801295, .... , -0.79417 , -0.839669], [-0.007085, 0.17173 , -0.442806, -0.276562, 0. , -0.79417 , 0.839669]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ WaterBigBoxPBE0.test_tddft_singlet ______________________ self = def test_tddft_singlet(self): > self.kernel('TDDFT') pyscf/pbc/tdscf/test/test_rks.py:374: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:361: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993473, -0.227675, -0. , -0.121503, 0. , -0.130551, -0. ], [ 0.029626, 0.801295, .... , -0.79417 , -0.839669], [-0.007085, 0.17173 , -0.442806, -0.276562, 0. , -0.79417 , 0.839669]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ WaterBigBoxPBE0.test_tddft_triplet ______________________ self = def test_tddft_triplet(self): > self.kernel('TDDFT', singlet=False) pyscf/pbc/tdscf/test/test_rks.py:377: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_rks.py:361: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1142: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:534: in mo_energy_with_exxdiv_none return _get_moe1(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993473, -0.227675, -0. , -0.121503, 0. , -0.130551, -0. ], [ 0.029626, 0.801295, .... , -0.79417 , -0.839669], [-0.007085, 0.17173 , -0.442806, -0.276562, 0. , -0.79417 , 0.839669]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________________ Diamond.test_tda _______________________________ self = def test_tda(self): # same as lowest roots in test_rhf/Diamond -> test_tda_singlet/triplet ref = [4.7209460258, 5.6500725912] > self.kernel('TDA', ref) pyscf/pbc/tdscf/test/test_uhf.py:61: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uhf.py:55: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , 0. , 0.664283, 0. , 0. , 0. , 0.758279], [ 0.366757, -....5046 , -0. ], [-0.43958 , -0.507839, 0.04839 , -0. , 0.678583, 0.046045, 0.309349, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________________ Diamond.test_tdhf _______________________________ self = def test_tdhf(self): # same as lowest roots in test_rhf/Diamond -> test_tdhf_singlet/triplet ref = [3.0396052214, 3.0396052214] > self.kernel('TDHF', ref) pyscf/pbc/tdscf/test/test_uhf.py:66: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uhf.py:55: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:930: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , 0. , 0.664283, 0. , 0. , 0. , 0.758279], [ 0.366757, -....5046 , -0. ], [-0.43958 , -0.507839, 0.04839 , -0. , 0.678583, 0.046045, 0.309349, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ WaterBigBox.test_tda _____________________________ self = def test_tda(self): > self.kernel('TDA') pyscf/pbc/tdscf/test/test_uhf.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uhf.py:111: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993977, -0.247542, 0. , -0. , -0.079171, -0.122865, 0. ], [ 0.027182, 0.926439, -....178934, -0.83567 , -0.858016], [-0.006027, 0.079604, -0.406117, -0. , -0.178934, -0.83567 , 0.858016]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ WaterBigBox.test_tdhf _____________________________ self = def test_tdhf(self): > self.kernel('TDHF') pyscf/pbc/tdscf/test/test_uhf.py:120: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uhf.py:111: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:930: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993977, -0.247542, 0. , -0. , -0.079171, -0.122865, 0. ], [ 0.027182, 0.926439, -....178934, -0.83567 , -0.858016], [-0.006027, 0.079604, -0.406117, -0. , -0.178934, -0.83567 , 0.858016]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ DiamondM06.test_camb3lyp_tda _________________________ self = def test_camb3lyp_tda(self): > self.check_rsh_tda('camb3lyp') pyscf/pbc/tdscf/test/test_uks.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:110: in check_rsh_tda td = mf.TDA().run(nstates=3, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , -0. , 0.664283, 0. , 0. , 0. , -0.758279], [-0.012673, ....691184, 0. ], [-0.055341, 0.4979 , 0.450006, 0. , 0.474532, 0.520915, -0.248513, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ DiamondM06.test_hse03_tda ___________________________ self = def test_hse03_tda(self): > self.check_rsh_tda('hse03') pyscf/pbc/tdscf/test/test_uks.py:123: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:110: in check_rsh_tda td = mf.TDA().run(nstates=3, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0.000002, -0.000001, 0.000002, 0.664281, -0.000002, -0.000001, -0.000009, 0.758281], [-0.358753, ....116344, 0. ], [ 0.187233, 0.52403 , -0.379225, 0.000008, -0.149227, 0.475849, 0.556406, 0.000002]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ DiamondM06.test_tda ______________________________ self = def test_tda(self): ref = [11.09731427, 11.57079413] > td = self.kernel('TDA', ref) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_uks.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:88: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664279, 0. , -0. , 0. , 0.758282], [ 0.243009, -....501042, -0. ], [ 0.548646, -0.036154, 0.388792, -0.000002, 0.431388, 0.607946, -0.050908, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ DiamondM06.test_tdhf _____________________________ self = def test_tdhf(self): ref = [9.09165361, 11.51362009] > td = self.kernel('TDDFT', ref, conv_tol=1e-8) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_uks.py:102: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:88: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:930: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664279, 0. , -0. , 0. , 0.758282], [ 0.243009, -....501042, -0. ], [ 0.548646, -0.036154, 0.388792, -0.000002, 0.431388, 0.607946, -0.050908, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ DiamondM06.test_wb97_tda ___________________________ self = def test_wb97_tda(self): > self.check_rsh_tda('wb97') pyscf/pbc/tdscf/test/test_uks.py:120: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:110: in check_rsh_tda td = mf.TDA().run(nstates=3, conv_tol=1e-7) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[-0. , 0. , 0. , 0.664264, 0. , 0. , 0. , 0.758296], [ 0.009032, -....723411, -0. ], [ 0.051801, -0.513985, -0.431969, 0. , 0.504768, 0.533561, -0.137206, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ WaterBigBoxPBE.test_tda ____________________________ self = def test_tda(self): > self.kernel('TDA') pyscf/pbc/tdscf/test/test_uks.py:180: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:174: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993154, -0.24162 , 0. , -0.096337, 0. , -0.1289 , 0. ], [ 0.03102 , 0.87515 , -.... , -0.814543, -0.872976], [-0.007426, 0.122896, -0.372874, -0.24103 , 0. , -0.814543, 0.872976]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ WaterBigBoxPBE.test_tdhf ___________________________ self = def test_tdhf(self): > self.kernel('TDDFT') pyscf/pbc/tdscf/test/test_uks.py:183: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:174: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uks.py:136: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993154, -0.24162 , 0. , -0.096337, 0. , -0.1289 , 0. ], [ 0.03102 , 0.87515 , -.... , -0.814543, -0.872976], [-0.007426, 0.122896, -0.372874, -0.24103 , 0. , -0.814543, 0.872976]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ DiamondPBE0.test_tda _____________________________ self = def test_tda(self): ref = [5.37745381, 5.37745449] > td = self.kernel('TDA', ref) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_uks.py:231: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:225: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664276, -0. , 0. , -0.000001, 0.758285], [ 0.310872, ....431386, 0.000001], [ 0.548198, -0.042473, 0.388795, -0.000001, 0.609106, -0.034278, 0.431386, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ DiamondPBE0.test_tdhf _____________________________ self = def test_tdhf(self): # nstates=6 is required to derive the lowest state ref = [4.6851639, 4.79043398, 4.79043398] > td = self.kernel('TDDFT', ref[1:3]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/test/test_uks.py:240: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:225: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:930: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0. , -0. , 0.000003, 0.664276, -0. , 0. , -0.000001, 0.758285], [ 0.310872, ....431386, 0.000001], [ 0.548198, -0.042473, 0.388795, -0.000001, 0.609106, -0.034278, 0.431386, 0.000001]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ WaterBigBoxPBE0.test_tda ___________________________ self = def test_tda(self): > self.kernel('TDA') pyscf/pbc/tdscf/test/test_uks.py:300: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:294: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:750: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993372, -0.243777, 0. , -0.090737, 0. , -0.127212, -0. ], [ 0.030004, 0.892004, -.... , -0.821705, -0.870426], [-0.00705 , 0.109067, -0.378789, -0.22269 , 0. , -0.821705, 0.870426]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ WaterBigBoxPBE0.test_tdhf ___________________________ self = def test_tdhf(self): > self.kernel('TDDFT') pyscf/pbc/tdscf/test/test_uks.py:303: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/tdscf/test/test_uks.py:294: in kernel td = getattr(self.mf, TD)().set(nstates=self.nstates, **kwargs).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:930: in kernel vind, hdiag = self.gen_vind(self._scf) ^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/tdscf/rhf.py:173: in gen_vind moe = scf.addons.mo_energy_with_exxdiv_none(mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:536: in mo_energy_with_exxdiv_none return _get_moek(mo_coeff, fockao) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:530: in _get_moek return [_get_moe1(C, fao) for C,fao in zip(kC, kfao)] ^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/addons.py:528: in _get_moe1 return lib.einsum('pi,pq,qi->i', C.conj(), fao, C).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qi->i' tensors = [array([[ 0.993372, -0.243777, 0. , -0.090737, 0. , -0.127212, -0. ], [ 0.030004, 0.892004, -.... , -0.821705, -0.870426], [-0.00705 , 0.109067, -0.378789, -0.22269 , 0. , -0.821705, 0.870426]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qi', 'iq']), ((1, 0), 'iq,qi->i', ['i'])] contraction = ((1, 0), 'pq,pi->iq', ['qi', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_k2gamma ___________________________ self = def test_k2gamma(self): cell = gto.Cell() cell.a = ''' 1.755000 1.755000 -1.755000 1.755000 -1.755000 1.755000 -1.755000 1.755000 1.755000''' cell.atom = '''Li 0.00000 0.00000 0.00000''' cell.basis = 'gth-szv' cell.pseudo = {'Li': 'GTH-PBE-q3'} cell.mesh = [20]*3 cell.verbose = 6 cell.output = '/dev/null' cell.build() kpts = cell.make_kpts([2,2,2]) mf = scf.KUKS(cell, kpts) mf.xc = 'lda,vwn' mf.kernel() > popa, popb = mf.mulliken_meta()[0] ^^^^^^^^^^^^^^^^^^ pyscf/pbc/tools/test/test_k2gamma.py:69: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/pbc/scf/kuhf.py:555: in mulliken_meta return mulliken_meta(cell, dm, kpts, s=s, verbose=verbose, pyscf/pbc/scf/kuhf.py:245: in mulliken_meta dm_a, dm_b = _make_rdm1_meta(cell, dm_ao_kpts, kpts, pre_orth_method, s) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/kuhf.py:229: in _make_rdm1_meta dm_a = lib.einsum('kap,kpq,kbq->ab', c_inv, dm_ao_kpts[0], c_inv.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kap,kpq,kbq->ab' tensors = [array([[[ 0.350562+0.j, 0.183976+0.j], [ 0.035302+0.j, 1.335354+0.j]], [[ 0.353686-0.j, -0.034018-0... [ 0.003679-0.j, 0.139179-0.j]], [[ 0.352625+0.j, -0.065448-0.j], [ 0.001 +0.j, 0.037842-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kpq,kap->aqk', ['kbq', 'aqk']), ((1, 0), 'aqk,kbq->ab', ['ab'])] contraction = ((1, 0), 'kpq,kap->aqk', ['kbq', 'aqk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_k2gamma_ksymm ________________________ self = def test_k2gamma_ksymm(self): cell = gto.Cell() cell.atom = ''' He 0. 0. 0. ''' cell.basis = {'He': [[0, (4.0, 1.0)], [0, (1.0, 1.0)]]} cell.a = np.eye(3) * 2. cell.space_group_symmetry = True cell.build() kmesh = [2,2,1] kpts = cell.make_kpts(kmesh, space_group_symmetry=True) kmf = scf.KRKS(cell, kpts).density_fit() > kmf.kernel() pyscf/pbc/tools/test/test_k2gamma.py:90: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:123: in kernel dm = mf.get_init_guess(mol, mf.init_guess, s1e=s1e, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/pbc/scf/khf_ksymm.py:371: in get_init_guess ne = lib.einsum('k,kij,kji', self.kpts.weights_ibz, dm_kpts, s1e).real ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'k,kij,kji' tensors = [array([0.25, 0.5 , 0.25]), NPArrayWithTag([[[0.008222, 0.116766], [0.116766, 1.658217]], ... [0.715557-0.j, 1.00158 -0.j]], [[1. -0.j, 0.715526+0.j], [0.715526+0.j, 0.998415-0.j]]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1), 'kji,kij->k', ['k', 'k']), ((1, 0), 'k,k->', [''])] contraction = ((2, 1), 'kji,kij->k', ['k', 'k']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rks_pbe0 ___________________________ self = def test_rks_pbe0(self): > e_tot, g_qm, g_mm = run_dft('PBE0') ^^^^^^^^^^^^^^^ pyscf/qmmm/pbc/test/test_qmmm.py:64: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/qmmm/pbc/test/test_qmmm.py:53: in run_dft e_dft = mf.kernel() ^^^^^^^^^^^ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:128: in kernel vhf = mf.get_veff(mol, dm) ^^^^^^^^^^^^^^^^^^^^ pyscf/qmmm/pbc/itrf.py:334: in get_veff mm_ewald_pot = self.get_mm_ewald_pot(mol, mm_mol) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/qmmm/pbc/itrf.py:139: in get_mm_ewald_pot return self.mm_mol.get_ewald_pot( pyscf/qmmm/pbc/mm_mole.py:217: in get_ewald_pot Tijab = 3 * lib.einsum('ija,ijb,ij->ijab', R_, R_, 1/r_**2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ija,ijb,ij->ijab' tensors = [array([[[ -5.669178, -7.558904, -9.226777]], [[ -7.099701, -7.558904, -10.336046]], [[ -4.238656, ....336046]], [[ -4.238656, -7.558904, -10.336046]]]), array([[0.005734], [0.004665], [0.005496]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1, 0), 'ij,ijb,ija->ijab', ['ijab'])] contraction = ((2, 1, 0), 'ij,ijb,ija->ijab', ['ijab']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnowValues.test_ccsd _____________________________ self = def test_ccsd(self): mol = gto.Mole() mol.atom = ''' O 0.00000000 0.00000000 -0.11081188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''' mol.basis = 'cc-pvdz' mol.build() coords = [(0.5,0.6,0.8)] charges = [-0.5] mf = itrf.mm_charge(scf.RHF(mol), coords, charges).run() g = mf.nuc_grad_method().kernel() mfs = mf.as_scanner() e1 = mfs(''' O 0.00000000 0.00000000 -0.10981188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''') e2 = mfs(''' O -0.00000000 0.00000000 -0.11181188 H -0.00000000 -0.84695236 0.59109389 H -0.00000000 0.89830571 0.52404783 ''') self.assertAlmostEqual(g[0,2], (e1 - e2)/0.002 * lib.param.BOHR, 5) mycc = cc.ccsd.CCSD(mf) mycc.conv_tol = 1e-8 ecc, t1, t2 = mycc.kernel() > g = mycc.nuc_grad_method().kernel() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/qmmm/test/test_itrf.py:192: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:436: in kernel l1, l2 = mycc.solve_lambda(eris=eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0. , -0. , 0. , 0. , 0. , -0. , -0. , 0. , -0. , 0. ,...0.002981, 0.000544, -0.000766, -0.000283, 0.000825, 0.000076, 0.00015 , 0.00008 , -0.000228, 0.000039]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'jc,kc->jk', ['kb', 'jk']), ((1, 0), 'jk,kb->bj', ['bj'])] contraction = ((2, 0), 'jc,kc->jk', ['kb', 'jk']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_project_dm_nr2nr _______________________ self = def test_project_dm_nr2nr(self): nao = mol.nao_nr() dm = numpy.random.random((nao,nao)) dm = dm + dm.T x1 = addons.project_dm_nr2nr(mol, dm, mol) self.assertAlmostEqual(abs(dm-x1).max(), 0, 12) numpy.random.seed(15) mo = numpy.random.random((nao,10)) mo1 = addons.project_mo_nr2nr(mol, mo, mol_dz) dm = numpy.dot(mo, mo.T) dmref = numpy.dot(mo1, mo1.T) > dm1 = addons.project_dm_nr2nr(mol, [dm,dm], mol_dz) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/scf/test/test_addons.py:117: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/scf/addons.py:662: in project_dm_nr2nr return lib.einsum('pi,nij,qj->npq', p21, dm1, p21.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,nij,qj->npq' tensors = [array([[ 0.994741, 0.452218, -0.030333, 0. , 0. , 0.000029, 0. , -0. , 0.000413, 0.007188,...0. , -0.002721, -0.002257, 0. , 0.003983, 0.003669, 0.004366, 0.000225, -0.047756, 0.037173]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'nij,pi->njp', ['qj', 'njp']), ((1, 0), 'njp,qj->npq', ['npq'])] contraction = ((1, 0), 'nij,pi->njp', ['qj', 'njp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_project_dm_nr2r _______________________ self = def test_project_dm_nr2r(self): numpy.random.seed(15) nao = mol.nao_nr() mo = numpy.random.random((nao,10)) mo1 = addons.project_mo_nr2r(mol, mo, mol_dz) dm = numpy.dot(mo, mo.T.conj()) dmref = numpy.dot(mo1, mo1.T.conj()) > dm1 = addons.project_dm_nr2r(mol, [dm,dm], mol_dz) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/scf/test/test_addons.py:150: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/scf/addons.py:678: in project_dm_nr2r return lib.einsum('pi,nij,qj->npq', p21, dm1, p21.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,nij,qj->npq' tensors = [array([[ 0.994872-0.j , 0.454618-0.j , -0.032981+0.j , 0. -0.j , -0. +0.j , -0.0...1j, -0. -0.004259j, -0. +0.0131j , -0. -0.011549j, 0. +0.050706j, -0. -0.040273j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'nij,pi->njp', ['qj', 'njp']), ((1, 0), 'njp,qj->npq', ['npq'])] contraction = ((1, 0), 'nij,pi->njp', ['qj', 'njp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_project_dm_r2r ________________________ self = def test_project_dm_r2r(self): nao = mol.nao_2c() dm = numpy.random.random((nao*2,nao*2)) dm = dm + numpy.sin(dm)*1j x1 = addons.project_dm_r2r(mol, dm, mol) self.assertTrue(numpy.allclose(dm, x1)) numpy.random.seed(15) n2c = mol.nao_2c() n4c = n2c * 2 mo = numpy.random.random((n4c,10)) + numpy.random.random((n4c,10))*1j mo1 = addons.project_mo_r2r(mol, mo, mol_dz) dm = numpy.dot(mo, mo.T.conj()) dmref = numpy.dot(mo1, mo1.T.conj()) > dm1 = addons.project_dm_r2r(mol, [dm,dm], mol_dz) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/scf/test/test_addons.py:137: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/scf/addons.py:692: in project_dm_r2r return lib.einsum('pi,nij,qj->npq', p21, dm1, p21.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,nij,qj->npq' tensors = [array([[ 0.994872+0.j , 0. -0.j , 0.454618+0.j , 0. +0.j , -0.032981+0.j , 0. ...005376j, -0. -0.j , 0. +0.034924j, 0. -0.j , 0. -0.017613j]], shape=(96, 52))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'nij,pi->njp', ['qj', 'njp']), ((1, 0), 'njp,qj->npq', ['npq'])] contraction = ((1, 0), 'nij,pi->njp', ['qj', 'njp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_rhf_smearing_nelec ______________________ self = def test_rhf_smearing_nelec(self): mol = gto.Mole() mol.verbose = 5 mol.output = '/dev/null' mol.atom = ''' 7 0. 0 -0.7 7 0. 