mvpa2.algorithms.benchmarks.hyperalignmentΒΆ
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. |
