MDP 1.1.0 --------- http://mdp-toolkit.sourceforge.net/ Modular toolkit for Data Processing (MDP) is a Python library to perform data processing. Already implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), and Growing Neural Gas (GNG). MDP allows to combine different algorithms and other data processing elements (nodes) into data processing sequences (flows). Moreover, it provides a framework that makes the implementation of new algorithms easy and intuitive. MDP supports the most common numerical extensions to Python, currently Numeric, Numarray, SciPy. When used together with SciPy and the symeig package, MDP gives to the scientific programmer the full power of well-known C and FORTRAN data processing libraries. MDP helps the programmer to exploit Python object oriented design with C and FORTRAN efficiency. MDP has been written for research in neuroscience, but it has been designed to be helpful in any context where trainable data processing algorithms are used. Its simplicity on the user side together with the reusability of the implemented nodes could make it also a valid educational tool. Requirements: * Python >= 2.3 * one of the following Python numerical extensions: Numeric, Numarray, or SciPy. For optimal performance we recommend to use SciPy with LAPACK and ATLAS libraries, and to install the symeig module. (sorry for multiple posting) -- Tiziano Zito Institute for Theoretical Biology Humboldt-Universitaet zu Berlin Invalidenstrasse, 43 D-10115 Berlin, Germany http://itb.biologie.hu-berlin.de/~zito/