0 0.7''' mol.basis = 'cc-pvdz' mol.charge = +1 mol.spin = 1 mol.build() mf = scf.hf.RHF(mol) mf = addons.frac_occ(mf) e_frac = mf.kernel() mf_smear = scf.RHF(mol) # a small sigma amplifies the errors in orbital energies, breaking the # orbital degeneracy. mf_smear = addons.smearing(mf_smear, sigma=1e-3, method='fermi') > e_smear = mf_smear.kernel() ^^^^^^^^^^^^^^^^^ pyscf/scf/test/test_addons.py:500: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ :2: in kernel ??? pyscf/scf/hf.py:2017: in scf kernel(self, self.conv_tol, self.conv_tol_grad, pyscf/scf/hf.py:176: in kernel mo_occ = mf.get_occ(mo_energy, mo_coeff) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/scf/addons.py:226: in get_occ logger.info(self, ' sigma = %g Optimized mu = %.12g entropy = %.12g', pyscf/lib/logger.py:135: in info flush(rec, msg, *args) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rec = msg = ' sigma = %g Optimized mu = %.12g entropy = %.12g' args = (0.001, array([-0.323359]), np.float64(2.2496372094712047)) def flush(rec, msg, *args): > rec.stdout.write(msg%args) ^^^^^^^^ E TypeError: only 0-dimensional arrays can be converted to Python scalars pyscf/lib/logger.py:114: TypeError ________________________ KnownValues.test_mute_chkfile _________________________ self = def test_mute_chkfile(self): # To ensure "mf.chkfile = None" does not affect post-SCF calculations mol = gto.M(atom='he', basis='6-311g', verbose=0) mf1 = scf.RHF(mol) mf1.chkfile = None mf1.newton().kernel() #mf1.apply('CISD').run() #mf1.apply('CCSD').run() > mf1.apply('TDHF').run() pyscf/scf/test/test_rhf.py:751: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[1., 0.]], [[0., 1.]]]), array([[-0.137951, -1.443869], [-1.153994, 1.698764], [ 1.427937, -0.696296]]), array([[0.527117], [0.974974], [0.794891]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ SolventWithDefaultGrids.test_rhf_tda _____________________ self = def test_rhf_tda(self): # TDA with equilibrium_solvation mf = mol.RHF().ddCOSMO().run(conv_tol=1e-12) > td = mf.TDA(equilibrium_solvation=True).run(conv_tol=1e-10) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo.py:508: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., ....004347, 0.17638 , 0.401878, 0.263097, 0. ], [ 0.010953, 0.06372 , 0.427295, 0.282561, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_B1 ______________________________ self = def test_B1(self): def getB(mol): pcm = ddcosmo.DDCOSMO(mol) pcm.lmax = 2 pcm.eps = 0 natm = mol.natm nao = mol.nao nlm = (pcm.lmax+1)**2 r_vdw = ddcosmo.get_atomic_radii(pcm) fi = ddcosmo.make_fi(pcm, r_vdw) ui = 1 - fi ui[ui<0] = 0 pcm.grids = grids = ddcosmo.Grids(mol).run(level=0) coords_1sph, weights_1sph = ddcosmo.make_grids_one_sphere(pcm.lebedev_order) ylm_1sph = numpy.vstack(sph.real_sph_vec(coords_1sph, pcm.lmax, True)) cached_pol = ddcosmo.cache_fake_multipoles(grids, r_vdw, pcm.lmax) L = ddcosmo.make_L(pcm, r_vdw, ylm_1sph, fi) return make_B(pcm, r_vdw, ui, ylm_1sph, cached_pol, L) pcm = ddcosmo.DDCOSMO(mol0) pcm.lmax = 2 pcm.eps = 0 natm = mol0.natm nao = mol0.nao nlm = (pcm.lmax+1)**2 r_vdw = ddcosmo.get_atomic_radii(pcm) fi = ddcosmo.make_fi(pcm, r_vdw) ui = 1 - fi ui[ui<0] = 0 pcm.grids = grids = ddcosmo.Grids(mol0).run(level=0) coords_1sph, weights_1sph = ddcosmo.make_grids_one_sphere(pcm.lebedev_order) ylm_1sph = numpy.vstack(sph.real_sph_vec(coords_1sph, pcm.lmax, True)) cached_pol = ddcosmo.cache_fake_multipoles(grids, r_vdw, pcm.lmax) L = ddcosmo.make_L(pcm, r_vdw, ylm_1sph, fi) > dB = make_B1(pcm, r_vdw, ui, ylm_1sph, cached_pol, L) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_grad.py:983: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/test/test_ddcosmo_grad.py:439: in make_B1 phi1[:,:,ia] += lib.einsum('n,ln,azn,ijn->azlij', weights_1sph, ylm_1sph, ui1[:,:,ia], v_nj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'n,ln,azn,ijn->azlij' tensors = [array([0.048107, 0.048107, 0.048107, 0.048107, 0.048107, 0.048107, 0.123072, 0.123072, 0.123072, 0.123072, 0.123072, ...24994 , 0.499396, 0.384617, 0.264062, 0.241087, 0.440815, 0.311641, 0.304805, 0.24994 ]]], shape=(4, 4, 110))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ln,n->ln', ['azn', 'ijn', 'ln']), ((2, 1, 0), 'ln,ijn,azn->azlij', ['azlij'])] contraction = ((1, 0), 'ln,n->ln', ['azn', 'ijn', 'ln']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casci_grad __________________________ self = def test_casci_grad(self): mf = scf.RHF(mol0).ddCOSMO().run() mc = solvent.ddCOSMO(mcscf.CASCI(mf, 2, 2)) > e, de = mc.nuc_grad_method().as_scanner()(mol0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_grad.py:817: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/grad/pcm.py:444: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.700196, -1.905843, 1.296864, 1.695534, -2.307512, 1.02644 , -1.102537, 1.500482, -1.334904, 0.434017...[[-0.587237, 1.586822], [ 0.808171, 0.454347], [-0.721621, -1.169974], [ 0.463869, -0.802744]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casscf_grad _________________________ self = def test_casscf_grad(self): mf = scf.RHF(mol0).ddCOSMO().run() mc = solvent.ddCOSMO(mcscf.CASSCF(mf, 2, 2)).set(conv_tol=1e-9) mc_g = mc.nuc_grad_method().as_scanner() > e, de = mc_g(mol0) ^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_grad.py:849: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/grad/pcm.py:444: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.801431, -1.34245 , 0.562173, 1.758045, -1.472421, 0.964126, -0.223882, 0.187509, -0.245558, 0.015636...[[ 0.629824, -1.647244], [-0.531867, 0.171179], [ 0.702799, 1.512371], [-0.088806, -0.000791]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ccsd_grad __________________________ self = def test_ccsd_grad(self): mf = scf.RHF(mol0).ddCOSMO().run() mycc = cc.CCSD(mf).ddCOSMO() > e, de = mycc.nuc_grad_method().as_scanner()(mol0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_grad.py:866: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/ccsd.py:253: in __call__ cc.kernel(t1=cc.t1, t2=cc.t2, eris=eris) pyscf/solvent/_attach_solvent.py:609: in kernel dm = basic_scanner.make_rdm1(ao_repr=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1339: in make_rdm1 if l1 is None: l1, l2 = self.solve_lambda(t1, t2) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[ 0., 0.], [ 0., -0.]]), array([[ 0.000742, 0.000675], [-0.006969, 0.002444]]), array([[ 0.000742, 0.000675], [-0.006969, 0.002444]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kb,kc->bc', ['jc', 'bc']), ((1, 0), 'bc,jc->bj', ['bj'])] contraction = ((1, 0), 'kb,kc->bc', ['jc', 'bc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_solvent_nuc _________________________ self = def test_solvent_nuc(self): def get_nuc(mol): pcm = ddcosmo.DDCOSMO(mol) pcm.lmax = 2 pcm.eps = 0 natm = mol.natm nao = mol.nao nlm = (pcm.lmax+1)**2 r_vdw = ddcosmo.get_atomic_radii(pcm) fi = ddcosmo.make_fi(pcm, r_vdw) ui = 1 - fi ui[ui<0] = 0 pcm.grids = grids = ddcosmo.Grids(mol).run(level=0) coords_1sph, weights_1sph = ddcosmo.make_grids_one_sphere(pcm.lebedev_order) ylm_1sph = numpy.vstack(sph.real_sph_vec(coords_1sph, pcm.lmax, True)) cached_pol = ddcosmo.cache_fake_multipoles(grids, r_vdw, pcm.lmax) L = ddcosmo.make_L(pcm, r_vdw, ylm_1sph, fi) return nuc_part(pcm, r_vdw, ui, ylm_1sph, cached_pol, L) pcm = ddcosmo.DDCOSMO(mol0) pcm.lmax = 2 pcm.eps = 0 natm = mol0.natm nao = mol0.nao nlm = (pcm.lmax+1)**2 r_vdw = ddcosmo.get_atomic_radii(pcm) fi = ddcosmo.make_fi(pcm, r_vdw) ui = 1 - fi ui[ui<0] = 0 pcm.grids = grids = ddcosmo.Grids(mol0).run(level=0) coords_1sph, weights_1sph = ddcosmo.make_grids_one_sphere(pcm.lebedev_order) ylm_1sph = numpy.vstack(sph.real_sph_vec(coords_1sph, pcm.lmax, True)) cached_pol = ddcosmo.cache_fake_multipoles(grids, r_vdw, pcm.lmax) L = ddcosmo.make_L(pcm, r_vdw, ylm_1sph, fi) > dvmat = nuc_part1(pcm, r_vdw, ui, ylm_1sph, cached_pol, L) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_grad.py:930: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/test/test_ddcosmo_grad.py:308: in nuc_part1 wtmp = lib.einsum('l,n,ln->ln', LS0[ia], weights_1sph, ylm_1sph) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'l,n,ln->ln' tensors = [array([ 0.541202, -0.109919, -0.039116, -0.075133, 0.007374, -0.081016, -0.027546, 0.012085, -0.033427]), array([0....0.421267, 0.421267, -0.125008, -0.125008, -0.125008, -0.125008, -0.421267, -0.421267, -0.421267, -0.421267]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 1, 0), 'ln,n,l->ln', ['ln'])] contraction = ((2, 1, 0), 'ln,n,l->ln', ['ln']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_tda_grad ___________________________ self = def test_tda_grad(self): mol0 = gto.M(atom='H 0 0 0 ; H .5 .5 .1', unit='B', basis='321g') mol1 = gto.M(atom='H 0 0 -.001; H .5 .5 .1', unit='B', basis='321g') mol2 = gto.M(atom='H 0 0 0.001; H .5 .5 .1', unit='B', basis='321g') mf = scf.RHF(mol0).ddCOSMO().run() > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_grad.py:883: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[1., 0., 0.]], [[0., 1., 0.]], [[0., 0., 1.]]]), array([[ 0.048693, -0.619761, -1.708212], ... [-3.257381, 0.643247, -1.889328]]), array([[0.700301], [0.435058], [0.700301], [0.435058]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_b3lyp_tda __________________________ self = def test_b3lyp_tda(self): mf = mol0.RKS().ddCOSMO().run(xc='b3lyp') > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:103: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [1.], [0.], [0.]], [[0.], [0.], [0.], .... , -0. , 0. , 1.999994, 0.005004], [ 0.005783, 0.265532, 1.377056, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_lda_tda ___________________________ self = def test_lda_tda(self): mf = mol0.RKS().ddCOSMO().run(xc='svwn') > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:92: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [1.], [0.], [0.]], [[0.], [0.], [0.], .... , 0. , -0. , -0.040275, 1.999594], [ 0.006382, 0.318967, 1.372154, -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_rhf_tda ___________________________ self = def test_rhf_tda(self): mf = mol0.RHF().ddCOSMO().run() > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [1.], [0.], [0.]], [[0.], [0.], [0.], .... , -0. , 0. , 2. , -0. ], [ 0.005333, 0.151676, 1.41052 , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_rhf_tda_triplet _______________________ self = def test_rhf_tda_triplet(self): mf = mol0.RHF().ddCOSMO().run() > td = mf.TDA(equilibrium_solvation=True).run(singlet=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [1.], [0.], [0.]], [[0.], [0.], [0.], .... , 0. , -0. , 0.356949, 1.967889], [ 0.005333, 0.151676, 1.41052 , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_rhf_tdhf ___________________________ self = def test_rhf_tdhf(self): mf = mol0.RHF().ddCOSMO().run() > td = mf.TDHF(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:48: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [1.], [0.], [0.]], [[0.], [0.], [0.], .... , 0. , -0. , 1.118824, 1.657779], [ 0.005333, 0.151676, 1.41052 , -0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_scanner ___________________________ self = def test_scanner(self): mol = gto.M(atom='H 0 0 0; F .1 0 2.1', verbose=0, unit='B') > td_ref = solvent.ddCOSMO(mol.RHF()).run().TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:136: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [1.], [0.], [0.]], [[0.], [0.], [0.], .... , -0. , -0. , 2. , -0. ], [-0.003517, -0.080982, 1.388666, -0. , -0.09513 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_ub3lyp_tda __________________________ self = def test_ub3lyp_tda(self): mf = mol0.UKS().ddCOSMO().run(xc='b3lyp') > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:125: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [0.], [1.], [0.]], [[0.], [0.], [0.], .... , -0. , 0. , 0.008705, 0.999962], [ 0.002892, 0.132766, 0.688528, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_uhf_tda ___________________________ self = def test_uhf_tda(self): mf = mol0.UHF().ddCOSMO().run() > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:70: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [0.], [1.], [0.]], [[0.], [0.], [0.], .... , -0. , -0. , 0.99821 , 0.059798], [ 0.002667, 0.075837, 0.705261, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_uhf_tdhf ___________________________ self = def test_uhf_tdhf(self): mf = mol0.UHF().ddCOSMO().run() > td = mf.TDHF(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [0.], [1.], [0.]], [[0.], [0.], [0.], .... , 0. , -0. , 0.665193, 0.746671], [ 0.002667, 0.075837, 0.705261, 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ulda_tda ___________________________ self = def test_ulda_tda(self): mf = mol0.UKS().ddCOSMO().run(xc='svwn') > td = mf.TDA(equilibrium_solvation=True).run() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_ddcosmo_tdscf_grad.py:114: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.], [0.], [0.], [1.], [0.]], [[0.], [0.], [0.], .... , 0. , 0. , 0.999986, -0.005304], [ 0.003191, 0.159483, 0.686077, -0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ccsd _____________________________ self = def test_ccsd(self): mf = scf.RHF(mol0).PCM() mf.conv_tol = 1e-12 mf.kernel() mycc = cc.CCSD(mf).PCM() > mycc.kernel() pyscf/solvent/test/test_pcm.py:167: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/_attach_solvent.py:609: in kernel dm = basic_scanner.make_rdm1(ao_repr=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1339: in make_rdm1 if l1 is None: l1, l2 = self.solve_lambda(t1, t2) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., 0.], [ 0., 0.], [ 0., 0.], [ 0., 0.], [-0., 0.]]), array([[-0.000031, -... [-0.000481, -0. ], [-0. , -0.003769], [ 0.013043, -0. ], [ 0. , -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kb,kc->bc', ['jc', 'bc']), ((1, 0), 'bc,jc->bj', ['bj'])] contraction = ((1, 0), 'kb,kc->bc', ['jc', 'bc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_tdhf _____________________________ self = def test_tdhf(self): mol = gto.Mole( verbose = 5, output = '/dev/null', atom = [ ['O', (0. , 0., 0.)], ['H', (0. , -0.757, 0.587)], ['H', (0. , 0.757, 0.587)], ], basis = 'def2svp') mf = mol.RHF().PCM() mf.with_solvent.method = 'C-PCM' mf.with_solvent.lebedev_order = 29 # 302 Lebedev grids mf.with_solvent.eps = 78 mf.run(conv_tol=1e-10) td = mf.TDHF() > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm.py:187: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.....003843, -0.064445, -0.043962, -0.059353, -0. ], [-0.003025, -0.035199, -0.062777, 0.008407, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casci_grad __________________________ self = def test_casci_grad(self): mf = scf.RHF(mol0).PCM().run() mc = solvent.PCM(mcscf.CASCI(mf, 2, 2)) > e, de = mc.nuc_grad_method().as_scanner()(mol0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_grad.py:183: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casci.py:252: in __call__ de = self.kernel(ci=ci, state=state, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/grad/pcm.py:444: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:315: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casci.py:151: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.698857, -1.908461, 1.302921, 1.694869, -2.314201, 1.0276 , -1.092198, 1.491304, -1.3244 , 0.426731...[[-0.586557, 1.587244], [ 0.810074, 0.454859], [-0.722088, -1.168347], [ 0.459871, -0.80464 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_casscf_grad _________________________ self = def test_casscf_grad(self): mf = scf.RHF(mol0).PCM().run() mc = solvent.PCM(mcscf.CASSCF(mf, 2, 2)).set(conv_tol=1e-9) mc_g = mc.nuc_grad_method().as_scanner() > e, de = mc_g(mol0) ^^^^^^^^^^ pyscf/solvent/test/test_pcm_grad.py:198: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/grad/casscf.py:185: in __call__ de = self.kernel(**kwargs) ^^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/grad/pcm.py:444: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:211: in kernel de = self.grad_elec(mo_coeff, ci, atmlst, log) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/grad/casscf.py:126: in grad_elec dm2_ao = lib.einsum('ijw,pi,qj->pqw', dm2buf, mo_cas[p0:p1], mo_cas[q0:q1]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'ijw,pi,qj->pqw' tensors = [array([[[ 0.797906, -1.339942, 0.562549, 1.754582, -1.473255, 0.964574, -0.217074, 0.182269, -0.238671, 0.014764...[[ 0.627954, -1.647856], [-0.531981, 0.172443], [ 0.703362, 1.511999], [-0.086297, -0.001645]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']), ((1, 0), 'pjw,qj->pqw', ['pqw'])] contraction = ((1, 0), 'pi,ijw->pjw', ['qj', 'pjw']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_ccsd_grad __________________________ self = def test_ccsd_grad(self): mf = scf.RHF(mol0).PCM() mf.conv_tol = 1e-12 mf.kernel() mycc = cc.CCSD(mf).PCM() mycc.with_solvent.conv_tol = 1e-12 mycc.conv_tol = 1e-12 > mycc.kernel() pyscf/solvent/test/test_pcm_grad.py:216: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/_attach_solvent.py:609: in kernel dm = basic_scanner.make_rdm1(ao_repr=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1339: in make_rdm1 if l1 is None: l1, l2 = self.solve_lambda(t1, t2) ^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd.py:1278: in solve_lambda ccsd_lambda.kernel(self, eris, t1, t2, l1, l2, pyscf/cc/ccsd_lambda.py:50: in kernel imds = fintermediates(mycc, t1, t2, eris) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/cc/ccsd_lambda.py:101: in make_intermediates w3 += lib.einsum('kc,kb,jc->bj', fov, t1, t1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'kc,kb,jc->bj' tensors = [array([[-0., -0.], [-0., 0.]]), array([[ 0.000754, 0.000693], [-0.00696 , 0.00244 ]]), array([[ 0.000754, 0.000693], [-0.00696 , 0.00244 ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'kb,kc->bc', ['jc', 'bc']), ((1, 0), 'bc,jc->bj', ['bj'])] contraction = ((1, 0), 'kb,kc->bc', ['jc', 'bc']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_hess_cpcm __________________________ self = def test_hess_cpcm(self): print('testing C-PCM Hessian with DF-RKS') mf = _make_mf(method='C-PCM') hobj = mf.Hessian() hobj.set(auxbasis_response=2) > h = hobj.kernel() ^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_hessian.py:153: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/hessian/pcm.py:1056: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:180: in _partial_hess_ejk wk_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocc_2, mocc_2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ....010182, 0.241127, -0.619899, -0.382781, 0. ], [-0.010182, 0.241127, 0.619899, -0.382781, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_hess_iefpcm _________________________ self = def test_hess_iefpcm(self): print("testing IEF-PCM hessian with DF-RKS") mf = _make_mf(method='IEF-PCM') hobj = mf.Hessian() hobj.set(auxbasis_response=2) > h = hobj.kernel() ^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_hessian.py:162: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/hessian/pcm.py:1056: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/rks.py:56: in partial_hess_elec de2, ej, ek = df_rhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/rhf.py:180: in _partial_hess_ejk wk_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocc_2, mocc_2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ....010182, 0.241151, -0.619947, -0.382829, -0. ], [-0.010182, 0.241151, 0.619947, -0.382829, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_uhf_hess_iefpcm _______________________ self = def test_uhf_hess_iefpcm(self): print("testing IEF-PCM hessian with DF-UKS") mf = _make_mf(method='IEF-PCM', restricted=False) hobj = mf.Hessian() hobj.set(auxbasis_response=2) > h = hobj.kernel() ^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_hessian.py:171: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/solvent/hessian/pcm.py:1056: in kernel self.de_solute = super().kernel(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/rhf.py:567: in kernel de = self.hess_elec(mo_energy, mo_coeff, mo_occ, atmlst=atmlst) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/hessian/uhf.py:51: in hess_elec de2 = hessobj.partial_hess_elec(mo_energy, mo_coeff, mo_occ, atmlst, pyscf/df/hessian/uks.py:60: in partial_hess_elec de2, ej, ek = df_uhf_hess._partial_hess_ejk(hessobj, mo_energy, mo_coeff, mo_occ, pyscf/df/hessian/uhf.py:193: in _partial_hess_ejk wka_ip2_P__[p0:p1] = lib.einsum('xuvp,ui,vj->pxij', int3c_ip2, mocca, mocca) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xuvp,ui,vj->pxij' tensors = [array([[[[-0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. , -0. ....0072 , 0.170519, -0.438369, -0.270701, 0. ], [-0.0072 , 0.170519, 0.438369, -0.270701, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']), ((1, 0), 'xivp,vj->pxij', ['pxij'])] contraction = ((1, 0), 'ui,xuvp->xivp', ['vj', 'xivp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_b3lyp_CPCM __________________________ self = def test_b3lyp_CPCM(self): mf = self.mf_b3lyp_nodf td = mf.TDDFT(equilibrium_solvation=False) > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_tdscf.