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A flexible derivative-free solver for (bound constrained) nonlinear least-squares minimization

Project description

Build Status GNU GPL v3 License Latest PyPI version

DFO-LS is a flexible package for solving nonlinear least-squares minimisation, without requiring derivatives of the objective. It is particularly useful when evaluations of the objective function are expensive and/or noisy.

This is an implementation of the algorithm from 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). DFO-LS is more flexible version of DFO-GN.

If you are interested in solving general optimization problems (without a least-squares structure), you may wish to try Py-BOBYQA, which has many of the same features as DFO-LS.


See manual.pdf or here.


DFO-LS requires the following software to be installed:

Additionally, the following python packages should be installed (these will be installed automatically if using pip, see Installation using pip):

Installation using pip

For easy installation, use pip as root:

$ [sudo] pip install DFO-LS

or alternatively easy_install:

$ [sudo] easy_install DFO-LS

If you do not have root privileges or you want to install DFO-LS for your private use, you can use:

$ pip install --user DFO-LS

which will install DFO-LS in your home directory.

Note that if an older install of DFO-LS is present on your system you can use:

$ [sudo] pip install --upgrade DFO-LS

to upgrade DFO-LS to the latest version.

Manual installation

Alternatively, you can download the source code from Github and unpack as follows:

$ git clone
$ cd dfols

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

$ [sudo] pip install .

If you do not have root privileges or you want to install DFO-LS for your private use, you can use:

$ pip install --user .


To upgrade DFO-LS to the latest version, navigate to the top-level directory (i.e. the one containing and rerun the installation using pip, as above:

$ git pull
$ [sudo] pip install .  # with admin privileges


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

$ python test

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


Examples of how to run DFO-LS are given in the documentation, and the examples directory in Github.


If DFO-LS was installed using pip you can uninstall as follows:

$ [sudo] pip uninstall DFO-LS

If DFO-LS was installed manually you have to remove the installed files by hand (located in your python site-packages directory).


Please report any bugs using GitHub’s issue tracker.


This algorithm is released under the GNU GPL license. Please contact NAG for alternative licensing.

Project details

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