To provide the most recent news and documentation www.pymvpa.org reflects the development 2.0 series (renamed 0.6 series) of PyMVPA. If you are interested in the documentation of the previous stable 0.4 series of PyMVPA, please visit v04.pymvpa.org.

Release Notes – PyMVPA 0.5

For The Impatient

• Datasets are no longer relatively static objects, but become flexible multi-purpose containers that can handle attributes for samples, feature, or whole datasets. There is some inital support for other datatypes than NumPy’s ndarrays, e.g. sparse matrices.

Critical API Changes

• states -> ca (for conditional attributes). All attributes stored in collections (parameters for Classifiers in .params, states in .ca) should be accessed not at top level of the object but through a collection.
• Dataset: behaves more like a NumPy array. No specialized Dataset classes, but constructors
  • MaskedDataset -> dataset_wizard
  • NiftiDataset -> fmri_dataset
  • ERNiftiDataset -> fmri_dataset + eventrelated_dataset (see event-related analysis example)
• MRI volumes: 3,4D volumes (and coordinates) are exposed with following order of axes: t,x,y,z. Previously we followed a convention of t,z,y,x order of axis in volume data (to be consistent with PyNIfTI).
• Masks (mask_mapper)

• now [1,1,0] is not the same as [True, True, False]

• We have weird (but consistent) conventions now - classes are CamelCased - factory functions (even for whatever might have been before a class) are in pythonic_style
• detrend -> poly_detrend
• perchunk=bool (in zscore/detrend) got refactored into chunks_attr=None or string to specify on which sample attribute to operate.
• internally and as provided by mvpa2.suite, numpy is imported as np, and pylab is imported as pl

General Changes

Datasets

Sparse data support

Dataset in principal now support non-ndarray types for dataset samples. However, most parts of PyMVPA still assume an (at least) ndarray-like interface.

Splitters

• permute -> permute_attr, so if you had permute=True, use attr='targets' if you like to permute targets