ANN: MDP 1.1.0
t.zito at biologie.hu-berlin.de
Mon Jun 13 13:49:46 CEST 2005
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
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
* 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)
Institute for Theoretical Biology
Humboldt-Universitaet zu Berlin
D-10115 Berlin, Germany
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