Installing DFO-LS
=================

Requirements
------------
DFO-LS requires the following software to be installed:

* Python 3.9 or higher (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 (http://www.numpy.org/)
* SciPy version 1.11 or higher (http://www.scipy.org/)
* Pandas (http://pandas.pydata.org/)

**Optional package:** DFO-LS versions 1.2 and higher also support the `trustregion <https://github.com/lindonroberts/trust-region>`_ package for fast trust-region subproblem solutions. To install this, make sure you have a Fortran compiler (e.g. `gfortran <https://gcc.gnu.org/wiki/GFortran>`_) and NumPy installed, then run :code:`pip install trustregion`. You do not have to have trustregion installed for DFO-LS to work, and it is not installed by default.

Installation using conda
------------------------
DFO-LS can be directly installed in Anaconda environments using `conda-forge <https://anaconda.org/conda-forge/dfo-ls>`_:

 .. code-block:: bash

    $ conda install -c conda-forge dfo-ls

Installation using pip
----------------------
For easy installation, use *pip* (http://www.pip-installer.org/) as root:

 .. code-block:: bash

    $ pip install DFO-LS

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

 .. code-block:: bash

    $ pip install --upgrade DFO-LS

to upgrade DFO-LS to the latest version.

Manual installation
-------------------
Alternatively, you can download the source code from `Github <https://github.com/numericalalgorithmsgroup/dfols>`_ and unpack as follows:

 .. code-block:: bash

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

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

 .. code-block:: bash

    $ pip install .

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

 .. code-block:: bash

    $ git pull
    $ pip install .

Testing
-------
If you installed DFO-LS manually, you can test your installation using the pytest package:

 .. code-block:: bash

    $ pip install pytest
    $ python -m pytest --pyargs dfols

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

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

 .. code-block:: bash

    $ 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).