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.

mvpa2.datasets.base

PyMVPA’s common Dataset container.

Functions

idhash_(val)	Craft unique id+hash for an object
mask_mapper([mask, shape, space])	Factory method to create a chain of Flatten+StaticFeatureSelection Mappers

Classes

AttrDataset(samples[, sa, fa, a])	Generic storage class for datasets with multiple attributes.
ChainMapper(nodes, **kwargs)	Class that amends ChainNode with a mapper-like interface.
Dataset(samples[, sa, fa, a])	Generic storage class for datasets with multiple attributes.
DatasetAttribute([value, name, doc, length])	Dataset attribute
DatasetAttributesCollection([items])	Container for attributes of datasets (i.e.
FeatureAttribute([value, name, doc, length])	Per feature attribute in a dataset
FeatureAttributesCollection([items, length])	Container for attributes of features
FlattenMapper([shape, maxdims])	Reshaping mapper that flattens multidimensional arrays into 1D vectors.
HollowSamples([shape, sid, fid, dtype])	Samples container that doesn’t store samples.
SampleAttribute([value, name, doc, length])	Per sample attribute in a dataset
SampleAttributesCollection([items, length])	Container for attributes of samples (i.e.
StaticFeatureSelection(slicearg[, dshape, ...])	Feature selection by static slicing argument.