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DFO-GN: Derivative-Free Nonlinear Least-Squares Solver |PyPI Version|
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DFO-GN is a package for solving nonlinear least-squares minimisation, without requiring derivatives of the objective.
This is an implementation of the algorithm from our paper:
`A Derivative-Free Gauss-Newton Method <https://arxiv.org/abs/1710.11005>`_, C. Cartis and L. Roberts, submitted (2017). For reproducibility of all figures in this paper, please feel free to contact the authors.
Note: we have released a newer package, called DFO-LS, which is an upgrade of DFO-GN to improve its flexibility and robustness to noisy problems. See `here <https://github.com/numericalalgorithmsgroup/dfols>`_ for details.
Documentation
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See manual.pdf or `here <https://numericalalgorithmsgroup.github.io/dfogn/>`_.
Requirements
------------
DFO-GN 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 <http://www.pip-installer.org/>`_, see `Installation using pip`_):
* `NumPy 1.11 or higher <http://www.numpy.org/>`_
* `SciPy 0.18 or higher <http://www.scipy.org/>`_
Installation using pip
----------------------
For easy installation, use `pip <http://www.pip-installer.org/>`_ as root:
.. code-block:: bash
$ [sudo] pip install --pre dfogn
If you do not have root privileges or you want to install DFO-GN for your private use, you can use:
.. code-block:: bash
$ pip install --pre --user dfogn
which will install DFO-GN in your home directory.
Note that if an older install of DFO-GN is present on your system you can use:
.. code-block:: bash
$ [sudo] pip install --pre --upgrade dfogn
to upgrade DFO-GN to the latest version.
Manual installation
-------------------
The source code for DFO-GN is `available on Github <https://https://github.com/numericalalgorithmsgroup/dfogn>`_:
.. code-block:: bash
$ git clone https://github.com/numericalalgorithmsgroup/dfogn
$ cd dfogn
DFO-GN is written in pure Python and requires no compilation. It can be installed using:
.. code-block:: bash
$ [sudo] pip install --pre .
If you do not have root privileges or you want to install DFO-GN for your private use, you can use:
.. code-block:: bash
$ pip install --pre --user .
instead.
Testing
-------
If you installed DFO-GN manually, you can test your installation by running:
.. code-block:: bash
$ python setup.py test
Alternatively, the `documentation <https://numericalalgorithmsgroup.github.io/dfogn/>`_ provides some simple examples of how to run DFO-GN, which are also available in the examples directory.
.. |PyPI Version| image:: https://img.shields.io/pypi/v/DFOGN.svg
:target: https://pypi.python.org/pypi/DFOGN
