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Sparse Optimisation Research Code

Project description

SPORCO is a Python package for solving optimisation problems with sparsity-inducing regularisation. These consist primarily of sparse coding and dictionary learning problems, including convolutional sparse coding and dictionary learning, but there is also support for other problems such as Total Variation regularisation and Robust PCA. In the current version all of the optimisation algorithms are based on the Alternating Direction Method of Multipliers (ADMM).

Requirements

The primary requirements are Python itself (SPORCO has only been tested on version 2.7), and modules scipy, numpy, pyfftw, and matplotlib. Module numexpr is not required, but some functions will be faster if it is installed.

Installation of these requirements is system dependent. Under a recent version of Ubuntu Linux, the following commands should be sufficient:

sudo apt-get install python-numpy
sudo apt-get install python-scipy
sudo apt-get install python-matplotlib
sudo apt-get install python-pip
sudo apt-get install libfftw3-dev
sudo pip install pyfftw

Installation

python setup.py build
python setup.py install

The install command will usually have to be performed with root permissions.

Usage

Scripts illustrating usage of the package can be found in the examples directory. These examples can be run from the root directory of the package by, for example

python examples/demo_bpdn.py

To run these scripts prior to installing the package it will be necessary to first set the PYTHONPATH environment variable to include the root directory of the package. For example, in a bash shell

export PYTHONPATH=$PYTHONPATH:`pwd`

from the root directory of the package.

Documentation

If the source has been obtained from a source distribution package then HTML documentation can be built in the build/sphinx/html directory (the top-level document is index.html) by the command

python setup.py build_sphinx

If the source has been cloned from the project github, it is necessary to first issue the command

sphinx-apidoc --separate -d 2 -o source ../sporco modules.rst

within the docs directory.

License

This package is distributed with a BSD license; see the LICENSE file for details.

Project details


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