for MDP 3.1
===========

- find a solution to the __revision__ problem: should it be set on installation?
   numpy solved the problem, do we want to go this route?
- parallel: provide adapters for more sophisticated schedulers
- add _bias attribute to PCANode to make it more consistent with SFA node.
  Maybe one could even create a new AffineNode node as a base class for PCA,
  SFA and other affine transformations?
  This might also be a good opportunity for some more PEP8 cleanup.
- add more classifier stuff, like a ClassifierFlow
- add an example of training a node with multiple training phases using a flow,
  where the training is done first using lists and then using a custom iterators.
  special care should be taken on explaining how to pass additional arguments to
  the train method. an example of how this can look confusing and go wrong can be 
  found in the testFlowWrongItarableException test in test_flows.py
- fix damned LLENode test for 2D shape embedded in 3D!
- check that SparsePCA works on machine with scipy 0.9.0, add it to MDP if so
- create a Flow metaclass to enable Flow extensions (think of ParallelFlow!)
- implement an extension context manager with additional parameters and 
  exception handling. E.g.:
  flow = Flow([PCANode()])
  with extension('parallel', args=(ProcessScheduler,8)):
      flow.train(x)
  note that the context manager takes care of initialize and shutting down the
  scheduler. Proposed syntax:
  extension(string, args=tuple, kwargs=dictionary)
- bimdp: add deep belief network flow and nodes to the core bimdp
- add cross-correlation tools, maybe support the use of a parallel scheduler
- check problem with LLENode tutorial demo when using matplotlib 
  0.99.1.2, see Olivier Grisel's email
- LinearRegressionNode: add optional 2nd phase that computes residuals
  and significance of the slope
- provide a Node pickler, for arrays use the binary numpy format (npy,
  numpy.save, numpy.load) and not pickle: pickling arrays is unsupported
- add benchmarks for parallel module
- provide different versions of the MDP logo which includes the
  website address, possibly one higher quality print version,
  available in "how to cite" section
- short and long description in a single file, automatically 
  updated everywhere (tutorial, sf.net, setup.py, webpage, 
  MDP announcement, ...) 
- Use the new property decorators when migrating to Python 2.6 (see
  http://docs.python.org/library/functions.html#property).
- kalman filters
- memory profiler
- GUI