%global pypi_name ipax

Name:           python-%{pypi_name}
Version:        0.13.0
Release:        1%{?dist}
Summary:        Array-API primal-dual interior-point solver for nonlinear optimisation

License:        Apache-2.0
URL:            https://github.com/wahln/ipax
Source0:        %{pypi_source %{pypi_name}}

BuildArch:      noarch
BuildRequires:  python3-devel
BuildRequires:  pyproject-rpm-macros
BuildRequires:  python3-pytest
BuildRequires:  python3-hypothesis
BuildRequires:  python3-numpy
BuildRequires:  python3-scipy
BuildRequires:  python3-sympy
BuildRequires:  python3-array-api-strict

%global _description %{expand:
ipax is a primal-dual interior-point solver for large-scale nonlinear
constrained optimisation, in the style of IPOPT, written against the Python array
API standard so it runs on NumPy, PyTorch, CuPy or JAX arrays. pyRadPlan uses it
as a pure-Python alternative to IPOPT for fluence optimisation.}

%description %_description

%package -n python3-%{pypi_name}
Summary:        %{summary}
Recommends:     python3-scipy
%description -n python3-%{pypi_name} %_description

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

%generate_buildrequires
%pyproject_buildrequires

%build
%pyproject_wheel

%install
%pyproject_install
%pyproject_save_files %{pypi_name}

%check
# Optional array backends: CuPy and JAX are not in Fedora, and PyTorch is not pulled in
# for a solver whose NumPy path is what pyRadPlan uses.
%pyproject_check_import -e 'ipax.backend.*.cupy' -e 'ipax.backend.*.torch' \
  -e 'ipax.problem.autodiff.jax' -e 'ipax.problem.autodiff.torch'
# GPU and sparse-direct adapters (cuDSS, nvmath, feral) are not in Fedora and skip;
# slow benchmarks are deselected.
%pytest -p no:cacheprovider tests -m "not slow and not gpu and not sparse" -o addopts="-ra"

%files -n python3-%{pypi_name} -f %{pyproject_files}
%license LICENSE NOTICE
%doc README.md

%changelog
* Fri Nov 06 2026 Morgan Hough <morgan.hough@gmail.com> - 0.13.0-1
- Initial package; pyRadPlan's interior-point fluence optimiser.