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.
sudo aptitude install python-mdp
Gentoo users can install the ebuild sci-mathematics/mdp from the
Use your favourite package manager or, alternatively:
emerge layman layman -L layman -a science emerge sci-mathematics/mdp
Installation from source¶
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.
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/
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;
Convolution2DNode, using the fast convolution routines in SciPy.
- Parallel Python: provide the
parallel python scheduler
- LibSVM ≥ 2.91:
- joblib ≥ 0.4.3: provide the
cachingextension and the corresponding
- sklearn ≥ 0.6: provide wrapper nodes to several sklearn algorithms.
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.
MDP is distributed under the open source BSD license.
This file is part of Modular toolkit for Data Processing (MDP). All the code in this package is distributed under the following conditions: Copyright (c) 2003-2016, MDP Developers <firstname.lastname@example.org> All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the Modular toolkit for Data Processing (MDP) nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.