Caution

You're reading an old version of this documentation. If you want up-to-date information, please have a look at 0.9.1.

Temporal segmentation

Recurrence and self-similarity

cross_similarity(data, data_ref, *[, k, ...])	Compute cross-similarity from one data sequence to a reference sequence.
recurrence_matrix(data, *[, k, width, ...])	Compute a recurrence matrix from a data matrix.
recurrence_to_lag(rec, *[, pad, axis])	Convert a recurrence matrix into a lag matrix.
lag_to_recurrence(lag, *[, axis])	Convert a lag matrix into a recurrence matrix.
timelag_filter(function[, pad, index])	Filtering in the time-lag domain.
path_enhance(R, n, *[, window, max_ratio, ...])	Multi-angle path enhancement for self- and cross-similarity matrices.

Temporal clustering

agglomerative(data, k, *[, clusterer, axis])	Bottom-up temporal segmentation.
subsegment(data, frames, *[, n_segments, axis])	Sub-divide a segmentation by feature clustering.