DFOGN 0.1

A simple derivative-free solver for (box constrained) nonlinear least-squares minimization

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, C. Cartis and L. Roberts, submitted (2017).

Documentation

Documentation for DFO-GN is available at [URL].

Requirements

DFO-GN requires the following software to be installed:

• Python 2.7 or Python 3

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

• SciPy 0.18 or higher

Installation using pip

For easy installation, use pip as root:

$ [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:

$ 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:

$ [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:

$ git clone https://github.com/numericalalgorithmsgroup/dfogn
$ cd dfogn

or through the Python Package Index:

$ wget http://pypi.python.org/packages/source/d/dfogn/dfogn-X.X.tar.gz
$ tar -xzvf dfogn-X.X.tar.gz
$ cd dfogn-X.X

DFO-GN is written in pure Python and requires no compilation. It can be installed using:

$ [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:

$ pip install --pre --user .

instead.

Testing

If you installed DFO-GN manually, you can test your installation by running:

$ python setup.py test

Alternatively, the HTML documentation provides some simple examples of how to run DFO-GN.