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.....005237, -0.06347 , -0.029397, -0.047748, -0. ], [-0.004143, -0.031159, -0.053844, 0.022048, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_b3lyp_IEFPCM _________________________ self = def test_b3lyp_IEFPCM(self): mf = self.mf_b3lyp_nodf_iefpcm td = mf.TDDFT(equilibrium_solvation=False) > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_tdscf.py:216: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.....005237, -0.063473, -0.029394, -0.047759, 0. ], [-0.004144, -0.031151, -0.053832, 0.022088, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_hf_CPCM ___________________________ self = def test_hf_CPCM(self): """ $rem JOBTYPE sp METHOD hf BASIS def2-svp CIS_N_ROOTS 5 CIS_SINGLETS TRUE CIS_TRIPLETS FALSE SYMMETRY FALSE SYM_IGNORE TRUE ! RPA 2 # whether tddft or tda BASIS_LIN_DEP_THRESH 12 SOLVENT_METHOD PCM $end $PCM Theory CPCM HeavyPoints 302 HPoints 302 $end $solvent dielectric 78 $end """ mf = self.mf td = mf.TDHF(equilibrium_solvation=False) > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_tdscf.py:174: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.....003843, -0.064445, -0.043962, -0.059353, -0. ], [-0.003025, -0.035199, -0.062777, 0.008407, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_unrestricted_b3lyp_CPCM ___________________ self = def test_unrestricted_b3lyp_CPCM(self): mf = self.mf_b3lyp_nodf_u td = mf.TDDFT(equilibrium_solvation=False) > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_tdscf.py:249: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.....002618, -0.031735, -0.014698, -0.023874, -0. ], [-0.002072, -0.01558 , -0.026922, 0.011024, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________ KnownValues.test_unrestricted_hf_CPCM _____________________ self = def test_unrestricted_hf_CPCM(self): mf = self.mfu td = mf.TDHF(equilibrium_solvation=False) > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/solvent/test/test_pcm_tdscf.py:237: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.....001921, -0.032222, -0.021981, -0.029677, -0. ], [-0.001512, -0.017599, -0.031389, 0.004203, -0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ab_hf ____________________________ self = def test_ab_hf(self): mf = scf.DHF(mol).run() > self._check_against_ab_ks(mf.TDHF(), 3.162381949829394, 0.11755137875158098) pyscf/tdscf/test/test_tddks.py:91: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tddks.py:144: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/dhf.py:64: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.313259j, 0.025926+0.041798j, 0.549662+0.7384j , 0.435322+0.657512j, 0.420368+0.214636j, 0.330335... , 0. -0.j , -0.697151+0.j ], [-0. +0.000001j, 0.000158+0.121843j, 0. -0.000001j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_col_gga_ab_ks ________________________ self = def test_col_gga_ab_ks(self): mf_b3lyp = dft.DKS(mol).set(xc='b3lyp5') mf_b3lyp.__dict__.update(scf.chkfile.load(mf_lda.chkfile, 'scf')) > self._check_against_ab_ks(mf_b3lyp.TDDFT(), 2.568259113326634, 0.1531691970098629) pyscf/tdscf/test/test_tddks.py:99: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tddks.py:144: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/dhf.py:64: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.313259j, 0.025926+0.041798j, 0.549662+0.7384j , 0.435322+0.657512j, 0.420368+0.214636j, 0.330335... , -0.154549+0.000141j, 0.000001+0.000003j], [ 0.202065-0.000013j, 0. +0.j , 0.704809-0.240971j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_col_lda_ab_ks ________________________ self = def test_col_lda_ab_ks(self): > self._check_against_ab_ks(mf_lda.TDDFT(), 2.6168030250127075, 0.10466808380307921) pyscf/tdscf/test/test_tddks.py:94: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tddks.py:144: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/dhf.py:64: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.313259j, 0.025926+0.041798j, 0.549662+0.7384j , 0.435322+0.657512j, 0.420368+0.214636j, 0.330335... , -0.154549+0.000141j, 0.000001+0.000003j], [ 0.202065-0.000013j, 0. +0.j , 0.704809-0.240971j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_col_mgga_ab_ks ________________________ self = def test_col_mgga_ab_ks(self): mf_m06l = dft.DKS(mol).set(xc='m06l') mf_m06l.__dict__.update(scf.chkfile.load(mf_lda.chkfile, 'scf')) > self._check_against_ab_ks(mf_m06l.TDDFT(), 3.382341929143924, 0.6409502830461241) pyscf/tdscf/test/test_tddks.py:104: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tddks.py:144: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/dhf.py:64: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.313259j, 0.025926+0.041798j, 0.549662+0.7384j , 0.435322+0.657512j, 0.420368+0.214636j, 0.330335... , -0.154549+0.000141j, 0.000001+0.000003j], [ 0.202065-0.000013j, 0. +0.j , 0.704809-0.240971j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_tda_lda ___________________________ self = def test_tda_lda(self): td = mf_lda.TDA() > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tddks.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/dhf.py:444: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/dhf.py:64: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0., 0., 0., 0., 0.... , -0.154549+0.000141j, 0.000001+0.000003j], [ 0.202065-0.000013j, 0. +0.j , 0.704809-0.240971j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_tddft_lda __________________________ self = def test_tddft_lda(self): td = mf_lda.TDDFT() > es = td.kernel(nstates=4)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tddks.py:73: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/dhf.py:563: in kernel self.converged, w, x1 = lr_eig( pyscf/tdscf/_lr_eig.py:339: in eig axt = aop(xt) ^^^^^^^ pyscf/tdscf/dhf.py:498: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0., 0., 0., 0., 0.... , -0.154549+0.000141j, 0.000001+0.000003j], [ 0.202065-0.000013j, 0. +0.j , 0.704809-0.240971j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ab_hf ____________________________ self = def test_ab_hf(self): mf = scf.GHF(molsym).newton().run(conv_tol=1e-12) > self._check_against_ab_ks_complex(mf.TDHF(), -4.4803646453030055, -1.5206818818244117, 5) pyscf/tdscf/test/test_tdgks.py:108: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tdgks.py:177: in _check_against_ab_ks_complex self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.04349j , 0.025926+0.247551j, 0.549662+0.943171j, 0.435322+0.55686j , 0.420368+0.357518j, 0.330335... [ 0.001401, -0.001401, -0.005873, -0.005872, -0.087615, 0.087615, 0.056956, -0.056956, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_col_gga_ab_ks ________________________ self = def test_col_gga_ab_ks(self): mf_b3lyp = dft.GKS(mol).set(xc='b3lyp5') mf_b3lyp.__dict__.update(scf.chkfile.load(mf_lda.chkfile, 'scf')) > self._check_against_ab_ks_real(mf_b3lyp.TDDFT(), -0.47606715615564554, 0.1771403691719411) pyscf/tdscf/test/test_tdgks.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tdgks.py:154: in _check_against_ab_ks_real self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995, 0.025926, 0.549662, 0.435322, 0.420368, 0.330335, 0.204649, 0.619271, 0.299655], [0.266827... 0. , 0.148118, 0. ], [ 0. , 0.195003, 0. ], [ 0. , 0.148118, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_col_lda_ab_ks ________________________ self = def test_col_lda_ab_ks(self): > self._check_against_ab_ks_real(tdscf.gks.TDDFT(mf_lda), -0.5233726312108345, 0.07876886521779444) pyscf/tdscf/test/test_tdgks.py:111: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tdgks.py:154: in _check_against_ab_ks_real self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995, 0.025926, 0.549662, 0.435322, 0.420368, 0.330335, 0.204649, 0.619271, 0.299655], [0.266827... 0. , 0.148118, 0. ], [ 0. , 0.195003, 0. ], [ 0. , 0.148118, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_col_mgga_ab_ks ________________________ self = def test_col_mgga_ab_ks(self): mf_m06l = dft.GKS(mol).set(xc='m06l') mf_m06l.__dict__.update(scf.chkfile.load(mf_lda.chkfile, 'scf')) > self._check_against_ab_ks_real(tdscf.gks.TDDFT(mf_m06l), -0.49217076039995644, 0.14593146495412246) pyscf/tdscf/test/test_tdgks.py:121: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/test/test_tdgks.py:154: in _check_against_ab_ks_real self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995, 0.025926, 0.549662, 0.435322, 0.420368, 0.330335, 0.204649, 0.619271, 0.299655], [0.266827... 0. , 0.148118, 0. ], [ 0. , 0.195003, 0. ], [ 0. , 0.148118, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_tda_lda ___________________________ self = def test_tda_lda(self): td = mf_lda.TDA() > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdgks.py:98: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/ghf.py:466: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., ... 0. , 0.148118, 0. ], [ 0. , 0.195003, 0. ], [ 0. , 0.148118, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_tda_with_wfnsym _______________________ self = def test_tda_with_wfnsym(self): td = mf_bp86.TDA() td.wfnsym = 'B2' > es = td.kernel(nstates=3)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdgks.py:189: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/ghf.py:466: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0.... [ 0. , 0.003278, 0. , 0.000635, 0.14853 , 0. , 0. , 0.10635 , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_tddft_lda __________________________ self = def test_tddft_lda(self): td = mf_lda.TDDFT() > es = td.kernel(nstates=4)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdgks.py:90: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/gks.py:130: in kernel self.converged, w2, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/gks.py:81: in vind dms = lib.einsum('xov,pv,qo->xpq', zs*d_ia, orbv, orbo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ], [0.614078... 0. , 0.148118, 0. ], [ 0. , 0.195003, 0. ], [ 0. , 0.148118, 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_tddft_with_wfnsym ______________________ self = def test_tddft_with_wfnsym(self): td = mf_bp86.CasidaTDDFT() td.wfnsym = 'B2' td.nroots = 3 > es = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tdgks.py:204: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/gks.py:130: in kernel self.converged, w2, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/gks.py:81: in vind dms = lib.einsum('xov,pv,qo->xpq', zs*d_ia, orbv, orbo) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ... [ 0. , 0.003278, 0. , 0.000635, 0.14853 , 0. , 0. , 0.10635 , 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ______________________ KnownValues.test_tdhf_with_wfnsym _______________________ self = def test_tdhf_with_wfnsym(self): mf_ghf = scf.GHF(molsym).run() td = mf_ghf.TDHF() td.wfnsym = 'B2' td.nroots = 3 > es = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tdgks.py:197: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/ghf.py:616: in kernel self.converged, w, x1 = lr_eig( pyscf/tdscf/_lr_eig.py:339: in eig axt = aop(xt) ^^^^^^^ pyscf/tdscf/ghf.py:537: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0.... [-0.001401, 0.001401, -0.005873, -0.005873, 0.087615, 0.087615, 0.056956, -0.056956, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_symmetry_init_guess _____________________ self = def test_symmetry_init_guess(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', symmetry='D2h') mf = mol.RHF.run() > td = mf.TDA().run(nstates=1) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrhf.py:78: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [.... , 0.552001, 0. ], [ 0.001989, -0.010607, -0.05964 , -0.058132, -0.396942, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_tda_singlet _________________________ self = def test_tda_singlet(self): td = mf.TDA().set(nstates=nstates) td.max_memory = 1e-3 > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tdrhf.py:43: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , 0. , 0. , 0. , 0.980401], [-0.0028 , 0.094185, 0.699376, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_tda_triplet _________________________ self = def test_tda_triplet(self): td = mf.TDA().set(nstates=nstates) td.singlet = False > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tdrhf.py:52: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , 0. , 0. , 0. , 0.980401], [-0.0028 , 0.094185, 0.699376, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_tdhf_singlet _________________________ self = def test_tdhf_singlet(self): td = mf.TDHF().set(nstates=nstates) > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tdrhf.py:60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , 0. , 0. , 0. , 0.980401], [-0.0028 , 0.094185, 0.699376, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_tdhf_triplet _________________________ self = def test_tdhf_triplet(self): td = mf.TDHF().set(nstates=nstates) td.singlet = False > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tdrhf.py:69: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:1167: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/rhf.py:1054: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0..... , 0. , 0. , 0. , 0.980401], [-0.0028 , 0.094185, 0.699376, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _________________________ KnownValues.test_wb97xv_tda __________________________ self = def test_wb97xv_tda(self): # Same Q-Chem input as above, Q-Chem computes both TDA and TDDFT in the same run reference_ground_state_energy = -151.3641561221 reference_excited_state_energy = np.array([-151.14537857, -151.09702586, -151.07806251, -151.04306837, -151.01364584]) reference_excitation_energy = reference_excited_state_energy - reference_ground_state_energy mf = make_mf(mol) tda = mf.TDA() tda.exclude_nlc = False > test_excitation_energy, test_state_vector = tda.kernel(nstates = len(reference_excited_state_energy)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks_vv10.py:120: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0....01021 ], [-0.002844, 0.000232, -0.022282, -0.031933, -0.012651, 0.030458, -0.017595, 0.042118, -0.025069]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_wb97xv_tda_triplet ______________________ self = def test_wb97xv_tda_triplet(self): # Same Q-Chem input as above, Q-Chem computes both TDA and TDDFT in the same run reference_ground_state_energy = -151.3641561221 reference_excited_state_energy = np.array([-151.19274710, -151.14933133, -151.09446103, -151.06656613, -151.06072560]) reference_excitation_energy = reference_excited_state_energy - reference_ground_state_energy mf = make_mf(mol) tda = mf.TDA() tda.singlet = False tda.exclude_nlc = False > test_excitation_energy, test_state_vector = tda.kernel(nstates = len(reference_excited_state_energy)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks_vv10.py:182: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/rhf.py:970: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/rhf.py:96: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()*2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0....01021 ], [-0.002844, 0.000232, -0.022282, -0.031933, -0.012651, 0.030458, -0.017595, 0.042118, -0.025069]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_wb97xv_unrestricted_tda ___________________ self = def test_wb97xv_unrestricted_tda(self): # Same Q-Chem input as above, Q-Chem computes both TDA and TDDFT in the same run reference_ground_state_energy = -150.9397884760 reference_excited_state_energy = np.array([-150.88981193, -150.79604327, -150.75118183, -150.72292823, -150.71461300]) reference_excitation_energy = reference_excited_state_energy - reference_ground_state_energy mf = make_mf(unrestricted_mol, restricted = False) tda = mf.TDA() tda.exclude_nlc = False > test_excitation_energy, test_state_vector = tda.kernel(nstates = len(reference_excited_state_energy)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tdrks_vv10.py:244: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ..., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0....001961], [-0.001403, 0.000118, -0.011189, -0.016221, -0.00898 , 0.015899, -0.01178 , 0.022347, -0.004929]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________ KnownValues.test_symmetry_init_guess _____________________ self = def test_symmetry_init_guess(self): mol = gto.M(atom='N 0 0 0; N 0 0 1.2', basis='631g', symmetry=True, verbose=0) mf = mol.UHF.run() > td = mf.TDA().run(nstates=1) ^^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/test/test_tduhf.py:80: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/lib/misc.py:637: in run self.kernel(*args) pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [... 0.276001, 0. ], [ 0.000995, -0.005303, -0.02982 , -0.029067, -0.198471, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_tda _____________________________ self = def test_tda(self): td = mf.TDA() td.nstates = 5 > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tduhf.py:51: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... 0. , 0. , 0. , 0.490201], [-0.0014 , 0.047093, 0.349688, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_tda1 _____________________________ self = def test_tda1(self): td = mf1.TDA() td.nstates = 5 > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tduhf.py:66: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:766: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/uhf.py:98: in vind dmsa = lib.einsum('xov,pv,qo->xpq', za, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0.], [0., 0., 0., 0., 0.], [0., 0., 0., 0., 0.], [0., 0., 0., 0., 0..... , 0.41508 , -0.008327, -0. ], [-0.001168, 0.037049, 0.346261, 0. , -0. , -0.357695]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->vxq', ['pv', 'vxq']), ((1, 0), 'vxq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->vxq', ['pv', 'vxq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_tdhf _____________________________ self = def test_tdhf(self): td = mf.TDHF() td.nstates = 5 td.conv_tol = 1e-5 > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tduhf.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0.], [0., 0.... 0. , 0. , 0. , 0.490201], [-0.0014 , 0.047093, 0.349688, 0. , 0. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_tdhf1 ____________________________ self = def test_tdhf1(self): td = mf1.TDHF() td.nstates = 4 > e = td.kernel()[0] ^^^^^^^^^^^ pyscf/tdscf/test/test_tduhf.py:73: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/uhf.py:953: in kernel self.converged, self.e, x1 = eig( pyscf/tdscf/_lr_eig.py:574: in real_eig axt = aop(np.hstack([V, W])) ^^^^^^^^^^^^^^^^^^^^^^ pyscf/tdscf/uhf.py:863: in vind dmsa = lib.einsum('xov,pv,qo->xpq', xa, orbva, orboa.