Multivariate Pattern Analysis in Python

# mvpa2.datasets.miscfx

Miscellaneous functions to perform operations on datasets.

All the functions defined in this module must accept dataset as the first argument since they are bound to Dataset class in the trailer.

Functions

`aggregate_features`(dataset[, fx]) | Apply a function to each row of the samples matrix of a dataset.
`coarsen_chunks`(source[, nchunks]) | Change chunking of the dataset
`get_nsamples_per_attr`(dataset, attr) | Returns the number of samples per unique value of a sample attribute.
`get_samples_by_attr`(dataset, attr, values[, …]) | Return indices of samples given a list of attributes
`get_samples_per_chunk_target`(dataset[, …]) | Returns an array with the number of samples per target in each chunk.
`random_samples`(dataset, npertarget[, …]) | Create a dataset with a random subset of samples.
`remove_invariant_features`(dataset) | Returns a new dataset with all invariant features removed.
`remove_nonfinite_features`(dataset) | Returns a new dataset with all non-finite (NaN,Inf) features removed
`summary`(dataset[, stats, lstats, sstats, …]) | String summary over the object
`summary_targets`(dataset[, targets_attr, …]) | Provide summary statistics over the targets and chunks

Classes

`SequenceStats`(seq[, order]) | Simple helper to provide representation of sequence statistics