| Name | cobyqa JSON |
| Version |
1.1.1
JSON |
| download |
| home_page | |
| Summary | Constrained Optimization BY Quadratic Approximations |
| upload_time | 2024-03-12 07:46:31 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | BSD 3-Clause License Copyright (c) 2021-2024, 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, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
blackbox-optimization
constrained-optimization
derivative-free-optimization
hyperparameter-optimization
nonlinear-optimization
numerical-optimization
optimization
optimization-algorithms
optimization-methods
optimization-tools
simulation-based-optimization
unconstrained-optimization
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
COBYQA: Constrained Optimization BY Quadratic Approximations
============================================================
.. image:: https://img.shields.io/github/actions/workflow/status/cobyqa/cobyqa/build.yml?logo=github&style=for-the-badge
:target: https://github.com/cobyqa/cobyqa/actions/workflows/build.yml
.. image:: https://img.shields.io/readthedocs/cobyqa/latest?logo=readthedocs&style=for-the-badge
:target: https://www.cobyqa.com/
.. image:: https://img.shields.io/codecov/c/github/cobyqa/cobyqa?logo=codecov&style=for-the-badge
:target: https://codecov.io/gh/cobyqa/cobyqa/
.. image:: https://img.shields.io/pypi/v/cobyqa?logo=pypi&style=for-the-badge
:target: https://pypi.org/project/cobyqa/
.. image:: https://img.shields.io/pypi/dm/cobyqa?logo=pypi&style=for-the-badge
:target: https://pypi.org/project/cobyqa/
.. image:: https://img.shields.io/conda/v/conda-forge/cobyqa?logo=anaconda&style=for-the-badge&label=conda-forge
:target: https://anaconda.org/conda-forge/cobyqa
.. image:: https://img.shields.io/conda/d/conda-forge/cobyqa?logo=anaconda&style=for-the-badge&label=downloads
:target: https://anaconda.org/conda-forge/cobyqa
COBYQA, an acronym for *Constrained Optimization BY Quadratic Approximations*, is designed to supersede `COBYLA <https://docs.scipy.org/doc/scipy/reference/optimize.minimize-cobyla.html>`_ as a general derivative-free optimization solver.
It can handle unconstrained, bound-constrained, linearly constrained, and nonlinearly constrained problems.
It uses only function values of the objective and constraint functions, if any.
No derivative information is needed.
**Documentation:** https://www.cobyqa.com.
Installation
------------
COBYQA can be installed for `Python 3.8 or above <https://www.python.org>`_.
Dependencies
~~~~~~~~~~~~
The following Python packages are required by COBYQA:
* `NumPy <https://www.numpy.org>`_ 1.17.0 or higher, and
* `SciPy <https://www.scipy.org>`_ 1.10.0 or higher.
If you install COBYQA using ``pip`` or ``conda`` (see below), these dependencies will be installed automatically.
More dependencies are required to run the test suite and some examples given in the folder ``examples``.
See the relevant sections below for more details.
User installation
~~~~~~~~~~~~~~~~~
The easiest way to install COBYQA is using ``pip`` or ``conda``.
To install it using ``pip``, run in a terminal or command window
.. code:: bash
pip install cobyqa
If you are using ``conda``, you can install COBYQA from the `conda-forge <https://anaconda.org/conda-forge/cobyqa>`_ channel by running
.. code:: bash
conda install conda-forge::cobyqa
To check your installation, you can execute
.. code:: bash
python -c "import cobyqa; cobyqa.show_versions()"
If your python launcher is not ``python``, you can replace it with the appropriate command (similarly for ``pip`` and ``conda``).
For example, you may need to use ``python3`` instead of ``python`` and ``pip3`` instead of ``pip``.
Testing
~~~~~~~
To execute the test suite of COBYQA, you first need to install ``pytest``.
You can then run the test suite by executing
.. code:: bash
pytest --pyargs cobyqa
The test suite takes several minutes to run.
It is unnecessary to run the test suite if you installed COBYQA using the recommended method described above.
Examples
--------
The folder ``examples`` contains a few examples of how to use COBYQA.
To run ``powell2015.py``, you first need to install ``matplotlib``.
These files contains headers explaining what problems they solve.
Support
-------
To report a bug or request a new feature, please open a new issue using the `issue tracker <https://github.com/cobyqa/cobyqa/issues>`_.
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