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0.], [0., 0., 0., 0., 0.], [0., 0., 0., 0., 0.], [0., 0., 0., 0., 0..... , 0.41508 , -0.008327, -0. ], [-0.001168, 0.037049, 0.346261, 0. , -0. , -0.357695]])] kwargs = {}, contract = , optimize = True contraction_list = [((2, 0), 'qo,xov->xvq', ['pv', 'xvq']), ((1, 0), 'xvq,pv->xpq', ['xpq'])] contraction = ((2, 0), 'qo,xov->xvq', ['pv', 'xvq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_ab_hf ____________________________ self = def test_ab_hf(self): mf = x2c.UHF(mol).newton().run(conv_tol=1e-12) > self._check_against_ab_ks(mf.TDHF(), -0.2404548371794495, 0.6508765417771681, 4) pyscf/x2c/test/test_tdscf.py:93: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/test/test_tdscf.py:143: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.406275j, 0.025926+0.027202j, 0.549662+0.247177j, 0.435322+0.067144j, 0.420368+0.993852j, 0.330335...j, 0.00226 -0.001061j, -0.196983+0.701443j], [ 0.004614-0.002143j, -0.073346+0.087793j, 0.002543+0.015685j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_col_gga_ab_ks ________________________ self = def test_col_gga_ab_ks(self): mf_b3lyp = dft.UKS(mol).set(xc='b3lyp5') mf_b3lyp.__dict__.update(scf.chkfile.load(mf_lda.chkfile, 'scf')) > self._check_against_ab_ks(mf_b3lyp.TDDFT(), -0.4758219953792988, 0.17715631269859033) pyscf/x2c/test/test_tdscf.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/test/test_tdscf.py:143: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.406275j, 0.025926+0.027202j, 0.549662+0.247177j, 0.435322+0.067144j, 0.420368+0.993852j, 0.330335... , -0. -0.000001j, 0.086949+0.754588j], [-0. +0.j , -0.148039+0.004571j, -0.000012+0.000001j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ________________________ KnownValues.test_col_lda_ab_ks ________________________ self = def test_col_lda_ab_ks(self): > self._check_against_ab_ks(mf_lda.TDDFT(), -0.5231134770778959, 0.07879428138412828) pyscf/x2c/test/test_tdscf.py:96: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/test/test_tdscf.py:143: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.406275j, 0.025926+0.027202j, 0.549662+0.247177j, 0.435322+0.067144j, 0.420368+0.993852j, 0.330335... , -0. -0.000001j, 0.086949+0.754588j], [-0. +0.j , -0.148039+0.004571j, -0.000012+0.000001j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_col_mgga_ab_ks ________________________ self = def test_col_mgga_ab_ks(self): mf_m06l = dft.UKS(mol).run(xc='m06l', conv_tol=1e-12) mf_m06l.__dict__.update(scf.chkfile.load(mf_lda.chkfile, 'scf')) > self._check_against_ab_ks(mf_m06l.TDDFT(), -0.4919270127924622, 0.14597029880651433, places=5) pyscf/x2c/test/test_tdscf.py:106: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/test/test_tdscf.py:143: in _check_against_ab_ks self.assertAlmostEqual(abs(ax - ftda([x]).reshape(nocc,nvir)).max(), 0, 12) ^^^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0.435995+0.406275j, 0.025926+0.027202j, 0.549662+0.247177j, 0.435322+0.067144j, 0.420368+0.993852j, 0.330335... , -0. -0.000001j, 0.086949+0.754588j], [-0. +0.j , -0.148039+0.004571j, -0.000012+0.000001j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->xop', ['qo', 'xop']), ((1, 0), 'xop,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->xop', ['qo', 'xop']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________________ KnownValues.test_tda_lda ___________________________ self = def test_tda_lda(self): td = mf_lda.TDA() > es = td.kernel(nstates=5)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/x2c/test/test_tdscf.py:82: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/ghf.py:466: in kernel self.converged, self.e, x1 = lr_eigh( pyscf/tdscf/_lr_eig.py:110: in eigh axt = aop(xt) ^^^^^^^ pyscf/tdscf/ghf.py:88: in vind dms = lib.einsum('xov,pv,qo->xpq', zs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., ... , -0. -0.000001j, 0.086949+0.754588j], [-0. +0.j , -0.148039+0.004571j, -0.000012+0.000001j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError __________________________ KnownValues.test_tddft_lda __________________________ self = def test_tddft_lda(self): td = mf_lda.TDDFT() > es = td.kernel(nstates=4)[0] ^^^^^^^^^^^^^^^^^^^^ pyscf/x2c/test/test_tdscf.py:74: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/tdscf/ghf.py:616: in kernel self.converged, w, x1 = lr_eig( pyscf/tdscf/_lr_eig.py:339: in eig axt = aop(xt) ^^^^^^^ pyscf/tdscf/ghf.py:537: in vind dms = lib.einsum('xov,pv,qo->xpq', xs, orbv, orbo.conj()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'xov,pv,qo->xpq' tensors = [array([[[0., 0., 0., 0., 0., 0., 0., 0., 0.], [1., 0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., ... , -0. -0.000001j, 0.086949+0.754588j], [-0. +0.j , -0.148039+0.004571j, -0.000012+0.000001j]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pv,xov->oxp', ['qo', 'oxp']), ((1, 0), 'oxp,qo->xpq', ['xpq'])] contraction = ((1, 0), 'pv,xov->oxp', ['qo', 'oxp']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_ghf _____________________________ self = def test_ghf(self): # Test whether the result of spinor X2C is a solution of .GHF().x2c() mol = gto.M(atom='C', basis='ccpvdz-dk') ref = mol.DHF().x2c().run() c = numpy.vstack(mol.sph2spinor_coeff()) mo1 = c.dot(ref.mo_coeff) dm = ref.make_rdm1(mo1, ref.mo_occ) mf = mol.GHF().x2c1e() mf.max_cycle = 1 mf.kernel(dm0=dm) self.assertTrue(mf.converged) self.assertAlmostEqual(mf.e_tot, ref.e_tot, 9) > self.assertAlmostEqual(abs(mf.dip_moment() - ref.dip_moment()).max(), 0, 9) ^^^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c.py:217: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/x2c.py:793: in dip_moment ao_dip = self.with_x2c.picture_change((r, prp)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/x2c/x2c.py:362: in picture_change return lib.einsum('pi,xpq,qj->xij', c, pc_mat, c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ 0.000851, -0.000362, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ,... , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 1. ]], shape=(52, 28))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_gks _____________________________ self = def test_gks(self): mol = gto.M(atom='C', basis='ccpvdz-dk') ref = mol.DKS(xc='b3lyp').x2c().run() c = numpy.vstack(mol.sph2spinor_coeff()) mo1 = c.dot(ref.mo_coeff) dm = ref.make_rdm1(mo1, ref.mo_occ) mf = mol.GKS(xc='b3lyp').x2c1e() mf.max_cycle = 1 mf.kernel(dm0=dm) self.assertTrue(mf.converged) self.assertAlmostEqual(mf.e_tot, ref.e_tot, 9) > self.assertAlmostEqual(abs(mf.dip_moment() - ref.dip_moment()).max(), 0, 9) ^^^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c.py:230: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/x2c.py:793: in dip_moment ao_dip = self.with_x2c.picture_change((r, prp)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/x2c/x2c.py:362: in picture_change return lib.einsum('pi,xpq,qj->xij', c, pc_mat, c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ 0.000851, -0.000362, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ,... , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 1. ]], shape=(52, 28))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _______________________ KnownValues.test_picture_change ________________________ self = def test_picture_change(self): c = lib.param.LIGHT_SPEED myx2c = x2c.UHF(mol) myx2c.with_x2c.xuncontract = False def tv(with_x2c): xmol = with_x2c.get_xmol()[0] t = xmol.intor_symmetric('int1e_spsp_spinor') * .5 #v = xmol.intor_symmetric('int1e_nuc_spinor') w = xmol.intor_symmetric('int1e_spnucsp_spinor') return t, 'int1e_nuc_spinor', w t, v, w = tv(myx2c.with_x2c) h1 = myx2c.with_x2c.picture_change((v, w*(.5/c)**2-t), t) href = myx2c.with_x2c.get_hcore() self.assertAlmostEqual(abs(href - h1).max(), 0, 9) myx2c.with_x2c.xuncontract = True t, v, w = tv(myx2c.with_x2c) > h1 = myx2c.with_x2c.picture_change((v, w*(.5/c)**2-t), t) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c.py:104: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/x2c.py:228: in picture_change return lib.einsum('pi,pq,qj->ij', c.conj(), pc_mat, c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qj->ij' tensors = [array([[ 0.00071 , 0. , -0.000314, 0. , 0. , 0. , 0. , 0. , 0. , 0. ,... , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 1. ]], shape=(80, 48))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qj', 'iq']), ((1, 0), 'iq,qj->ij', ['ij'])] contraction = ((1, 0), 'pq,pi->iq', ['qj', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ___________________ KnownValues.test_sfx2c1e_picture_change ____________________ self = def test_sfx2c1e_picture_change(self): c = lib.param.LIGHT_SPEED myx2c = scf.RHF(mol).sfx2c1e() myx2c.with_x2c.xuncontract = False def tv(with_x2c): xmol = with_x2c.get_xmol()[0] t = xmol.intor_symmetric('int1e_kin') w = xmol.intor_symmetric('int1e_pnucp') return t, 'int1e_nuc', w t, v, w = tv(myx2c.with_x2c) h1 = myx2c.with_x2c.picture_change((v, w*(.5/c)**2-t), t) href = myx2c.with_x2c.get_hcore() self.assertAlmostEqual(abs(href - h1).max(), 0, 9) myx2c.with_x2c.xuncontract = True t, v, w = tv(myx2c.with_x2c) > h1 = myx2c.with_x2c.picture_change((v, w*(.5/c)**2-t), t) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c.py:132: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/sfx2c1e.py:242: in picture_change return lib.einsum('pi,pq,qj->ij', c, pc_mat, c) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,pq,qj->ij' tensors = [array([[ 0.00071 , -0.000314, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ,... , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 1. ]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'pq,pi->iq', ['qj', 'iq']), ((1, 0), 'iq,qj->ij', ['ij'])] contraction = ((1, 0), 'pq,pi->iq', ['qj', 'iq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_R1 ______________________________ self = def test_R1(self): with lib.light_speed(10) as c: R_1 = get_R(mol1) R_2 = get_R(mol2) R1_ref = (R_1 - R_2) / 0.0002 * lib.param.BOHR R1t = get_r1(mol, 0, 2) self.assertAlmostEqual(abs(R1t-R1_ref).max(), 0, 7) x0 = get_x0(mol) h0, s0 = get_h0_s0(mol) e0, c0 = scipy.linalg.eigh(h0, s0) get_h1_etc = sfx2c1e_grad._gen_first_order_quantities(mol, e0, c0, x0) > R1 = get_h1_etc(0)[6][2] ^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c_grad.py:241: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.343377, -0. , 0.002762, 0. , -0.056192, 0.002714, -0. , 0. , -0.001804, ... -0.007702, -0.013365, -0.104093, 0. , 0.105854, 0.182251, 0.067184, 1.037999, -1.431333]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_hfw _____________________________ self = def test_hfw(self): with lib.light_speed(10) as c: x2c_1 = sfx2c1e.SpinFreeX2C(mol1) x2c_2 = sfx2c1e.SpinFreeX2C(mol2) x2cobj = sfx2c1e.SpinFreeX2C(mol) fh_ref = (x2c_1.get_hcore() - x2c_2.get_hcore()) / 0.0002 * lib.param.BOHR fh = x2cobj.hcore_deriv_generator(deriv=1) > self.assertAlmostEqual(abs(fh(0)[2] - fh_ref).max(), 0, 7) ^^^^^ pyscf/x2c/test/test_x2c_grad.py:251: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/sfx2c1e_grad.py:42: in hcore_deriv h1 = get_h1_xmol(atm_id) ^^^^^^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:83: in hcore_deriv h1_ao, s1_ao, e1, c1, x1, s_nesc1, R1, c_fw1 = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ 0.817305, 0.075775, -0.002282, -0. , 0.00001 , 0. , -0.005511, -0.000072, -0. , 0. ,...05 , -0. , 0.211879, -0.578892, 0.265738, 0.385859, -0.278879, -0.064065, 0.002398]], shape=(42, 42))] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError _____________________________ KnownValues.test_x1 ______________________________ self = def test_x1(self): with lib.light_speed(10) as c: x_1 = get_x0(mol1) x_2 = get_x0(mol2) x1_ref = (x_1 - x_2) / 0.0002 * lib.param.BOHR x1t = get_x1(mol, 0) self.assertAlmostEqual(abs(x1t[2]-x1_ref).max(), 0, 7) x0 = get_x0(mol) h0, s0 = get_h0_s0(mol) e0, c0 = scipy.linalg.eigh(h0, s0) get_h1_etc = sfx2c1e_grad._gen_first_order_quantities(mol, e0, c0, x0) > x1 = get_h1_etc(0)[4] ^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c_grad.py:226: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.343377, -0. , 0.002762, 0. , -0.056192, 0.002714, -0. , 0. , -0.001804, ... -0.007702, -0.013365, -0.104093, 0. , 0.105854, 0.182251, 0.067184, 1.037999, -1.431333]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError ____________________________ KnownValues.test_hfw2 _____________________________ self = def test_hfw2(self): h1_deriv_1 = sfx2c1e_grad.gen_sf_hfw(mol1, approx='1E') h1_deriv_2 = sfx2c1e_grad.gen_sf_hfw(mol2, approx='1E') h2_deriv = sfx2c1e_hess.gen_sf_hfw(mol, approx='1E') > h2 = h2_deriv(0,0) ^^^^^^^^^^^^^ pyscf/x2c/test/test_x2c_hess.py:619: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pyscf/x2c/sfx2c1e_hess.py:195: in hcore_deriv h1i, s1i, e1i, c1i, x1i, s_nesc1i, R1i, c_fw1i = get_h1_etc(ia) ^^^^^^^^^^^^^^ pyscf/x2c/sfx2c1e_grad.py:180: in get_first_order h1mo = lib.einsum('pi,xpq,qj->xij', c0.conj(), h1ao, c0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ subscripts = 'pi,xpq,qj->xij' tensors = [array([[ -0.015852, -0.000214, -0. , -0.00037 , -0. , 0.000064, 0.612828, 0. , 0....535, -330.961442, 282.560628, -0.030734, -0.417454, -0.38756 , -0.82848 , 1.196839, -0.355285]])] kwargs = {}, contract = , optimize = True contraction_list = [((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']), ((1, 0), 'xiq,qj->xij', ['xij'])] contraction = ((1, 0), 'xpq,pi->xiq', ['qj', 'xiq']) def einsum(subscripts, *tensors, **kwargs): '''Perform a more efficient einsum via reshaping to a matrix multiply. Current differences compared to numpy.einsum: This assumes that each repeated index is actually summed (i.e. no 'i,i->i') and appears only twice (i.e. no 'ij,ik,il->jkl'). The output indices must be explicitly specified (i.e. 'ij,j->i' and not 'ij,j'). ''' contract = kwargs.pop('_contract', _contract) subscripts = subscripts.replace(' ','') if len(tensors) <= 1 or '...' in subscripts: out = _numpy_einsum(subscripts, *tensors, **kwargs) elif len(tensors) <= 2: out = _contract(subscripts, *tensors, **kwargs) else: optimize = kwargs.pop('optimize', True) tensors = list(tensors) contraction_list = _einsum_path(subscripts, *tensors, optimize=optimize, einsum_call=True)[1] for contraction in contraction_list: > inds, idx_rm, einsum_str, remaining = contraction[:4] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: not enough values to unpack (expected 4, got 3) pyscf/lib/numpy_helper.py:244: ValueError =============================== warnings summary =============================== pyscf/lib/gto/test/test_ecp.py:18 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/gto/test/test_ecp.py:18: DeprecationWarning: scipy.misc is deprecated and will be removed in 2.0.0 import scipy.misc pyscf/mp/mp2f12_slow.py:36 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/mp/mp2f12_slow.py:36: UserWarning: Module MP2-F12 is under testing warnings.warn('Module MP2-F12 is under testing') pyscf/solvent/test/test_cosmors.py:77 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/solvent/test/test_cosmors.py:77: SyntaxWarning: "\[" is an invalid escape sequence. Such sequences will not work in the future. Did you mean "\\["? A raw string is also an option. E_diel = float(re.search('Dielectric energy \[a.u.\] += +(-*\d+\.\d+)', text).group(1)) pyscf/solvent/ddpcm.py:37 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/solvent/ddpcm.py:37: UserWarning: Module ddPCM is under testing warnings.warn('Module ddPCM is under testing') pyscf/df/test/test_df_grad.py: 2 warnings pyscf/grad/test/test_casci.py: 1 warning pyscf/grad/test/test_casscf.py: 1 warning pyscf/grad/test/test_ccsd.py: 1 warning pyscf/grad/test/test_cisd.py: 1 warning pyscf/grad/test/test_mp2.py: 2 warnings pyscf/grad/test/test_tdrhf_grad.py: 1 warning pyscf/tdscf/test/test_tdrhf.py: 1 warning /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.RHF.run is deprecated and will be removed in a future release. Please use mol.RHF().run instead. warnings.warn( pyscf/df/test/test_df_grad.py::KnownValues::test_uks_gga_grad pyscf/df/test/test_df_grad.py::KnownValues::test_uks_lda_grad pyscf/df/test/test_df_hessian.py::KnownValues::test_uks_hess /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.UKS.run is deprecated and will be removed in a future release. Please use mol.UKS().run instead. warnings.warn( pyscf/df/test/test_df_grad.py::KnownValues::test_uks_gga_grad pyscf/df/test/test_df_hessian.py::KnownValues::test_uks_hess /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.UKS.density_fit is deprecated and will be removed in a future release. Please use mol.UKS().density_fit instead. warnings.warn( pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_gga_hess pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_lda_hess pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_mgga_hess pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_rsh_hess /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.RKS.run is deprecated and will be removed in a future release. Please use mol.RKS().run instead. warnings.warn( pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_gga_hess pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_lda_hess pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_mgga_hess pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_rsh_hess /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.RKS.density_fit is deprecated and will be removed in a future release. Please use mol.RKS().density_fit instead. warnings.warn( pyscf/dft/test/test_numint.py::KnownValues::test_eval_mat /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/dft/numint.py:636: UserWarning: Note the output of libxc.eval_xc cannot be directly used in eval_mat. vsigma from eval_xc should be restructured as (vsigma[:,0],vsigma[:,1]) warnings.warn('Note the output of libxc.eval_xc cannot be ' pyscf/fci/test/test_addons.py::KnownValues::test_cylindrical_init_guess /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/addons.py:103: UserWarning: Initial guess for cylindrical symmetry is under testing warnings.warn('Initial guess for cylindrical symmetry is under testing') pyscf/fci/test/test_direct_nosym.py::KnownValues::test_kernel /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/direct_nosym.py:208: UserWarning: direct_nosym.kernel is not able to diagonalize non-Hermitian Hamiltonian. If h1e and h2e is not hermtian, calling symmetric diagonalization in eig can lead to wrong results. warnings.warn('direct_nosym.kernel is not able to diagonalize ' pyscf/fci/test/test_selected_ci.py::KnownValues::test_cas_2_2 pyscf/fci/test/test_selected_ci.py::KnownValues::test_h8 pyscf/fci/test/test_selected_ci.py::KnownValues::test_spin_square /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci.py:700: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) ci1 *= .5 pyscf/fci/test/test_selected_ci.py::KnownValues::test_cas_2_2 pyscf/fci/test/test_selected_ci.py::KnownValues::test_cas_2_2 pyscf/fci/test/test_selected_ci.py::KnownValues::test_h8 pyscf/fci/test/test_selected_ci.py::KnownValues::test_h8 pyscf/fci/test/test_selected_ci.py::KnownValues::test_spin_square pyscf/fci/test/test_selected_ci.py::KnownValues::test_spin_square /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci.py:701: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) ci1 += (neleca-nelecb)**2*.25*ci_coeff