Metadata-Version: 2.4
Name: optiprofiler
Version: 1.3.1
Summary: Benchmarking optimization solvers
Author-email: Cunxin Huang <cun-xin.huang@connect.polyu.hk>, "Tom M. Ragonneau" <tom.ragonneau@polyu.edu.hk>, Zaikun Zhang <zaikun.zhang@polyu.edu.hk>
Maintainer-email: Cunxin Huang <cun-xin.huang@connect.polyu.hk>, "Tom M. Ragonneau" <tom.ragonneau@polyu.edu.hk>, Zaikun Zhang <zaikun.zhang@polyu.edu.hk>
License: BSD 3-Clause License
        
        Copyright (c) 2023-2025, Cunxin Huang, Tom M. Ragonneau, and Zaikun Zhang
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        1. Redistributions of source code must retain the above copyright notice, this
           list of conditions and the following disclaimer.
        
        2. Redistributions in binary form must reproduce the above copyright notice,
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Project-URL: homepage, https://www.optprof.com
Project-URL: documentation, http://www.optprof.com
Project-URL: source, https://github.com/optiprofiler/optiprofiler
Project-URL: download, https://pypi.org/project/optiprofiler/#files
Project-URL: tracker, https://github.com/optiprofiler/optiprofiler/issues
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Testing
Requires-Python: >=3.8
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: matplotlib>=3.4.0
Requires-Dist: numpy>=1.17.0
Requires-Dist: scipy>=1.10.0
Requires-Dist: pandas>=1.1.0
Requires-Dist: h5py>=3.0.0
Requires-Dist: pypdf>=3.8.0
Provides-Extra: doc
Requires-Dist: numpydoc==1.7.0; extra == "doc"
Requires-Dist: Sphinx==7.3.6; extra == "doc"
Requires-Dist: sphinx-copybutton==0.5.2; extra == "doc"
Requires-Dist: sphinx-book-theme==1.1.2; extra == "doc"
Requires-Dist: sphinx-design==0.5.0; extra == "doc"
Requires-Dist: sphinxcontrib-bibtex==2.6.2; extra == "doc"
Requires-Dist: sphinxcontrib-matlabdomain; extra == "doc"
Requires-Dist: sphinxext-opengraph; extra == "doc"
Provides-Extra: extra
Requires-Dist: pycutest>=1.6.1; extra == "extra"
Provides-Extra: tests
Requires-Dist: pytest; extra == "tests"
Requires-Dist: pytest-cov; extra == "tests"
Dynamic: license-file

OptiProfiler: a platform for benchmarking optimization solvers
==============================================================

|docs_badge| |codecov_badge|

|py_unit| |py_multi_os| |py_random| |py_stress|

|ml_unit| |ml_multi_os| |ml_random| |ml_stress|

.. |docs_badge| image:: https://img.shields.io/readthedocs/optiprofiler/latest?logo=readthedocs&style=for-the-badge
    :target: http://www.optprof.com
.. |codecov_badge| image:: https://img.shields.io/codecov/c/github/optiprofiler/optiprofiler?style=for-the-badge&logo=codecov
   :target: https://app.codecov.io/github/optiprofiler/optiprofiler/tree/main
.. |py_unit| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-unit_test.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-unit_test.yml
.. |py_multi_os| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-test_multi-os.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-test_multi-os.yml
.. |py_random| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-random_test.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-random_test.yml
.. |py_stress| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-stress_test.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/python-stress_test.yml
.. |ml_unit| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-unit_test.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-unit_test.yml
.. |ml_multi_os| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-test_multi-os.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-test_multi-os.yml
.. |ml_random| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-random_test.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-random_test.yml
.. |ml_stress| image:: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-stress_test.yml/badge.svg
   :target: https://github.com/optiprofiler/optiprofiler/actions/workflows/matlab-stress_test.yml

🌐 **Website:** `www.optprof.com <https://www.optprof.com>`_

Python
------

Install OptiProfiler from PyPI:

.. code-block:: bash

    pip install optiprofiler

You can also install OptiProfiler from conda-forge:

.. code-block:: bash

    conda install conda-forge::optiprofiler

.. note::

    OptiProfiler includes the `S2MPJ <https://github.com/GrattonToint/S2MPJ>`_ problem library by default. Optional problem libraries include `PyCUTEst <https://jfowkes.github.io/pycutest/>`_ and the SOLAR adapter. PyCUTEst requires a separate installation. SOLAR uses a slim runtime derived from `bbopt/solar <https://github.com/bbopt/solar>`_ under LGPL-2.1; see the adapter README and runtime manifest for provenance.

MATLAB
------

1. Clone the repository using the following command:

.. code-block:: bash

    git clone https://github.com/optiprofiler/optiprofiler.git

2. In MATLAB, navigate to the folder where the source code is located, and you will see a file named ``setup.m``. Run the following command in the MATLAB command window:

.. code-block:: matlab

    setup

If the optional SOLAR MATLAB adapter is not installed locally, ``setup``
asks whether to download it. For non-interactive scripts, pass the choice
explicitly:

.. code-block:: matlab

    setup(struct('install_solar', true))
    setup(struct('install_solar', false))

When accepted or requested, ``setup`` clones `optiprofiler/solar_matlab
<https://github.com/optiprofiler/solar_matlab>`_ into the local directory
``matlab/optiprofiler/problem_libs/solar`` and adds it to the MATLAB path.
This directory is a local optional installation, not a submodule of the
OptiProfiler repository. Passing ``install_solar=false`` skips the prompt and
optional download when the adapter is not installed locally, which is useful
in CI and batch scripts.
The public problem-library name remains ``solar``; use ``plibs={'solar'}``
in MATLAB benchmark options.
