# SigPy -- signal processing and iterative reconstruction in Python (Lustig lab,
# UC Berkeley): linear operators, proximal operators and solvers on NumPy (and
# optionally CuPy), with an MRI package covering SENSE/L1-wavelet/TV recon,
# ESPIRiT coil sensitivity calibration, NUFFT, density compensation, sampling
# patterns and RF pulse design.
#
# WHY IT IS HERE: DeepInverse's multi-coil MRI operator uses it for coil maps.
# deepinv.physics.MultiCoilMRI's ESPIRiT estimation calls sigpy.mri.app.EspiritCalib,
# and its simulated birdcage coils call sigpy.mri.birdcage_maps. SigPy is also the
# standard Python comparison point for BART (tests/deepinv-bart-mri.bats).
#
# Class 1 under docs/PACKAGING-POLICY.md: Fedora ships no package by this source
# name and nothing provides python3dist(sigpy). Verified 2026-10-12:
#   dnf repoquery --whatprovides 'python3dist(sigpy)'  -> empty
#
# Chroots: numba is a hard runtime dependency. Fedora 44+ gets it from this
# Copr (python-numba); Fedora 43 has neither a Fedora nor a Copr numba
# (python-llvmlite 0.50 fails there). So this package is not built for f43.

%global pypi_name       sigpy

Name:           python-%{pypi_name}
Version:        0.1.27
Release:        1%{?dist}
Summary:        Signal processing and iterative reconstruction, with MRI tools

License:        BSD-3-Clause
URL:            https://github.com/mikgroup/sigpy
# The GitHub tag. The PyPI sdist for 0.1.27 contains only metadata (11 files,
# no sigpy/ package and no tests/), so it cannot be built from.
Source0:        %{url}/archive/v%{version}/%{pypi_name}-%{version}.tar.gz

BuildArch:      noarch

BuildRequires:  python3-devel
BuildRequires:  python3dist(pytest)
BuildRequires:  python3dist(pytest-xdist)
# tests/test_pytorch.py checks the to_pytorch/from_pytorch bridges.
BuildRequires:  python3dist(torch)

%global _description %{expand:
SigPy is a package for signal processing, with an emphasis on iterative
reconstruction. It provides linear operators, proximal operators and
first-order solvers (conjugate gradient, gradient methods, primal-dual) that
run on NumPy arrays, or on CuPy arrays when CuPy is installed. Its MRI module
covers parallel imaging (SENSE, L1-wavelet and total-variation regularised
reconstruction), ESPIRiT coil sensitivity calibration, the non-uniform FFT,
density compensation, Poisson-disc and radial sampling, and RF pulse design.}

%description %_description

%package -n     python3-%{pypi_name}
Summary:        %{summary}
# sigpy.to_pytorch_function and the torch bridge in sigpy.pytorch import torch on
# use, not at module scope. Not a hard dependency: SigPy's core is NumPy.
Suggests:       python3-torch

%description -n python3-%{pypi_name} %_description

%prep
%autosetup -p1 -n %{pypi_name}-%{version}

%generate_buildrequires
%pyproject_buildrequires

%build
%pyproject_wheel

%install
%pyproject_install
%pyproject_save_files -l %{pypi_name}

%check
export NUMBA_CACHE_DIR=$(mktemp -d)
%pyproject_check_import
# Upstream runs `python -m unittest`; pytest collects the same unittest cases.
# Run from a copy of tests/ so the source tree's sigpy/ cannot shadow the
# installed package.
#  - tests/learn: tests for sigpy.learn, a subpackage upstream removed; 0.1.27
#    ships no sigpy/learn/, so both modules fail to import (stale upstream tests).
#  - NUMBA_CACHE_DIR: SigPy's kernels are @numba.jit(cache=True), and numba
#    writes its cache next to the module when that is writable, which in %%check
#    is the buildroot. Pointed at a scratch directory above, before the import
#    check, which compiles nothing but would create the directory.
cp -a tests %{_builddir}/sigpy-tests
cd %{_builddir}/sigpy-tests
test ! -e %{buildroot}%{python3_sitelib}/sigpy/learn
%pytest -c /dev/null --rootdir=. . -p no:cacheprovider -n %{_smp_build_ncpus} -q -rs \
    --ignore=learn

%files -n python3-%{pypi_name} -f %{pyproject_files}
%doc README.rst

%changelog
* Mon Oct 12 2026 Morgan Hough <morgan.hough@gmail.com> - 0.1.27-1
- Initial package: ESPIRiT and birdcage coil maps for DeepInverse's MRI operator.