Installation¶
You can install using pip (Windows, MacOSX, Linux), binary packages or from source.
pip (Windows, MacOSX, Linux)¶
MDP is listed in the Python Package Index and can be installed with pip:
pip install MDP
This is the preferred method of installation if you are using Windows or MacOSX.
Binary packages (Linux/BSD)¶
Debian, Ubuntu and derivatives¶
Thanks to Yaroslav Halchenko, users of Debian, Ubuntu and derivatives can install the python-mdp package.
Just type:
sudo aptitude install python-mdp
Gentoo¶
Gentoo users can install the ebuild sci-mathematics/mdp from the
science
overlay.
Use your favourite package manager or, alternatively:
emerge layman
layman -L
layman -a science
emerge sci-mathematics/mdp
Installation from source¶
Requirements¶
Download the latest MDP release source archive here.
If you want to live on the bleeding edge, check out the MDP git repositories.
You can either browse the repository
or clone the mdp-toolkit
repository with:
git clone git://github.com/mdp-toolkit/mdp-toolkit
and then install as explained below.
Installation¶
Unpack the archive file and change to the project directory or change to the cloned git repository, and type:
python setup.py install
If you want to use MDP without installing it on the system Python path:
python setup.py install --prefix=/some_dir_in_PYTHONPATH/
Optional Libraries¶
MDP can make use of several additional libraries if they are installed on your system. They are not required for using MDP, but may give more functionality. Here a list of optional libraries and the corresponding additional features in MDP:
SciPy ≥ 0.5.2: Use the fast and efficient LAPACK wrapper for the symmetrical eigensolver, used interally by many nodes; use the fast FFT routines in some nodes; provide the
Convolution2DNode
, using the fast convolution routines in SciPy.Parallel Python: provide the parallel python scheduler
PPScheduler
in theparallel
module.LibSVM ≥ 2.91: provide the
LibSVMClassifier
node.joblib ≥ 0.4.3: provide the
caching
extension and the correspondingcache
context manager.sklearn ≥ 0.6: provide wrapper nodes to several sklearn algorithms.
Testing¶
If you have successfully installed MDP, you can test your installation in a Python shell as follows:
>>> import mdp
>>> mdp.test()
>>> import bimdp
>>> bimdp.test()
Note that you will need to install pytest to run the tests.
If some test fails, please report it to the mailing list.
License¶
MDP is distributed under the open source BSD license.