Installation

You can install coclust with all the dependencies with:

pip install "coclust[alldeps]"

It will install the following libraries:

• numpy
• scipy
• scikit-learn
• matplotlib

If you only want to use co-clustering algorithms and don’t want to install visualization or evaluation dependencies, you can install it with:

pip install coclust

It will install the following required libraries:

• numpy
• scipy
• scikit-learn

Windows users

It is recommended to use a third party distribution to install the dependencies before installing coclust. For example, when using the Continuum distribution, go to the download site to get and double-click the graphical installer. Then, enter pip install coclust at the command line.

Linux users

It is recommended to install the dependencies with your package manager. For example, on Ubuntu or Debian:

sudo apt-get install python-numpy python-scipy python-sklearn python-matplotlib
sudo pip install coclust

Performance note

OpenBLAS provides a fast multi-threaded implementation, you can install it with:

sudo apt-get install libopenblas-base

If other implementations are installed on your system, you can select OpenBLAS with:

sudo update-alternatives --config libblas.so.3

Running the tests

In order to run the tests, you have to install nose, for example with:

pip install nose

You also have to get the datasets used for the tests:

git clone https://github.com/franrole/cclust_package.git

And then, run the tests:

cd cclust_package
nosetests --with-coverage --cover-inclusive --cover-package=coclust