mvpa2.datasets.baseΒΆ

PyMVPA’s common Dataset container.

Inheritance diagram of mvpa2.datasets.base

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 :Parameters: mask : None or array an array in the original dataspace and its nonzero elements are used to define the features included in the dataset.

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.

NeuroDebian

NITRC-listed