pyscf/fci/test/test_selected_ci.py::KnownValues::test_contract_2e_1 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/test/test_selected_ci.py:134: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) self.assertAlmostEqual(float(abs(c1-c2).sum()), 0, 9) pyscf/fci/test/test_selected_ci.py: 13 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:66: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1[a,i,str1] += sign * fcivec[str0] pyscf/fci/test/test_selected_ci.py::KnownValues::test_contract_2e_vs_slow_version /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:67: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) fcinew += numpy.einsum('ps,psab->ab', h_ps, t1) # (*) pyscf/fci/test/test_selected_ci.py: 15 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:73: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) fcinew[:,str0] += sign * t1[a,i,:,str1] pyscf/fci/test/test_selected_ci.py: 15 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:80: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1[a,i,:,str1] += sign * fcivec[:,str0] pyscf/fci/test/test_selected_ci.py::KnownValues::test_contract_2e_vs_slow_version /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:81: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) fcinew += numpy.einsum('ps,psab->ab', h_ps, t1) # (*) pyscf/fci/test/test_selected_ci.py: 13 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:87: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) fcinew[str0] += sign * t1[a,i,str1] pyscf/fci/test/test_selected_ci.py: 18 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:95: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1[i,j,str1] += sign * fcivec[str0] pyscf/fci/test/test_selected_ci.py: 18 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:101: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) fcinew[str0] += sign * t1[i,j,str1] pyscf/fci/test/test_selected_ci.py: 18 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:108: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1[i,j,:,str1] += sign * fcivec[:,str0] pyscf/fci/test/test_selected_ci.py: 18 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:114: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) fcinew[:,str0] += sign * t1[i,j,:,str1] pyscf/fci/test/test_selected_ci.py::KnownValues::test_contract_2e_vs_slow_version /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/test/test_selected_ci.py:466: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) self.assertAlmostEqual(abs(ci1-ciref).max(), 0, 12) pyscf/fci/test/test_selected_ci.py::KnownValues::test_enlarge_space /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/test/test_selected_ci.py:106: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) self.assertAlmostEqual(abs(cic[[0,1,5]][:,[0,1,2]] - ci_coeff).sum(), 0, 12) pyscf/fci/test/test_selected_ci.py::KnownValues::test_from_to_fci /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/test/test_selected_ci.py:285: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) self.assertAlmostEqual(abs(ci1-ci_coeff).sum(), 0, 12) pyscf/fci/test/test_selected_ci.py::KnownValues::test_guess_wfnsym /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/addons.py:279: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) idx = abs(ci).argmax() pyscf/fci/test/test_selected_ci.py::KnownValues::test_guess_wfnsym pyscf/fci/test/test_selected_ci.py::KnownValues::test_guess_wfnsym pyscf/fci/test/test_selected_ci.py::KnownValues::test_guess_wfnsym pyscf/fci/test/test_selected_ci.py::KnownValues::test_kernel_symm /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_symm.py:199: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) if all(abs(c.reshape(na, nb)[mask]).max() < 1e-5 for c in fcivec): pyscf/fci/test/test_selected_ci.py::KnownValues::test_h8 pyscf/fci/test/test_selected_ci.py::KnownValues::test_h8 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci.py:798: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) addra, addrb = numpy.where(abs(ci) > tol) pyscf/fci/test/test_selected_ci.py::KnownValues::test_kernel /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_spin0.py:83: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) abs_ci = abs(ci0).max(axis=0) pyscf/fci/test/test_selected_ci.py::KnownValues::test_kernel_symm /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/addons.py:249: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) ci1 *= 1/numpy.linalg.norm(ci1) pyscf/fci/test/test_selected_ci.py: 13 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:380: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1a[a,i,str1] += sign * fcivec[str0] pyscf/fci/test/test_selected_ci.py: 15 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:384: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1b[a,i,:,str1] += sign * fcivec[:,str0] pyscf/fci/test/test_selected_ci.py: 18 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:395: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1a[i,j,str1] += sign * fcivec[str0] pyscf/fci/test/test_selected_ci.py: 18 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/fci/selected_ci_slow.py:404: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0) t1b[i,j,:,str1] += sign * fcivec[:,str0] pyscf/gto/test/test_basis_parser.py::KnownValues::test_basis_load /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/basis/__init__.py:660: UserWarning: Basis may be available in basis-set-exchange. It is recommended to install basis-set-exchange: pip install basis-set-exchange warnings.warn( pyscf/gto/test/test_ecp.py::KnownValues::test_pp_int pyscf/pbc/scf/test/test_hf.py::KnownValues::test_rhf_0d_inf_vacuum /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/moleintor.py:283: UserWarning: Function int1e_r2_origi_sph not found. Set its comp to 1 warnings.warn('Function %s not found. Set its comp to 1' % intor_name) pyscf/gto/test/test_ecp.py::KnownValues::test_pp_int pyscf/pbc/scf/test/test_hf.py::KnownValues::test_rhf_0d_inf_vacuum /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/moleintor.py:283: UserWarning: Function int1e_r4_origi_sph not found. Set its comp to 1 warnings.warn('Function %s not found. Set its comp to 1' % intor_name) pyscf/gto/test/test_mole.py::KnownValues::test_format_basis pyscf/gto/test/test_mole.py::KnownValues::test_uncontract /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:537: UserWarning: For basis with kappa != 0, the uncontract basis might be wrong. Please double check the resultant attribute mol._basis warnings.warn('For basis with kappa != 0, the uncontract basis might be wrong. ' pyscf/gto/test/test_moleintor.py::KnownValues::test_unknonw /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/moleintor.py:283: UserWarning: Function int4c3e_sph not found. Set its comp to 1 warnings.warn('Function %s not found. Set its comp to 1' % intor_name) pyscf/hessian/test/test_thermo.py::KnownValues::test_thermo /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.HF.run is deprecated and will be removed in a future release. Please use mol.HF().run instead. warnings.warn( pyscf/lib/test/test_linalg_helper.py::KnownValues::test_eig2 /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/lib/linalg_helper.py:926: UserWarning: Left eigenvectors from subspace diagonalization method may not be converged warnings.warn('Left eigenvectors from subspace diagonalization method may not be converged') pyscf/pbc/dft/test/test_rks.py::KnownValues::test_chkfile_k_point /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/pbc/gto/cell.py:1757: UserWarning: .nimgs is a deprecated attribute. It is replaced by .rcut attribute for lattice sum cutoff radius. The given nimgs [2, 2, 2] is far over the estimated cutoff radius 0.01. warnings.warn(msg) pyscf/pbc/gto/pseudo/test/test_pp.py: 128000 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/pbc/gto/pseudo/pp.py:213: DeprecationWarning: `scipy.special.sph_harm` is deprecated as of SciPy 1.15.0 and will be removed in SciPy 1.17.0. Please use `scipy.special.sph_harm_y` instead. return scipy.special.sph_harm(m,l,phi,theta) pyscf/pbc/gto/test/test_rcut.py::KnownValues::test_lattice_Ls_low_dim /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/pbc/gto/cell.py:1315: UserWarning: Electron number 1 and spin 0 are not consistent in cell warnings.warn('Electron number %d and spin %d are not consistent ' pyscf/pbc/symm/test/test_basis.py::KnownValues::test_C2h_symorb /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/pbc/gto/cell.py:1315: UserWarning: Electron number 29 and spin 0 are not consistent in cell warnings.warn('Electron number %d and spin %d are not consistent ' pyscf/pbc/tools/test/test_k2gamma.py::KnownValues::test_double_translation_indices pyscf/pbc/tools/test/test_k2gamma.py::KnownValues::test_k2gamma /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/pbc/gto/cell.py:1315: UserWarning: Electron number 3 and spin 0 are not consistent in cell warnings.warn('Electron number %d and spin %d are not consistent ' pyscf/pbc/tools/test/test_pbc.py::KnownValues::test_coulG_ws /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/pbc/tools/pbc.py:294: UserWarning: cell.gs is deprecated. It is replaced by cell.mesh,the number of PWs (=2*gs+1) along each direction. warnings.warn('cell.gs is deprecated. It is replaced by cell.mesh,' pyscf/solvent/test/test_ddcosmo.py: 700 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/solvent/test/test_ddcosmo.py:303: DeprecationWarning: `scipy.special.sph_harm` is deprecated as of SciPy 1.15.0 and will be removed in SciPy 1.17.0. Please use `scipy.special.sph_harm_y` instead. ylm[l] = scipy.special.sph_harm(0, l, theta, varphi).real pyscf/solvent/test/test_ddcosmo.py: 2100 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/solvent/test/test_ddcosmo.py:305: DeprecationWarning: `scipy.special.sph_harm` is deprecated as of SciPy 1.15.0 and will be removed in SciPy 1.17.0. Please use `scipy.special.sph_harm_y` instead. f1 = scipy.special.sph_harm(-m, l, theta, varphi) pyscf/solvent/test/test_ddcosmo.py: 2100 warnings /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/solvent/test/test_ddcosmo.py:306: DeprecationWarning: `scipy.special.sph_harm` is deprecated as of SciPy 1.15.0 and will be removed in SciPy 1.17.0. Please use `scipy.special.sph_harm_y` instead. f2 = scipy.special.sph_harm( m, l, theta, varphi) pyscf/tdscf/test/test_tduhf.py::KnownValues::test_symmetry_init_guess /builddir/build/BUILD/python-pyscf-2.11.0-build/pyscf-2.11.0/pyscf/gto/mole.py:4345: DeprecationWarning: The API mol.UHF.run is deprecated and will be removed in a future release. Please use mol.UHF().run instead. warnings.warn( -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html =========================== short test summary info ============================ FAILED pyscf/adc/test/test_radc/test_ea_H2O.py::KnownValues::test_ea_adc2 - V... FAILED pyscf/adc/test/test_radc/test_ea_H2O.py::KnownValues::test_ea_adc2x - ... FAILED pyscf/adc/test/test_radc/test_ea_H2O.py::KnownValues::test_ea_adc3 - V... FAILED pyscf/adc/test/test_radc/test_ea_N2.py::KnownValues::test_ea_adc2 - Va... FAILED pyscf/adc/test/test_radc/test_ea_N2.py::KnownValues::test_ea_adc2x - V... FAILED pyscf/adc/test/test_radc/test_ea_N2.py::KnownValues::test_ea_adc3 - Va... FAILED pyscf/adc/test/test_radc/test_ee_H2O.py::KnownValues::test_ee_adc3 - V... FAILED pyscf/adc/test/test_radc/test_ee_N2.py::KnownValues::test_ee_adc3 - Va... FAILED pyscf/adc/test/test_radc/test_ee_df_H2O.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_radc/test_ee_df_N2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_radc/test_ee_outcore_H2O.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_radc/test_ip_H2O.py::KnownValues::test_ip_adc2 - V... FAILED pyscf/adc/test/test_radc/test_ip_H2O.py::KnownValues::test_ip_adc2x - ... FAILED pyscf/adc/test/test_radc/test_ip_H2O.py::KnownValues::test_ip_adc3 - V... FAILED pyscf/adc/test/test_radc/test_ip_N2.py::KnownValues::test_ip_adc2 - Va... FAILED pyscf/adc/test/test_radc/test_ip_N2.py::KnownValues::test_ip_adc2x - V... FAILED pyscf/adc/test/test_radc/test_ip_N2.py::KnownValues::test_ip_adc3 - Va... FAILED pyscf/adc/test/test_radc/test_ip_cvs_H2O.py::KnownValues::test_ip_adc3 FAILED pyscf/adc/test/test_radc/test_ip_cvs_N2.py::KnownValues::test_ip_adc3 FAILED pyscf/adc/test/test_radc/test_ip_ea_df_N2.py::KnownValues::test_dfadc3_ip FAILED pyscf/adc/test/test_radc/test_ip_outcore_H2O.py::KnownValues::test_ip_adc3 FAILED pyscf/adc/test/test_uadc/test_approx_trans_moments_CN.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ea_N2.py::KnownValues::test_ea_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ea_OH.py::KnownValues::test_ea_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ea_P.py::KnownValues::test_ea_adc3 - Val... FAILED pyscf/adc/test/test_uadc/test_ee_CN.py::KnownValues::test_ee_adc2 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_CN.py::KnownValues::test_ee_adc2x - V... FAILED pyscf/adc/test/test_uadc/test_ee_CN.py::KnownValues::test_ee_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_F2.py::KnownValues::test_ee_adc2 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_F2.py::KnownValues::test_ee_adc2x - V... FAILED pyscf/adc/test/test_uadc/test_ee_F2.py::KnownValues::test_ee_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_H2O.py::KnownValues::test_ee_adc2 - V... FAILED pyscf/adc/test/test_uadc/test_ee_H2O.py::KnownValues::test_ee_adc2x - ... FAILED pyscf/adc/test/test_uadc/test_ee_H2O.py::KnownValues::test_ee_adc3 - V... FAILED pyscf/adc/test/test_uadc/test_ee_O2.py::KnownValues::test_ee_adc2 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_O2.py::KnownValues::test_ee_adc2x - V... FAILED pyscf/adc/test/test_uadc/test_ee_O2.py::KnownValues::test_ee_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_OH.py::KnownValues::test_ee_adc2 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_OH.py::KnownValues::test_ee_adc2x - V... FAILED pyscf/adc/test/test_uadc/test_ee_OH.py::KnownValues::test_ee_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ee_df_CN.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_CN.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_CN.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_df_F2.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_F2.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_F2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_df_H2O.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_H2O.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_H2O.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_df_O2.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_O2.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_O2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_df_OH.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_OH.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_OH.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_rohf_O2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_df_rohf_OH.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_F2.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_F2.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_outcore_F2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_outcore_H2O.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_O2.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_O2.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_outcore_O2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_OH.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_OH.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_outcore_OH.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_outcore_rohf_OH.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_rohf_CN.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_rohf_CN.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_rohf_CN.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_rohf_O2.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_rohf_O2.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_rohf_O2.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ee_rohf_OH.py::KnownValues::test_ee_adc2 FAILED pyscf/adc/test/test_uadc/test_ee_rohf_OH.py::KnownValues::test_ee_adc2x FAILED pyscf/adc/test/test_uadc/test_ee_rohf_OH.py::KnownValues::test_ee_adc3 FAILED pyscf/adc/test/test_uadc/test_ip_OH.py::KnownValues::test_ip_adc3 - Va... FAILED pyscf/adc/test/test_uadc/test_ip_OH.py::KnownValues::test_ip_adc3_oneroot FAILED pyscf/adc/test/test_uadc/test_ip_P.py::KnownValues::test_ip_adc3 - Val... FAILED pyscf/adc/test/test_uadc/test_ip_cvs_OH.py::KnownValues::test_ip_adc3 FAILED pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py::KnownValues::test_ea_dfadc3 FAILED pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py::KnownValues::test_hf_dfadc3_ip FAILED pyscf/adc/test/test_uadc/test_ip_ea_df_OH.py::KnownValues::test_ip_dfadc3_dif_aux_basis FAILED pyscf/ao2mo/test/test_incore.py::KnownValues::test_incore - ValueError... FAILED pyscf/ao2mo/test/test_nrr_outcore.py::KnownValues::test_nrr_ghf - Valu... FAILED pyscf/ao2mo/test/test_nrr_outcore.py::KnownValues::test_nrr_spinor - V... FAILED pyscf/ao2mo/test/test_r_outcore.py::KnownValues::test_ao2mo_r_e2 - Val... FAILED pyscf/ao2mo/test/test_semi_incore.py::KnowValues::test_general - Value... FAILED pyscf/ao2mo/test/test_semi_incore.py::KnowValues::test_general_complex FAILED pyscf/cc/test/test_2e.py::KnownValues::test_ccsd - ValueError: not eno... FAILED pyscf/cc/test/test_addons.py::KnownValues::test_bccd_kernel_ - ValueEr... FAILED pyscf/cc/test/test_ccd.py::KnownValues::test_rdm - ValueError: not eno... FAILED pyscf/cc/test/test_ccsd_lambda.py::KnownValues::test_ccsd - ValueError... FAILED pyscf/cc/test/test_ccsd_lambda.py::KnownValues::test_restart - ValueEr... FAILED pyscf/cc/test/test_ccsd_t.py::KnownValues::test_ccsd_t_rdm - ValueErro... FAILED pyscf/cc/test/test_dfccsd.py::KnownValues::test_df_eaccsd - ValueError... FAILED pyscf/cc/test/test_dfccsd.py::KnownValues::test_df_eaccsd_koopmans - V... FAILED pyscf/cc/test/test_dfccsd.py::KnownValues::test_df_eaccsd_partition - ... FAILED pyscf/cc/test/test_dfccsd.py::KnownValues::test_df_ipccsd - ValueError... FAILED pyscf/cc/test/test_dfccsd.py::KnownValues::test_df_ipccsd_koopmans - V... FAILED pyscf/cc/test/test_dfccsd.py::KnownValues::test_df_ipccsd_partition - ... FAILED pyscf/cc/test/test_fno_uhf.py::Water::test_fno_by_thresh - ValueError:... FAILED pyscf/cc/test/test_fno_uhf.py::Water::test_fno_by_thresh_frozen - Valu... FAILED pyscf/cc/test/test_gccsd_lambda.py::KnownValues::test_gccsd_t_lambda FAILED pyscf/cc/test/test_h2o.py::KnownValues::test_ccsd_lambda - ValueError:... FAILED pyscf/cc/test/test_h2o.py::KnownValues::test_ccsd_rdm - ValueError: no... FAILED pyscf/cc/test/test_rccsd_lambda.py::KnownValues::test_rdm - ValueError... FAILED pyscf/cc/test/test_rccsd_lambda.py::KnownValues::test_rdm_trace - Valu... FAILED pyscf/cc/test/test_rccsd_lambda.py::KnownValues::test_update_lambda_complex FAILED pyscf/cc/test/test_rccsd_lambda.py::KnownValues::test_update_lambda_real FAILED pyscf/cc/test/test_rccsd_t_lambda.py::KnownValues::test_lambda_intermediates_real FAILED pyscf/cc/test/test_rccsd_t_lambda.py::KnownValues::test_rdm_intermediates_real FAILED pyscf/cc/test/test_uccsd_lambda.py::KnownValues::test_update_lambda_complex FAILED pyscf/cc/test/test_uccsd_lambda.py::KnownValues::test_update_lambda_real FAILED pyscf/ci/test/test_cisd.py::KnownValues::test_overlap - ValueError: no... FAILED pyscf/ci/test/test_ucisd.py::KnownValues::test_overlap - ValueError: n... FAILED pyscf/ci/test/test_ucisd.py::KnownValues::test_with_df_s0 - ValueError... FAILED pyscf/ci/test/test_ucisd.py::KnownValues::test_with_df_s2 - ValueError... