mvpa2.algorithms.benchmarks.hyperalignment

Benchmarks for hyperalignment algorithms

Functions

mean_group_sample(attrs[, attrfx])	Returns a mapper that computes the mean samples of unique sample groups.
timesegments_classification(dss[, hyper, ...])	Time-segment classification across subjects using Hyperalignment
vstack(datasets[, a, fa])	Stacks datasets vertically (appending samples).
wipe_out_offdiag(a, window_size[, value])	Wipe-out (fill with np.inf, as default) close-to-diagonal elements
zscore(ds, \*\*kwargs)	In-place Z-scoring of a Dataset or ndarray.

Classes

BoxcarMapper(startpoints, boxlength[, offset])	Mapper to combine multiple samples into a single sample.
FlattenMapper([shape, maxdims])	Reshaping mapper that flattens multidimensional arrays into 1D vectors.
HalfPartitioner([count, selection_strategy, ...])	Partition a dataset into two halves of the sample attribute.
IdentityMapper(\*\*kwargs)	A mapper that performs an identity transformation (i.e.
NFoldPartitioner([cvtype])	Generic N-fold data partitioner.
Splitter(attr[, attr_values, count, ...])	Generator node for dataset splitting.