A flexible derivative-free solver for (bound constrained) general objective minimization
Project description
===================================================================================
Py-BOBYQA: Derivative-Free Solver for Bound-Constrained Minimization |PyPI Version|
===================================================================================
Py-BOBYQA is a flexible package for solving bound-constrained general objective minimization, without requiring derivatives of the objective. It is a Python implementation of the BOBYQA algorithm by Powell. Py-BOBYQA is particularly useful when evaluations of the objective function are expensive and/or noisy.
More details about Py-BOBYQA can be found in our paper: C. Cartis, J. Fiala, B. Marteau and L. Roberts, Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers, technical report, University of Oxford, (2018).
The original paper by Powell is: M. J. D. Powell, The BOBYQA algorithm for bound constrained optimization without derivatives, technical report DAMTP 2009/NA06, University of Cambridge (2009), and the original Fortran implementation is available `here <http://mat.uc.pt/~zhang/software.html>`_.
If you are interested in solving least-squares minimization problems, you may wish to try `DFO-LS <https://github.com/numericalalgorithmsgroup/dfols>`_, which has the same features as Py-BOBYQA (plus some more), and exploits the least-squares problem structure, so performs better on such problems.
Documentation
-------------
See manual.pdf or `here <http://people.maths.ox.ac.uk/robertsl/pybobyqa>`_.
Requirements
------------
Py-BOBYQA requires the following software to be installed:
* Python 2.7 or Python 3 (http://www.python.org/)
Additionally, the following python packages should be installed (these will be installed automatically if using *pip*, see `Installation using pip`_):
* NumPy 1.11 or higher (http://www.numpy.org/)
* SciPy 0.18 or higher (http://www.scipy.org/)
* Pandas 0.17 or higher (http://pandas.pydata.org/)
Installation using pip
----------------------
For easy installation, use `pip <http://www.pip-installer.org/>`_ as root::
$ [sudo] pip install Py-BOBYQA
or alternatively *easy_install*::
$ [sudo] easy_install Py-BOBYQA
If you do not have root privileges or you want to install Py-BOBYQA for your private use, you can use::
$ pip install --user Py-BOBYQA
which will install Py-BOBYQA in your home directory.
Note that if an older install of Py-BOBYQA is present on your system you can use::
$ [sudo] pip install --upgrade Py-BOBYQA
to upgrade Py-BOBYQA to the latest version.
Manual installation
-------------------
Alternatively, you can download the source code from `Github <https://github.com/numericalalgorithmsgroup/pybobyqa>`_ and unpack as follows:
.. code-block:: bash
$ git clone https://github.com/numericalalgorithmsgroup/pybobyqa
$ cd pybobyqa
Py-BOBYQA is written in pure Python and requires no compilation. It can be installed using:
.. code-block:: bash
$ [sudo] pip install .
If you do not have root privileges or you want to install Py-BOBYQA for your private use, you can use:
.. code-block:: bash
$ pip install --user .
instead.
Testing
-------
If you installed Py-BOBYQA manually, you can test your installation by running:
.. code-block:: bash
$ python setup.py test
Alternatively, the HTML documentation provides some simple examples of how to run Py-BOBYQA.
Examples
--------
Examples of how to run Py-BOBYQA are given in the `documentation <http://people.maths.ox.ac.uk/robertsl/pybobyqa>`_, and the `examples <https://github.com/numericalalgorithmsgroup/pybobyqa/tree/master/examples>`_ directory in Github.
Uninstallation
--------------
If Py-BOBYQA was installed using *pip* you can uninstall as follows:
.. code-block:: bash
$ [sudo] pip uninstall Py-BOBYQA
If Py-BOBYQA was installed manually you have to remove the installed files by hand (located in your python site-packages directory).
Bugs
----
Please report any bugs using GitHub's issue tracker.
License
-------
This algorithm is released under the GNU GPL license.
