Benchmarks for hyperalignment algorithms


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.


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.