mvpa2.algorithms.hyperalignmentΒΆ

Transformation of individual feature spaces into a common space

The Hyperalignment class in this module implements an algorithm published in Haxby et al., Neuron (2011) A common, high-dimensional model of the representational space in human ventral temporal cortex.

Inheritance diagram of mvpa2.algorithms.hyperalignment

Functions

deepcopy(x[, memo, _nil]) Deep copy operation on arbitrary Python objects.
zscore(ds, **kwargs) In-place Z-scoring of a Dataset or ndarray.

Classes

ChainMapper(nodes, **kwargs) Class that amends ChainNode with a mapper-like interface.
ClassWithCollections([descr]) Base class for objects which contain any known collection
ConditionalAttribute([enabled]) Simple container intended to conditionally store the value ..
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
Hyperalignment(**kwargs) Align the features across multiple datasets into a common feature space.
Parameter(default[, ro, index, value, name, doc]) This class shall serve as a representation of a parameter.
ProcrusteanMapper([space]) Mapper to project from one space to another using Procrustean
StaticProjectionMapper(proj, **kwargs) Mapper to project data onto arbitrary space using transformation given as input.
ZScoreMapper([params, param_est, ...]) Mapper to normalize features (Z-scoring).

NeuroDebian

NITRC-listed