.. |PyPI Version| image:: https://img.shields.io/pypi/v/Py-BOBYQA.svg
:target: https://pypi.python.org/pypi/Py-BOBYQA
Py-BOBYQA: Derivative-Free Solver for Bound-Constrained Minimization |PyPI Version|
===================================================================================
Py-BOBYQA is a flexible package for solving bound-constrained general objective minimization, without requiring derivatives of the objective. It is a Python implementation of the BOBYQA algorithm by Powell. Py-BOBYQA is particularly useful when evaluations of the objective function are expensive and/or noisy.
More details about Py-BOBYQA can be found in our paper: C. Cartis, J. Fiala, B. Marteau and L. Roberts, Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers, technical report, University of Oxford, (2018).
The original paper by Powell is: M. J. D. Powell, The BOBYQA algorithm for bound constrained optimization without derivatives, technical report DAMTP 2009/NA06, University of Cambridge (2009), and the original Fortran implementation is available `here <http://mat.uc.pt/~zhang/software.html>`_.
If you are interested in solving least-squares minimization problems, you may wish to try `DFO-LS <https://github.com/numericalalgorithmsgroup/dfols>`_, which has the same features as Py-BOBYQA (plus some more), and exploits the least-squares problem structure, so performs better on such problems.
Documentation
-------------
See manual.pdf or `here <http://people.maths.ox.ac.uk/robertsl/pybobyqa>`_.
Requirements
------------
Py-BOBYQA requires the following software to be installed:
* Python 2.7 or Python 3 (http://www.python.org/)
Additionally, the following python packages should be installed (these will be installed automatically if using *pip*, see `Installation using pip`_):
* NumPy 1.11 or higher (http://www.numpy.org/)
* SciPy 0.18 or higher (http://www.scipy.org/)
* Pandas 0.17 or higher (http://pandas.pydata.org/)
Installation using pip
----------------------
For easy installation, use `pip <http://www.pip-installer.org/>`_ as root::
$ [sudo] pip install Py-BOBYQA
or alternatively *easy_install*::
$ [sudo] easy_install Py-BOBYQA
If you do not have root privileges or you want to install Py-BOBYQA for your private use, you can use::
$ pip install --user Py-BOBYQA
which will install Py-BOBYQA in your home directory.
Note that if an older install of Py-BOBYQA is present on your system you can use::
$ [sudo] pip install --upgrade Py-BOBYQA
to upgrade Py-BOBYQA to the latest version.
Manual installation
-------------------
Alternatively, you can download the source code from `Github <https://github.com/numericalalgorithmsgroup/pybobyqa>`_ and unpack as follows:
.. code-block:: bash
$ git clone https://github.com/numericalalgorithmsgroup/pybobyqa
$ cd pybobyqa
Py-BOBYQA is written in pure Python and requires no compilation. It can be installed using:
.. code-block:: bash
$ [sudo] pip install .
If you do not have root privileges or you want to install Py-BOBYQA for your private use, you can use:
.. code-block:: bash
$ pip install --user .
instead.
Testing
-------
If you installed Py-BOBYQA manually, you can test your installation by running:
.. code-block:: bash
$ python setup.py test
Alternatively, the HTML documentation provides some simple examples of how to run Py-BOBYQA.
Examples
--------
Examples of how to run Py-BOBYQA are given in the `documentation <http://people.maths.ox.ac.uk/robertsl/pybobyqa>`_, and the `examples <https://github.com/numericalalgorithmsgroup/pybobyqa/tree/master/examples>`_ directory in Github.
Uninstallation
--------------
If Py-BOBYQA was installed using *pip* you can uninstall as follows:
.. code-block:: bash
$ [sudo] pip uninstall Py-BOBYQA
If Py-BOBYQA was installed manually you have to remove the installed files by hand (located in your python site-packages directory).
Bugs
----
Please report any bugs using GitHub's issue tracker.
License
-------
This algorithm is released under the GNU GPL license.
.. |PyPI Version| image:: https://img.shields.io/pypi/v/Py-BOBYQA.svg
:target: https://pypi.python.org/pypi/Py-BOBYQA
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