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_casscf_grad - ValueEr... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_rhf_grad - ValueError... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_rks_gga_grad - ValueE... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_rks_lda_grad - ValueE... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_rks_mgga_grad - Value... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_rks_rsh_grad - ValueE... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_sacasscf_grad - Value... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_uhf_grad - ValueError... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_uks_gga_grad - ValueE... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_uks_lda_grad - ValueE... FAILED pyscf/df/test/test_df_grad.py::KnownValues::test_uks_rsh_grad - ValueE... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_rhf_hess - ValueEr... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_gga_hess - Val... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_lda_hess - Val... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_mgga_hess - Va... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_rks_rsh_hess - Val... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_uhf_hess - ValueEr... FAILED pyscf/df/test/test_df_hessian.py::KnownValues::test_uks_hess - ValueEr... FAILED pyscf/dft/test/test_numint.py::KnownValues::test_rsh_omega - TypeError... FAILED pyscf/fci/test/test_spin1_cyl_sym.py::KnownValues::test_contract_2e - ... FAILED pyscf/fci/test/test_spin1_cyl_sym.py::KnownValues::test_contract_2e_1 FAILED pyscf/fci/test/test_spin1_cyl_sym.py::KnownValues::test_linearmole_a2 FAILED pyscf/fci/test/test_spin1_cyl_sym.py::KnownValues::test_spin1_cyl_sym FAILED pyscf/fci/test/test_spin1_cyl_sym.py::KnownValues::test_triplet_degeneracy FAILED pyscf/fci/test/test_spin1_cyl_sym.py::KnownValues::test_wrong_initial_guess FAILED pyscf/fci/test/test_spin_op.py::KnownValues::test_spin_squre - ValueEr... FAILED pyscf/grad/test/test_casci.py::KnownValues::test_casci_grad - ValueErr... FAILED pyscf/grad/test/test_casci.py::KnownValues::test_casci_grad_excited_state FAILED pyscf/grad/test/test_casci.py::KnownValues::test_casci_grad_with_ccsd_solver FAILED pyscf/grad/test/test_casci.py::KnownValues::test_scanner - ValueError:... FAILED pyscf/grad/test/test_casci.py::KnownValues::test_small_mem - ValueErro... FAILED pyscf/grad/test/test_casci.py::KnownValues::test_state_average_mix_scanner FAILED pyscf/grad/test/test_casci.py::KnownValues::test_state_average_scanner FAILED pyscf/grad/test/test_casci.py::KnownValues::test_state_specific_scanner FAILED pyscf/grad/test/test_casci.py::KnownValues::test_symmetrize - ValueErr... FAILED pyscf/grad/test/test_casci.py::KnownValues::test_with_qmmm_scanner - V... FAILED pyscf/grad/test/test_casci.py::KnownValues::test_with_x2c_scanner - Va... FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_casscf_grad - ValueE... FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_df_casscf_grad - Val... FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_df_state_average_scanner FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_scanner - ValueError... FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_state_average_mix_scanner FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_state_average_scanner FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_state_average_scanner_spin_penalty FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_state_specific_scanner FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_symmetrize - ValueEr... FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_with_qmmm_scanner - ... FAILED pyscf/grad/test/test_casscf.py::KnownValues::test_with_x2c_scanner - V... FAILED pyscf/grad/test/test_ccsd.py::KnownValues::test_ccsd_frozen - ValueErr... FAILED pyscf/grad/test/test_ccsd.py::KnownValues::test_ccsd_grad - ValueError... FAILED pyscf/grad/test/test_ccsd.py::KnownValues::test_rdm2_mo2ao - ValueErro... FAILED pyscf/grad/test/test_ccsd.py::KnownValues::test_symmetrize - ValueErro... FAILED pyscf/grad/test/test_ccsd.py::KnownValues::test_with_qmmm_scanner - Va... FAILED pyscf/grad/test/test_ccsd.py::KnownValues::test_with_x2c_scanner - Val... FAILED pyscf/grad/test/test_ccsd_t.py::KnownValues::test_ccsd_t_frozen - Valu... FAILED pyscf/grad/test/test_ccsd_t.py::KnownValues::test_ccsd_t_grad - ValueE... FAILED pyscf/grad/test/test_cmspdft.py::KnownValues::test_diab_grad_sanity - ... FAILED pyscf/grad/test/test_h2o.py::KnownValues::test_ccsd - ValueError: not ... FAILED pyscf/grad/test/test_hf.py::KnownValues::test_ccsd - ValueError: not e... FAILED pyscf/grad/test/test_hf.py::KnownValues::test_ccsd_scanner - ValueErro... FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_dfrohf_sanity - Value... FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_hhe_lin2ftlda22_631g_slow FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_hhe_lin2ftlda24_631g_slow FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_hhe_lin3ftlda22_631g_slow FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_lih_lin2ftlda22_sto3g_slow FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_lih_lin2ftlda46_sto3g_slow FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_lih_lin2ftpbe22_sto3g FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_lih_lin2ftpbe22_sto3g_df FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_lih_lin3ftlda22_sto3g_slow FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_grad_scanner - ValueE... FAILED pyscf/grad/test/test_lpdft.py::KnownValues::test_rohf_sanity - ValueEr... FAILED pyscf/grad/test/test_mcpdft.py::KnownValues::test_gradients - ValueErr... FAILED pyscf/grad/test/test_mcpdft.py::KnownValues::test_scanner - ValueError... FAILED pyscf/grad/test/test_mcpdft.py::KnownValues::test_triplet_mol - ValueE... FAILED pyscf/grad/test/test_mcpdft.py::KnownValues::test_triplet_mol_df - Val... FAILED pyscf/grad/test/test_metagga_mcpdft.py::KnownValues::test_grad_lih_sa2mc2322_sto3g FAILED pyscf/grad/test/test_metagga_mcpdft.py::KnownValues::test_grad_lih_sa2mc2322_sto3g_df FAILED pyscf/grad/test/test_metagga_mcpdft.py::KnownValues::test_grad_lih_sa2tm06l22_sto3g FAILED pyscf/grad/test/test_metagga_mcpdft.py::KnownValues::test_grad_lih_ssmc2322_sto3g FAILED pyscf/grad/test/test_metagga_mcpdft.py::KnownValues::test_grad_lih_sstm06l22_sto3g FAILED pyscf/grad/test/test_mp2.py::KnownValues::test_with_x2c_scanner - Valu... FAILED pyscf/grad/test/test_mspdft.py::KnownValues::test_offdiag_grad_sanity FAILED pyscf/grad/test/test_mspdft.py::KnownValues::test_scanner - ValueError... FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_dfrohf_sanity FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_h2_cms2ftlda22_631g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_h2_cms2ftlda22_sto3g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_h2_cms3ftlda22_631g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_h2_cms3ftlda22_sto3g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_lih_cms2ftlda22_sto3g_df FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_lih_cms2ftlda22_sto3g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_lih_cms2ftlda44_sto3g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_lih_cms2ftpbe22_sto3g FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_lih_cms2tm06l22_sto3g FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_grad_lih_cms3ftlda22_sto3g_slow FAILED pyscf/grad/test/test_pdft_diatomic_gradients.py::KnownValues::test_rohf_sanity FAILED pyscf/grad/test/test_pdft_h2co.py::KnownValues::test_sa - ValueError: ... FAILED pyscf/grad/test/test_pdft_h2co.py::KnownValues::test_ss - ValueError: ... FAILED pyscf/grad/test/test_rhf.py::KnownValues::test_df_rhf_grad - ValueErro... FAILED pyscf/grad/test/test_rhf.py::KnownValues::test_finite_diff_df_rhf_grad FAILED pyscf/grad/test/test_rhf.py::KnownValues::test_finite_diff_x2c_rhf_grad FAILED pyscf/grad/test/test_rhf.py::KnownValues::test_x2c_rhf_grad - ValueErr... FAILED pyscf/grad/test/test_rks.py::KnownValues::test_finite_diff_df_rks_grad FAILED pyscf/grad/test/test_rohf.py::KnownValues::test_finite_diff_df_rohf_grad FAILED pyscf/grad/test/test_roks.py::KnownValues::test_finite_diff_df_roks_grad FAILED pyscf/grad/test/test_tdrhf_grad.py::KnownValues::test_symmetrize - Val... FAILED pyscf/grad/test/test_tdrhf_grad.py::KnownValues::test_tda_singlet - Va... FAILED pyscf/grad/test/test_tdrhf_grad.py::KnownValues::test_tda_triplet - Va... FAILED pyscf/grad/test/test_tdrhf_grad.py::KnownValues::test_tdhf_singlet - V... FAILED pyscf/grad/test/test_tdrhf_grad.py::KnownValues::test_tdhf_triplet - V... FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tda_singlet_b3lyp_xcfun FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tda_singlet_b88 FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tda_singlet_lda FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tda_singlet_mgga FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tda_triplet_b3lyp FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tda_triplet_lda FAILED pyscf/grad/test/test_tdrks_grad.py::KnownValues::test_tddft_lda - Valu... FAILED pyscf/grad/test/test_tduhf_grad.py::KnownValues::test_tda - ValueError... FAILED pyscf/grad/test/test_tduhf_grad.py::KnownValues::test_tdhf - ValueErro... FAILED pyscf/grad/test/test_tduks_grad.py::KnownValues::test_custom_xc - Valu... FAILED pyscf/grad/test/test_tduks_grad.py::KnownValues::test_range_separated FAILED pyscf/grad/test/test_tduks_grad.py::KnownValues::test_tda_b88 - ValueE... FAILED pyscf/grad/test/test_tduks_grad.py::KnownValues::test_tda_lda - ValueE... FAILED pyscf/grad/test/test_tduks_grad.py::KnownValues::test_tddft_b3lyp - Va... FAILED pyscf/grad/test/test_tduks_grad.py::KnownValues::test_tddft_lda - Valu... FAILED pyscf/grad/test/test_uhf.py::KnownValues::test_finite_diff_df_uhf_grad FAILED pyscf/grad/test/test_uks.py::KnownValues::test_finite_diff_df_uks_grad FAILED pyscf/grad/test/test_ump2.py::KnownValues::test_as_scanner - ValueErro... FAILED pyscf/grad/test/test_ump2.py::KnownValues::test_frozen - ValueError: n... FAILED pyscf/grad/test/test_ump2.py::KnownValues::test_mp2_grad - ValueError:... FAILED pyscf/grad/test/test_ump2.py::KnownValues::test_mp2_grad_finite_diff FAILED pyscf/gw/test/test_gw.py::KnownValues::test_gw_exact - ValueError: not... FAILED pyscf/hessian/test/test_rhf.py::KnownValues::test_finite_diff_x2c_rhf_hess FAILED pyscf/hessian/test/test_vv10_hessian.py::KnownValues::test_vv10_only_hessian_density_fitting FAILED pyscf/hessian/test/test_vv10_hessian.py::KnownValues::test_wb97xv_hessian FAILED pyscf/lib/test/test_einsum.py::KnownValues::test_3operands - ValueErro... FAILED pyscf/lib/test/test_einsum.py::KnownValues::test_3operands1 - ValueErr... FAILED pyscf/lib/test/test_einsum.py::KnownValues::test_3operands2 - ValueErr... FAILED pyscf/lib/test/test_einsum.py::KnownValues::test_4operands - ValueErro... FAILED pyscf/lo/test/test_ibo.py::KnownValues::test_ibo_PM - ValueError: not ... FAILED pyscf/lo/test/test_localizer.py::KnownValues::test_pipek - ValueError:... FAILED pyscf/lo/test/test_localizer.py::KnownValues::test_pipek_becke_scheme FAILED pyscf/lo/test/test_localizer.py::KnownValues::test_pipek_exp4 - ValueE... FAILED pyscf/lo/test/test_pipek.py::Water::test_grad_hess - ValueError: not e... FAILED pyscf/lo/test/test_vvo.py::KnownValues::test_livvo_PM - ValueError: no... FAILED pyscf/mcpdft/test/test_cmspdft.py::KnownValues::test_lih_cms2ftlda22 FAILED pyscf/mcpdft/test/test_cmspdft.py::KnownValues::test_lih_cms2mc2322 - ... FAILED pyscf/mcpdft/test/test_cmspdft.py::KnownValues::test_scanner - ValueEr... FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_h2_cms2ftlda22_631g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_h2_cms2ftlda22_sto3g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_h2_cms3ftlda22_631g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_h2_cms3ftlda22_sto3g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_lih_cms2ftlda22_sto3g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_lih_cms2ftlda22_sto3g_df FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_lih_cms2ftlda44_sto3g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_lih_cms2ftpbe22_sto3g FAILED pyscf/mcpdft/test/test_diatomic_energies.py::KnownValues::test_lih_cms3ftlda22_sto3g FAILED pyscf/mcscf/test/test_addons.py::KnownValues::test_make_natural_orbitals_from_restricted FAILED pyscf/mcscf/test/test_addons.py::KnownValues::test_make_natural_orbitals_from_unrestricted FAILED pyscf/md/test/test_velocverlet.py::KnownValues::test_ss_s0_ethylene_zero_init_veloc FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_fock_response - ... FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_memory - ValueEr... FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_natorbs_relaxed FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_natorbs_relaxed_fc FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_natorbs_relaxed_fclist FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_scs_natorbs_relaxed FAILED pyscf/mp/test/test_dfmp2_native.py::KnownValues::test_solve_cphf - Val... FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_memory - ValueE... FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_natorbs - Value... FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_natorbs_fc - Va... FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_natorbs_fclist FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_natorbs_relaxed FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_natorbs_relaxed_fc FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_natorbs_relaxed_fclist FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_scs_natorbs - V... FAILED pyscf/mp/test/test_dfump2_native.py::KnownValues::test_scs_natorbs_relaxed FAILED pyscf/mp/test/test_mp2.py::KnownValues::test_mp2_dm - ValueError: not ... FAILED pyscf/nac/test/test_cmspdft.py::KnownValues::test_nac_h2_cms2ftlsda22_631g FAILED pyscf/nac/test/test_cmspdft.py::KnownValues::test_nac_h2_cms2ftlsda22_sto3g FAILED pyscf/nac/test/test_cmspdft.py::KnownValues::test_nac_h2_cms3ftlsda22_631g FAILED pyscf/nac/test/test_cmspdft.py::KnownValues::test_nac_h2_cms3ftlsda22_sto3g FAILED pyscf/nac/test/test_cmspdft.py::KnownValues::test_nac_lih_cms2ftlsda22_sto3g FAILED pyscf/nac/test/test_cmspdft.py::KnownValues::test_nac_lih_cms3ftlsda22_sto3g FAILED pyscf/nac/test/test_sacasscf.py::KnownValues::test_nac_h2_sa2caasf22_631g FAILED pyscf/nac/test/test_sacasscf.py::KnownValues::test_nac_h2_sa2casscf22_sto3g FAILED pyscf/nac/test/test_sacasscf.py::KnownValues::test_nac_h2_sa3casscf22_631g FAILED pyscf/nac/test/test_sacasscf.py::KnownValues::test_nac_h2_sa3casscf22_sto3g FAILED pyscf/nac/test/test_sacasscf.py::KnownValues::test_nac_lih_cms3ftlda22_sto3g FAILED pyscf/nac/test/test_sacasscf.py::KnownValues::test_nac_lih_sa2casscf22_sto3g FAILED pyscf/pbc/adc/test/test_k_vs_supercell_ea.py::KnownValues::test_ea_adc3_supercell_vs_k FAILED pyscf/pbc/cc/test/test_eom_kgccsd_diag.py::KnownValues::test_he_112_diag FAILED pyscf/pbc/cc/test/test_eom_kgccsd_diag.py::KnownValues::test_he_131_diag FAILED pyscf/pbc/cc/test/test_eom_kgccsd_diag.py::KnownValues::test_supercell_vs_kpt FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_eomea_l_matvec FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_eomea_matvec FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_n3_diffuse - V... FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_n3_diffuse_Ta FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_n3_diffuse_Ta_against_so FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_n3_diffuse_frozen FAILED pyscf/pbc/cc/test/test_eom_krccsd.py::KnownValues::test_n3_ee - ValueE... FAILED pyscf/pbc/cc/test/test_eom_kuccsd.py::KnownValues::test_eomea_matvec FAILED pyscf/pbc/cc/test/test_eom_kuccsd.py::KnownValues::test_n3_diffuse - V... FAILED pyscf/pbc/cc/test/test_eom_kuccsd.py::KnownValues::test_n3_diffuse_frozen FAILED pyscf/pbc/cc/test/test_eom_kuccsd_diag.py::KnownValues::test_he_112_ea_diag FAILED pyscf/pbc/cc/test/test_eom_kuccsd_diag.py::KnownValues::test_he_112_ea_diag_shift FAILED pyscf/pbc/cc/test/test_eom_kuccsd_diag.py::KnownValues::test_he_112_ip_diag FAILED pyscf/pbc/cc/test/test_eom_kuccsd_diag.py::KnownValues::test_he_112_ip_diag_shift FAILED pyscf/pbc/cc/test/test_eom_kuccsd_diag.py::KnownValues::test_he_131_ea_diag FAILED pyscf/pbc/cc/test/test_eom_kuccsd_diag.py::KnownValues::test_he_131_ip_diag FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_111_n0 - ValueErro... FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_111_n1 - ValueErro... FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_111_n3 - ValueErro... FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_211_n3 - ValueErro... FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_h4_fcc_k2 - ValueE... FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_h4_fcc_k2_frozen FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_rand_ccsd - ValueE... FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_rand_ccsd_frozen0 FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_rand_ccsd_frozen1 FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_rand_ccsd_frozen2 FAILED pyscf/pbc/cc/test/test_kgccsd.py::KnownValues::test_rand_ccsd_frozen3 FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_ccsd_t_non_hf_frozen FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_frozen_n3 - ValueE... FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_h4_fcc_k2 - ValueE... FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_h4_fcc_k2_frozen FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_rand_ccsd - ValueE... FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_rand_ccsd_frozen0 FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_rand_ccsd_frozen1 FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_rand_ccsd_frozen2 FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_rand_ccsd_frozen3 FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_rccsd_t_hf_against_so FAILED pyscf/pbc/cc/test/test_krccsd.py::KnownValues::test_single_kpt - Value... FAILED pyscf/pbc/cc/test/test_krccsd_gamma.py::KnownValues::test_111_n0 - Val... FAILED pyscf/pbc/cc/test/test_krccsd_gamma.py::KnownValues::test_111_n1 - Val... FAILED pyscf/pbc/cc/test/test_krccsd_gamma.py::KnownValues::test_111_n3 - Val... FAILED pyscf/pbc/cc/test/test_krccsd_gamma.py::KnownValues::test_311_n1 - Val... FAILED pyscf/pbc/cc/test/test_kuccsd.py::KnownValues::test_kuccsd_rdm_slow - ... FAILED pyscf/pbc/cc/test/test_kuccsd.py::KnownValues::test_update_amps - Valu... FAILED pyscf/pbc/cc/test/test_kuccsd_openshell.py::test_kuccsd_openshell - Va... FAILED pyscf/pbc/cc/test/test_rccsd_t_shift.py::KnownValues::test_water - Val... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_convert_from FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_get_bands - Va... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_gga_df - Value... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_gga_df_newton FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_krks_gamma_center FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_krks_monkhorst FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_krks_multigrid_newton FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_krks_symorb - ... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_kuks_gamma_center FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_kuks_monkhorst FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_kuks_multigrid_newton FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_lda_df - Value... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_multigrid - Va... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_multigrid_kuks FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_rsh - ValueErr... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_rsh_df - Value... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_to_rhf - Value... FAILED pyscf/pbc/dft/test/test_krks_ksym.py::KnownValues::test_to_uhf - Value... FAILED pyscf/pbc/dft/test/test_krkspu.py::KnownValues::test_KRKSpU_ksymm - Va... FAILED pyscf/pbc/dft/test/test_kuks.py::KnownValues::test_kuks_as_kuhf - Valu... FAILED pyscf/pbc/dft/test/test_kukspu.py::KnownValues::test_KUKSpU_ksymm - Va... FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_eval_rhoG_nonorth_gga FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_eval_rhoG_orth_gga FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_eval_rhoG_orth_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_gen_rhf_response FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_gen_uhf_response FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_multigrid_krks FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_multigrid_kroks FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_multigrid_kuks FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_multigrid_rks FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_multigrid_roks FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_multigrid_uks FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nonorth_get_j FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nonorth_get_j_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nonorth_get_pp FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nr_rks_fxc - V... FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nr_rks_fxc_hermi0 FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nr_rks_fxc_st FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_nr_uks_fxc - V... FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_get_j_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_get_nuc_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_get_pp - ... FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_rks_gga_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_rks_lda_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_uks_fxc_hermi0 FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_orth_uks_gga_kpts FAILED pyscf/pbc/dft/test/test_multigrid.py::KnownValues::test_rcut_vs_ke_cut FAILED pyscf/pbc/gw/test/test_krgw.py::KnownValues::test_gw - ValueError: not... FAILED pyscf/pbc/gw/test/test_kugw.py::KnownValues::test_gwac_pade - ValueErr... FAILED pyscf/pbc/mp/test/test_scs.py::KnownValues::test_ksymm - ValueError: n... FAILED pyscf/pbc/scf/test/test_addons.py::KnownValues::test_krhf_smearing - T... FAILED pyscf/pbc/scf/test/test_addons.py::KnownValues::test_kuhf_smearing - T... FAILED pyscf/pbc/scf/test/test_addons.py::KnownValues::test_rhf_smearing - Ty... FAILED pyscf/pbc/scf/test/test_addons.py::KnownValues::test_uhf_smearing - Ty... FAILED pyscf/pbc/scf/test/test_khf.py::KnownValues::test_analyze - ValueError... FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_noshift::test_kghf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_noshift::test_krhf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_noshift::test_krohf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_noshift::test_kuhf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_shift::test_kghf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_shift::test_krhf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_shift::test_krohf FAILED pyscf/pbc/scf/test/test_mulliken_meta.py::KPTvsSUPCELL_shift::test_kuhf FAILED pyscf/pbc/scf/test/test_rohf.py::KnownValues::test_analyze - ValueErro... FAILED pyscf/pbc/scf/test/test_rohf.py::KnownValues::test_krohf_kernel - Valu... FAILED pyscf/pbc/scf/test/test_rsjk.py::KnownValues::test_2d - ValueError: no... FAILED pyscf/pbc/scf/test/test_rsjk.py::KnownValues::test_get_jk - ValueError... FAILED pyscf/pbc/scf/test/test_rsjk.py::KnownValues::test_get_jk_fft_dd_block FAILED pyscf/pbc/scf/test/test_rsjk.py::KnownValues::test_get_jk_sr_without_dddd FAILED pyscf/pbc/scf/test/test_uhf.py::KnownValues::test_kuhf_kernel - ValueE... FAILED pyscf/pbc/tdscf/test/test_krhf.py::Diamond::test_tda_singlet - ValueEr... FAILED pyscf/pbc/tdscf/test/test_krhf.py::Diamond::test_tda_singlet_eomccs - ... FAILED pyscf/pbc/tdscf/test/test_krhf.py::Diamond::test_tda_triplet - ValueEr... FAILED pyscf/pbc/tdscf/test/test_krhf.py::Diamond::test_tdhf_singlet - ValueE... FAILED pyscf/pbc/tdscf/test/test_krhf.py::Diamond::test_tdhf_triplet - ValueE... FAILED pyscf/pbc/tdscf/test/test_krhf.py::WaterBigBox::test_tda_singlet - Val... FAILED pyscf/pbc/tdscf/test/test_krhf.py::WaterBigBox::test_tda_triplet - Val... FAILED pyscf/pbc/tdscf/test/test_krhf.py::WaterBigBox::test_tdhf_singlet - Va... FAILED pyscf/pbc/tdscf/test/test_krhf.py::WaterBigBox::test_tdhf_triplet - Va... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE::test_tda_singlet - Valu... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE::test_tda_triplet - Valu... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE::test_tdhf_singlet - Val... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE::test_tdhf_triplet - Val... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE0::test_tda_singlet - Val... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE0::test_tda_triplet - Val... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE0::test_tdhf_singlet - Va... FAILED pyscf/pbc/tdscf/test/test_krks.py::DiamondPBE0::test_tdhf_triplet - Va... FAILED pyscf/pbc/tdscf/test/test_kuhf.py::WaterBigBox::test_tda - ValueError:... FAILED pyscf/pbc/tdscf/test/test_kuhf.py::WaterBigBox::test_tdhf - ValueError... FAILED pyscf/pbc/tdscf/test/test_kuks.py::DiamondPBE::test_tda - ValueError: ... FAILED pyscf/pbc/tdscf/test/test_kuks.py::DiamondPBE::test_tdhf - ValueError:... FAILED pyscf/pbc/tdscf/test/test_kuks.py::DiamondPBE0::test_tda - ValueError:... FAILED pyscf/pbc/tdscf/test/test_kuks.py::DiamondPBE0::test_tdhf - ValueError... FAILED pyscf/pbc/tdscf/test/test_rhf.py::Diamond::test_tda_singlet - ValueErr... FAILED pyscf/pbc/tdscf/test/test_rhf.py::Diamond::test_tda_triplet - ValueErr... FAILED pyscf/pbc/tdscf/test/test_rhf.py::Diamond::test_tdhf_singlet - ValueEr... FAILED pyscf/pbc/tdscf/test/test_rhf.py::Diamond::test_tdhf_triplet - ValueEr... FAILED pyscf/pbc/tdscf/test/test_rhf.py::DiamondShifted::test_tda_singlet - V... FAILED pyscf/pbc/tdscf/test/test_rhf.py::DiamondShifted::test_tda_triplet - V... FAILED pyscf/pbc/tdscf/test/test_rhf.py::DiamondShifted::test_tdhf_singlet - ... FAILED pyscf/pbc/tdscf/test/test_rhf.py::DiamondShifted::test_tdhf_triplet - ... FAILED pyscf/pbc/tdscf/test/test_rhf.py::WaterBigBox::test_tda_singlet - Valu... FAILED pyscf/pbc/tdscf/test/test_rhf.py::WaterBigBox::test_tda_triplet - Valu... FAILED pyscf/pbc/tdscf/test/test_rhf.py::WaterBigBox::test_tdhf_singlet - Val... FAILED pyscf/pbc/tdscf/test/test_rhf.py::WaterBigBox::test_tdhf_triplet - Val... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_camb3lyp_tda - ValueEr... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_hse06_tda - ValueError... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_tda_singlet - ValueErr... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_tda_triplet - ValueErr... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_tddft_singlet - ValueE... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_tddft_triplet - ValueE... FAILED pyscf/pbc/tdscf/test/test_rks.py::Diamond::test_wb97_tda - ValueError:... FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBEShifted::test_tda_singlet FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBEShifted::test_tda_triplet FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBEShifted::test_tddft_singlet FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBEShifted::test_tddft_triplet FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE::test_tda_singlet - V... FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE::test_tda_triplet - V... FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE::test_tddft_singlet FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE::test_tddft_triplet FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBE0::test_tda_singlet - Valu... FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBE0::test_tda_triplet - Valu... FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBE0::test_tddft_singlet - Va... FAILED pyscf/pbc/tdscf/test/test_rks.py::DiamondPBE0::test_tddft_triplet - Va... FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE0::test_tda_singlet - ... FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE0::test_tda_triplet - ... FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE0::test_tddft_singlet FAILED pyscf/pbc/tdscf/test/test_rks.py::WaterBigBoxPBE0::test_tddft_triplet FAILED pyscf/pbc/tdscf/test/test_uhf.py::Diamond::test_tda - ValueError: not ... FAILED pyscf/pbc/tdscf/test/test_uhf.py::Diamond::test_tdhf - ValueError: not... FAILED pyscf/pbc/tdscf/test/test_uhf.py::WaterBigBox::test_tda - ValueError: ... FAILED pyscf/pbc/tdscf/test/test_uhf.py::WaterBigBox::test_tdhf - ValueError:... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondM06::test_camb3lyp_tda - Valu... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondM06::test_hse03_tda - ValueEr... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondM06::test_tda - ValueError: n... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondM06::test_tdhf - ValueError: ... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondM06::test_wb97_tda - ValueErr... FAILED pyscf/pbc/tdscf/test/test_uks.py::WaterBigBoxPBE::test_tda - ValueErro... FAILED pyscf/pbc/tdscf/test/test_uks.py::WaterBigBoxPBE::test_tdhf - ValueErr... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondPBE0::test_tda - ValueError: ... FAILED pyscf/pbc/tdscf/test/test_uks.py::DiamondPBE0::test_tdhf - ValueError:... FAILED pyscf/pbc/tdscf/test/test_uks.py::WaterBigBoxPBE0::test_tda - ValueErr... FAILED pyscf/pbc/tdscf/test/test_uks.py::WaterBigBoxPBE0::test_tdhf - ValueEr... FAILED pyscf/pbc/tools/test/test_k2gamma.py::KnownValues::test_k2gamma - Valu... FAILED pyscf/pbc/tools/test/test_k2gamma.py::KnownValues::test_k2gamma_ksymm FAILED pyscf/qmmm/pbc/test/test_qmmm.py::KnownValues::test_rks_pbe0 - ValueEr... FAILED pyscf/qmmm/test/test_itrf.py::KnowValues::test_ccsd - ValueError: not ... FAILED pyscf/scf/test/test_addons.py::KnownValues::test_project_dm_nr2nr - Va... FAILED pyscf/scf/test/test_addons.py::KnownValues::test_project_dm_nr2r - Val... FAILED pyscf/scf/test/test_addons.py::KnownValues::test_project_dm_r2r - Valu... FAILED pyscf/scf/test/test_addons.py::KnownValues::test_rhf_smearing_nelec - ... FAILED pyscf/scf/test/test_rhf.py::KnownValues::test_mute_chkfile - ValueErro... FAILED pyscf/solvent/test/test_ddcosmo.py::SolventWithDefaultGrids::test_rhf_tda FAILED pyscf/solvent/test/test_ddcosmo_grad.py::KnownValues::test_B1 - ValueE... FAILED pyscf/solvent/test/test_ddcosmo_grad.py::KnownValues::test_casci_grad FAILED pyscf/solvent/test/test_ddcosmo_grad.py::KnownValues::test_casscf_grad FAILED pyscf/solvent/test/test_ddcosmo_grad.py::KnownValues::test_ccsd_grad FAILED pyscf/solvent/test/test_ddcosmo_grad.py::KnownValues::test_solvent_nuc FAILED pyscf/solvent/test/test_ddcosmo_grad.py::KnownValues::test_tda_grad - ... FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_b3lyp_tda FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_lda_tda FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_rhf_tda FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_rhf_tda_triplet FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_rhf_tdhf FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_scanner FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_ub3lyp_tda FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_uhf_tda FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_uhf_tdhf FAILED pyscf/solvent/test/test_ddcosmo_tdscf_grad.py::KnownValues::test_ulda_tda FAILED pyscf/solvent/test/test_pcm.py::KnownValues::test_ccsd - ValueError: n... FAILED pyscf/solvent/test/test_pcm.py::KnownValues::test_tdhf - ValueError: n... FAILED pyscf/solvent/test/test_pcm_grad.py::KnownValues::test_casci_grad - Va... FAILED pyscf/solvent/test/test_pcm_grad.py::KnownValues::test_casscf_grad - V... FAILED pyscf/solvent/test/test_pcm_grad.py::KnownValues::test_ccsd_grad - Val... FAILED pyscf/solvent/test/test_pcm_hessian.py::KnownValues::test_hess_cpcm - ... FAILED pyscf/solvent/test/test_pcm_hessian.py::KnownValues::test_hess_iefpcm FAILED pyscf/solvent/test/test_pcm_hessian.py::KnownValues::test_uhf_hess_iefpcm FAILED pyscf/solvent/test/test_pcm_tdscf.py::KnownValues::test_b3lyp_CPCM - V... FAILED pyscf/solvent/test/test_pcm_tdscf.py::KnownValues::test_b3lyp_IEFPCM FAILED pyscf/solvent/test/test_pcm_tdscf.py::KnownValues::test_hf_CPCM - Valu... FAILED pyscf/solvent/test/test_pcm_tdscf.py::KnownValues::test_unrestricted_b3lyp_CPCM FAILED pyscf/solvent/test/test_pcm_tdscf.py::KnownValues::test_unrestricted_hf_CPCM FAILED pyscf/tdscf/test/test_tddks.py::KnownValues::test_ab_hf - ValueError: ... FAILED pyscf/tdscf/test/test_tddks.py::KnownValues::test_col_gga_ab_ks - Valu... FAILED pyscf/tdscf/test/test_tddks.py::KnownValues::test_col_lda_ab_ks - Valu... FAILED pyscf/tdscf/test/test_tddks.py::KnownValues::test_col_mgga_ab_ks - Val... FAILED pyscf/tdscf/test/test_tddks.py::KnownValues::test_tda_lda - ValueError... FAILED pyscf/tdscf/test/test_tddks.py::KnownValues::test_tddft_lda - ValueErr... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_ab_hf - ValueError: ... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_col_gga_ab_ks - Valu... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_col_lda_ab_ks - Valu... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_col_mgga_ab_ks - Val... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_tda_lda - ValueError... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_tda_with_wfnsym - Va... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_tddft_lda - ValueErr... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_tddft_with_wfnsym - ... FAILED pyscf/tdscf/test/test_tdgks.py::KnownValues::test_tdhf_with_wfnsym - V... FAILED pyscf/tdscf/test/test_tdrhf.py::KnownValues::test_symmetry_init_guess FAILED pyscf/tdscf/test/test_tdrhf.py::KnownValues::test_tda_singlet - ValueE... FAILED pyscf/tdscf/test/test_tdrhf.py::KnownValues::test_tda_triplet - ValueE... FAILED pyscf/tdscf/test/test_tdrhf.py::KnownValues::test_tdhf_singlet - Value... FAILED pyscf/tdscf/test/test_tdrhf.py::KnownValues::test_tdhf_triplet - Value... FAILED pyscf/tdscf/test/test_tdrks_vv10.py::KnownValues::test_wb97xv_tda - Va... FAILED pyscf/tdscf/test/test_tdrks_vv10.py::KnownValues::test_wb97xv_tda_triplet FAILED pyscf/tdscf/test/test_tdrks_vv10.py::KnownValues::test_wb97xv_unrestricted_tda FAILED pyscf/tdscf/test/test_tduhf.py::KnownValues::test_symmetry_init_guess FAILED pyscf/tdscf/test/test_tduhf.py::KnownValues::test_tda - ValueError: no... FAILED pyscf/tdscf/test/test_tduhf.py::KnownValues::test_tda1 - ValueError: n... FAILED pyscf/tdscf/test/test_tduhf.py::KnownValues::test_tdhf - ValueError: n... FAILED pyscf/tdscf/test/test_tduhf.py::KnownValues::test_tdhf1 - ValueError: ... FAILED pyscf/x2c/test/test_tdscf.py::KnownValues::test_ab_hf - ValueError: no... FAILED pyscf/x2c/test/test_tdscf.py::KnownValues::test_col_gga_ab_ks - ValueE... FAILED pyscf/x2c/test/test_tdscf.py::KnownValues::test_col_lda_ab_ks - ValueE... FAILED pyscf/x2c/test/test_tdscf.py::KnownValues::test_col_mgga_ab_ks - Value... FAILED pyscf/x2c/test/test_tdscf.py::KnownValues::test_tda_lda - ValueError: ... FAILED pyscf/x2c/test/test_tdscf.py::KnownValues::test_tddft_lda - ValueError... FAILED pyscf/x2c/test/test_x2c.py::KnownValues::test_ghf - ValueError: not en... FAILED pyscf/x2c/test/test_x2c.py::KnownValues::test_gks - ValueError: not en... FAILED pyscf/x2c/test/test_x2c.py::KnownValues::test_picture_change - ValueEr... FAILED pyscf/x2c/test/test_x2c.py::KnownValues::test_sfx2c1e_picture_change FAILED pyscf/x2c/test/test_x2c_grad.py::KnownValues::test_R1 - ValueError: no... FAILED pyscf/x2c/test/test_x2c_grad.py::KnownValues::test_hfw - ValueError: n... FAILED pyscf/x2c/test/test_x2c_grad.py::KnownValues::test_x1 - ValueError: no... FAILED pyscf/x2c/test/test_x2c_hess.py::KnownValues::test_hfw2 - ValueError: ... ERROR pyscf/agf2/test/test_dfragf2_h2o.py::KnownValues::test_dfragf2_h2o_ea ERROR pyscf/agf2/test/test_dfragf2_h2o.py::KnownValues::test_dfragf2_h2o_ground_state ERROR pyscf/agf2/test/test_dfragf2_h2o.py::KnownValues::test_dfragf2_h2o_ip ERROR pyscf/agf2/test/test_dfuagf2_beh.py::KnownValues::test_dfuagf2_beh_ea ERROR pyscf/agf2/test/test_dfuagf2_beh.py::KnownValues::test_dfuagf2_beh_ground_state ERROR pyscf/agf2/test/test_dfuagf2_beh.py::KnownValues::test_dfuagf2_beh_ip ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_frozen - Val... ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_frozen_fully_outcore ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_frozen_outcore ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_h2o_ea - Val... ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_h2o_ground_state ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_h2o_ip - Val... ERROR pyscf/agf2/test/test_ragf2_h2o.py::KnownValues::test_ragf2_outcore - Va... ERROR pyscf/agf2/test/test_uagf2_beh.py::KnownValues::test_uagf2_beh_ea - Val... ERROR pyscf/agf2/test/test_uagf2_beh.py::KnownValues::test_uagf2_beh_ground_state ERROR pyscf/agf2/test/test_uagf2_beh.py::KnownValues::test_uagf2_beh_ip - Val... ERROR pyscf/agf2/test/test_uagf2_beh.py::KnownValues::test_uagf2_frozen_fully_outcore ERROR pyscf/agf2/test/test_uagf2_beh.py::KnownValues::test_uagf2_frozen_outcore ERROR pyscf/agf2/test/test_uagf2_beh.py::KnownValues::test_uagf2_outcore - Va... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_ao2mo - ValueError: no... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_eaccsd - ValueError... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_eaccsd_koopmans - V... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_eomee_ccsd_diag - V... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_eomee_ccsd_matvec ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_eomee_init_guess - ... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_eomsf_ccsd_matvec ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_ipccsd - ValueError... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_df_ipccsd_koopmans - V... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_eomee - ValueError: no... ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_eomee_ccsd_spin_keep ERROR pyscf/cc/test/test_dfuccsd.py::KnownValues::test_with_df - ValueError: ... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_ea_matvec - ValueErr... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_eaccsd - ValueError:... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_eaccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_eomee_diag - ValueEr... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_eomee_matvec - Value... