ENH: swaroop is playing with hyperalignment trying to decrease performance to match matlab
adding few debug printouts to troubleshoot timing within DS
Merge remote branch 'pymvpa/master' into tent/hyper_enhancements
Corrected a typo in Splitter doc string.
ENH: Changed the computation of Pearson correlation in DSMatrix top use np.corrcoef instead of nested for loop.
BF: Accidentally changed Spearman instead of Pearson correlation in DSMatrix
Added Zscores
Merge remote branch 'pymvpa/master' into tent/hyper_enhancements

Conflicts:
	mvpa/generators/splitters.py
minor fix, found uncommitted
BF: explicitly turn-off compression off for scalar datatypes

required for h5py >= 2.0.0; otherwise leads to:

ERROR: mvpa2.tests.test_hdf5.test_dataset_without_chunks
  ----------------------------------------------------------------------
  Traceback (most recent call last):
    File "/usr/lib/pymodules/python2.6/nose/case.py", line 187, in runTest
      self.test(*self.arg)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/tests/test_hdf5.py", line 156, in test_dataset_without_chunks
      save(ds, f.name, compression='gzip')
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/dataset.py", line 837, in save
      obj2hdf(hdf, dataset, name, compression=compression)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 601, in obj2hdf
      _seqitems_to_hdf(pieces[1], args, memo, **kwargs)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 397, in _seqitems_to_hdf
      obj2hdf(items, item, name=str(i), memo=memo, noid=noid, **kwargs)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 581, in obj2hdf
      noid=True, **kwargs)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 397, in _seqitems_to_hdf
      obj2hdf(items, item, name=str(i), memo=memo, noid=noid, **kwargs)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 575, in obj2hdf
      _seqitems_to_hdf(obj, grp, memo, **kwargs)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 397, in _seqitems_to_hdf
      obj2hdf(items, item, name=str(i), memo=memo, noid=noid, **kwargs)
    File "/home/neurodebian/proj/pymvpa/logs/daily/pymvpa_tests-20111010_173301/PyMVPA/mvpa2/base/hdf5.py", line 486, in obj2hdf
      hdf.create_dataset(name, None, None, obj, **kwargs)
    File "/usr/lib/python2.6/dist-packages/h5py/_hl/group.py", line 69, in create_dataset
      dsid = dataset.make_new_dset(self, shape, dtype, data, **kwds)
    File "/usr/lib/python2.6/dist-packages/h5py/_hl/dataset.py", line 79, in make_new_dset
      shuffle, fletcher32, maxshape)
    File "/usr/lib/python2.6/dist-packages/h5py/_hl/filters.py", line 71, in generate_dcpl
      raise TypeError("Scalar datasets don't support chunk/filter options")
  TypeError: Scalar datasets don't support chunk/filter options
BF: workaround for unittest failure due to h5py returning scalars of type np.bool_ instead of bool

probably correct solution lays down in figuring out why h5py does that
and either it is not a bug, and possibly making sure at the level of
pymvpa to assure consistent typing
ENH: use with_tempfile decorator for test_h5py_io
ENH: obj2hdf -- mark numpy scalars explicitly as such, otherwise use np.asscalar while loading
ENH: removing custom workaround introduced in 0f88d4c54c40112e489fdc060dc90dfdfdd4b7df

with non-ambiguous handling of python_scalars-vs-numpy_scalars
introduced in 7e6d0f20102ffa65fe83cb04729f869c6a8065e7 we should not
require custom handling
cosmit
DOC: added a docstring to recently added get_vmem
Merge remote branch 'gh-yarikoptic/master'

* gh-yarikoptic/master: (34 commits)
  DOC: added a docstring to recently added get_vmem
  cosmit
  ENH: removing custom workaround introduced in 0f88d4c54c40112e489fdc060dc90dfdfdd4b7df
  ENH: obj2hdf -- mark numpy scalars explicitly as such, otherwise use np.asscalar while loading
  ENH: use with_tempfile decorator for test_h5py_io
  BF: workaround for unittest failure due to h5py returning scalars of type np.bool_ instead of bool
  BF: explicitly turn-off compression off for scalar datatypes
  DOC: updating references to Jonas's paper
  ENH: added a unittest for a function which combines two selectors
  WEB: website already goes after mvpa2 - so warning adjusted accordingly
  DOC: various little sphinx-fixing changes in doc(strings)
  DOC: fixing modref to point to mvpa2. not mvpa. (+prune moved from misc)
  ENH: little smoke unittest for regression SL with also additional .sa as input
  Publications update.
  just a usecase from Peter demostrating limitation -- we cannot change # of samples by mapper in MappedClassifier
  BF: while reading .fsf split() fields only twice (thanks Russel for the report and tentative patch)
  Sample FSL's feat specification file (.fsf)
  BF: pylint works in emacs again -- missing import of gzip and use nrows property
  NF: add a .mailmap file
  ENH: use psutil module to provide output for debug vmem metric
  ...
BF(+RF): 2nd wake to fix hdf5 compression-related compatibility issues

RF: just unified variables names a bit to correspond to the ones in
    the HDF5 fields: is_obj_array -> is_objarray
RF: remove svmocas from clfswh for now since it fails to generalize with default settings
RF: make corr_error available unconditionally of scipy