ANN: MDP release 2.6 and MDP Sprint 2010

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ANN: MDP release 2.6 and MDP Sprint 2010

Tiziano Zito-2
We are glad to announce release 2.6 of the Modular toolkit for Data
Processing (MDP).

MDP is a Python library of widely used data processing algorithms
that can be combined according to a pipeline analogy to build more
complex data processing software. The base of available algorithms
includes, to name but the most common, Principal Component Analysis
(PCA and NIPALS), several Independent Component Analysis algorithms
(CuBICA, FastICA, TDSEP, JADE, and XSFA), Slow Feature Analysis,
Restricted Boltzmann Machine, and Locally Linear Embedding.

What's new in version 2.6?

- Several new classifier nodes have been added.
- A new node extension mechanism makes it possible to dynamically
  add methods or attributes for specific features to node classes,
  enabling aspect-oriented programming in MDP. Several MDP features
  (like parallelization) are now based on this mechanism, and users
  can add their own custom node extensions.
- BiMDP is a large new package in MDP that introduces bidirectional
  data flows to MDP, including backpropagation and even loops. BiMDP
  also enables the transportation of additional data in flows via
- BiMDP includes a new flow inspection tool, that runs as as a
  graphical debugger in the webrowser to step through complex flows.
  It can be extended by users for the analysis and visualization of
  intermediate data.
- As usual, tons of bug fixes

The new additions in the library have been thoroughly tested but, as
usual after a public release, we especially welcome user's feedback
and bug reports.

MDP Sprint 2010

Following our tradition of sprint-driven development, the team of the
core developers decided to organize a programming sprint open to
external participants. We invite in particular all users who
implemented new algorithms and would like to see them integrated in
MDP: you will work together with a core developer!
More info: 

Mailing list:


Pietro Berkes
Volen Center for Complex Systems
Brandeis University
Waltham, MA, USA

Rike-Benjamin Schuppner
Berlin, Germany

Niko Wilbert
Institute for Theoretical Biology
Berlin, Germany

Tiziano Zito
Modelling of Cognitive Processes
Berlin Institute of Technology and
Bernstein Center for Computational Neuroscience
Berlin, Germany

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