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_h2o_star - ValueErro... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_ip_matvec - ValueErr... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_ipccsd - ValueError:... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_ipccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_t3p2_intermediates_complex ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_t3p2_intermediates_real ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_vector_to_amplitudes ERROR pyscf/cc/test/test_eom_gccsd.py::KnownValues::test_vector_to_amplitudes_overwritten ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ea_matvec - ValueErr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ea_matvec1 - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ea_matvec2 - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eaccsd - ValueError:... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eaccsd2 - ValueError... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eaccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eaccsd_koopmans2 - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eaccsd_partition - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eaccsd_partition2 - ... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eeccsd - ValueError:... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eeccsd2 - ValueError... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eeccsd3 - ValueError... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eeccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eeccsd_koopmans2 - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eeccsd_koopmans3 - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_matvec_singlet ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_matvec_singlet2 ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_matvec_singlet3 ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_matvec_triplet ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_matvec_triplet2 ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_matvec_triplet3 ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_singlet ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_ccsd_triplet ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_diag - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_diag2 - ValueE... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomee_diag3 - ValueE... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomsf_ccsd - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomsf_ccsd_matvec - ... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomsf_ccsd_matvec2 ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_eomsf_ccsd_matvec3 ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_h2o_star - ValueErro... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ip_matvec - ValueErr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ip_matvec1 - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ip_matvec2 - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ip_matvec3 - ValueEr... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd - ValueError:... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd2 - ValueError... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd3 - ValueError... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd_koopmans2 - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd_koopmans3 - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd_partition - V... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd_partition2 - ... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_ipccsd_partition3 - ... ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_sort_left_right_eigensystem ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_t3p2_intermediates_against_so ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_t3p2_intermediates_complex ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_t3p2_intermediates_real ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_vector_to_amplitudes ERROR pyscf/cc/test/test_eom_rccsd.py::KnownValues::test_vector_to_amplitudes_overwritten ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_eaccsd - ValueError:... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_eaccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_eomee - ValueError: ... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_eomee1 - ValueError:... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_eomee_ccsd_spin_keep ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_eomsf_ccsd - ValueEr... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ipccsd - ValueError:... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ipccsd_koopmans - Va... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_spatial2spin_eomsf ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_eomea_matvec - V... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_eomee_ccsd_diag ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_eomee_ccsd_matvec ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_eomee_init_guess ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_eomip_matvec - V... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_eomsf_ccsd_matvec ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_ucc_update_amps - Va... ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_vector_to_amplitudes_eom_spin_keep ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_vector_to_amplitudes_eomsf ERROR pyscf/cc/test/test_eom_uccsd.py::KnownValues::test_vector_to_amplitudes_overwritten ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_ERIS - ValueError: not e... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_amplitudes_from_rccsd_or_uccsd ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_frozen - ValueError: not... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_gccsd - ValueError: not ... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_mbpt2 - ValueError: not ... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_rdm_complex - ValueError... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_rdm_real - ValueError: n... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_rdm_real1 - ValueError: ... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_rdm_vs_rccsd - ValueErro... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_rdm_vs_uccsd - ValueErro... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_spin2spatial - ValueErro... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_update_amps - ValueError... ERROR pyscf/cc/test/test_gccsd.py::KnownValues::test_vector_size - ValueError... ERROR pyscf/cc/test/test_gccsd_t.py::KnownValues::test_gccsd_t - ValueError: ... ERROR pyscf/cc/test/test_gccsd_t.py::KnownValues::test_gccsd_t_compare_uccsd_t ERROR pyscf/cc/test/test_gccsd_t.py::KnownValues::test_gccsd_t_complex - Valu... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_0 - ValueError: not ... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_1 - ValueError: not ... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_2 - ValueError: not ... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_3 - ValueError: not ... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_4 - ValueError: not ... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_5 - ValueError: not ... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_amp_input - ValueErr... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_chkfile - ValueError... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_density_fitting - Va... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_hermi_moments - Valu... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_lambda_assertion - V... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_misc - ValueError: n... ERROR pyscf/cc/test/test_momgfccsd.py::KnownValues::test_mom_input - ValueErr... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_ERIS - ValueError: not e... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_add_vvvv - ValueError: n... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_amplitudes_to_vector - V... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_ao2mo - ValueError: not ... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_ao_direct - ValueError: ... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_ccsd_t - ValueError: not... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_density_fit_interface - ... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_diagnostic - ValueError:... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_dump_chk - ValueError: n... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_eris_contract_vvvv_t2 - ... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_incore_complete - ValueE... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_iterative_dampling - Val... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_mbpt2 - ValueError: not ... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_no_diis - ValueError: no... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_rccsd_frozen - ValueErro... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_restart - ValueError: no... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_roccsd - ValueError: not... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_update_amps - ValueError... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_vector_size - ValueError... ERROR pyscf/cc/test/test_rccsd.py::KnownValues::test_vector_to_amplitudes_overwritten ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_ERIS - ValueError: not e... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_add_vvVV - ValueError: n... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_add_vvvv - ValueError: n... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_amplitudes_from_rccsd - ... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_ao2mo - ValueError: not ... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_damping - ValueError: no... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_eris_contract_vvvv_t2 - ... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_h2o_rdm - ValueError: no... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_h4_rdm - ValueError: not... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_mbpt2 - ValueError: not ... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_rdm - ValueError: not en... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_reset - ValueError: not ... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_uccsd_frozen - ValueErro... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_uintermediats - ValueErr... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_update_amps1 - ValueErro... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_update_amps2 - ValueErro... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_vector_size - ValueError... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_vector_to_amplitudes - V... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_vector_to_amplitudes_overwritten ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_with_df_s0 - ValueError:... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_with_df_s2 - ValueError:... ERROR pyscf/cc/test/test_uccsd.py::KnownValues::test_zero_beta_electrons - Va... ERROR pyscf/cc/test/test_uccsd_t.py::KnownValues::test_uccsd_t - ValueError: ... ERROR pyscf/cc/test/test_uccsd_t.py::KnownValues::test_uccsd_t_complex - Valu... ERROR pyscf/cc/test/test_uccsd_t.py::KnownValues::test_uccsd_t_rdm - ValueErr... ERROR pyscf/mcpdft/test/test_mspdft.py::KnownValues::test_diabatize - ValueEr... ERROR pyscf/mcpdft/test/test_mspdft.py::KnownValues::test_final_adiabats - Va... ERROR pyscf/mcpdft/test/test_mspdft.py::KnownValues::test_intermediate_diabats ERROR pyscf/mcpdft/test/test_mspdft.py::KnownValues::test_reference_adiabats ERROR pyscf/pbc/cc/test/test_eom_kgccsd.py::KnownValues::test_n3_diffuse - Va... ERROR pyscf/pbc/cc/test/test_eom_kgccsd.py::KnownValues::test_n3_diffuse_Ta ERROR pyscf/pbc/cc/test/test_eom_kgccsd.py::KnownValues::test_n3_diffuse_frozen ERROR pyscf/pbc/cc/test/test_eom_kgccsd.py::KnownValues::test_n3_diffuse_star ERROR pyscf/pbc/cc/test/test_kccsd_ksymm.py::KnownValues::test_krccsd_ksym - ... ERROR pyscf/pbc/cc/test/test_kccsd_ksymm.py::KnownValues::test_vs_krccsd - Va... ERROR pyscf/pbc/mp/test/test_ksym.py::KnownValues::test_kmp2 - ValueError: no... ERROR pyscf/pbc/mp/test/test_ksym.py::KnownValues::test_rdm1 - ValueError: no... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_convert_from - V... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_get_rho - ValueE... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_init_guess_from_chkfile ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_kghf - ValueErro... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_khf_newton - Val... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_krhf_df - ValueE... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_krhf_gamma_center ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_krhf_monkhorst ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_krhf_symorb - Va... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_kuhf_df - ValueE... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_kuhf_gamma_center ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_kuhf_monkhorst ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_kuhf_newton - Va... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_kuhf_smearing - ... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_to_khf - ValueEr... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_to_khf_with_chkfile ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_to_rhf - ValueEr... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_to_uhf - ValueEr... ERROR pyscf/pbc/scf/test/test_khf_ksym.py::KnownValues::test_transform_fock ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_ab_b3lyp - ValueError... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_ab_hf - ValueError: n... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_ab_lda - ValueError: ... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_ab_mgga - ValueError:... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_analyze - ValueError:... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_dRPA - ValueError: no... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_dTDA - ValueError: no... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_init - ValueError: no... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_nohbrid_b88p86 - Valu... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_nohbrid_lda - ValueEr... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_nto - ValueError: not... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_reset - ValueError: n... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_scanner - ValueError:... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_b3lyp_triplet - V... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_b3lypg - ValueErr... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_lda - ValueError:... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_lda_triplet - Val... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_m06l_singlet - Va... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_rsh - ValueError:... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tda_with_wfnsym - Val... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_b3lyp - ValueEr... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_b88p86 - ValueE... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_b88p86_triplet ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_camb3lyp - Valu... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_hse06 - ValueEr... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_lda - ValueErro... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tddft_with_wfnsym - V... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_tdhf_with_wfnsym - Va... ERROR pyscf/tdscf/test/test_tdrks.py::KnownValues::test_transition_multipoles ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_ab_b3lyp - ValueError... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_ab_hf - ValueError: n... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_ab_lda - ValueError: ... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_ab_mgga - ValueError:... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_analyze - ValueError:... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_init - ValueError: no... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_nohybrid_b88p86 - Val... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_nohybrid_lda - ValueE... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_nto - ValueError: not... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tda_b3lyp - ValueErro... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tda_lda - ValueError:... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tda_m06l - ValueError... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tda_rsh - ValueError:... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tda_with_wfnsym - Val... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tddft_b3lyp - ValueEr... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tddft_b88p86 - ValueE... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tddft_camb3lyp - Valu... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tddft_lda - ValueErro... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tddft_with_wfnsym - V... ERROR pyscf/tdscf/test/test_tduks.py::KnownValues::test_tdhf_with_wfnsym - Va... = 589 failed, 2071 passed, 58 skipped, 251 deselected, 133163 warnings, 267 errors in 1172.43s (0:19:32) = There are 0 leftover temporary files error: Bad exit status from /var/tmp/rpm-tmp.dgM6Qn (%check) Bad exit status from /var/tmp/rpm-tmp.dgM6Qn (%check) RPM build errors: Finish: rpmbuild python-pyscf-2.11.0-2.fc44.src.rpm Finish: build phase for python-pyscf-2.11.0-2.fc44.src.rpm INFO: chroot_scan: 1 files copied to /var/lib/copr-rpmbuild/results/chroot_scan INFO: /var/lib/mock/fedora-43-aarch64-1768641411.012166/root/var/log/dnf5.log INFO: chroot_scan: creating tarball /var/lib/copr-rpmbuild/results/chroot_scan.tar.gz /bin/tar: Removing leading `/' from member names ERROR: Exception(/var/lib/copr-rpmbuild/results/python-pyscf-2.11.0-2.fc44.src.rpm) Config(fedora-43-aarch64) 20 minutes 41 seconds INFO: Results and/or logs in: /var/lib/copr-rpmbuild/results INFO: Cleaning up build root ('cleanup_on_failure=True') Start: clean chroot INFO: unmounting tmpfs. Finish: clean chroot ERROR: Command failed: # /usr/bin/systemd-nspawn -q -M 2e6d45c7d0094a44af6076e4b8511ec4 -D /var/lib/mock/fedora-43-aarch64-1768641411.012166/root -a -u mockbuild --capability=cap_ipc_lock --capability=cap_ipc_lock --bind=/tmp/mock-resolv.ge4rfket:/etc/resolv.conf --bind=/dev/btrfs-control --bind=/dev/mapper/control --bind=/dev/fuse --bind=/dev/loop-control --bind=/dev/loop0 --bind=/dev/loop1 --bind=/dev/loop2 --bind=/dev/loop3 --bind=/dev/loop4 --bind=/dev/loop5 --bind=/dev/loop6 --bind=/dev/loop7 --bind=/dev/loop8 --bind=/dev/loop9 --bind=/dev/loop10 --bind=/dev/loop11 --console=pipe --setenv=TERM=vt100 --setenv=SHELL=/bin/bash --setenv=HOME=/builddir --setenv=HOSTNAME=mock --setenv=PATH=/usr/bin:/bin:/usr/sbin:/sbin '--setenv=PROMPT_COMMAND=printf "\033]0;\007"' '--setenv=PS1= \s-\v\$ ' --setenv=LANG=C.UTF-8 --resolv-conf=off bash --login -c '/usr/bin/rpmbuild -bb --target aarch64 --nodeps /builddir/build/originals/python-pyscf.spec' Copr build error: Build failed