API Reference#

In this section, you will find detailed documentation of all the functions, classes, and methods available in our API.

Whether you are a developer who is new to our API or an experienced user looking for more advanced features, we hope you find this documentation helpful. If you have any questions or feedback, please don’t hesitate to reach out to us.



AA([n_archetypes, n_init, max_iter, tol, ...])

Archetype Analysis estimator.

BiAA([n_archetypes, n_init, max_iter, tol, ...])

Bi-Archetype Analysis estimator.


AA(k, m, n[, device])

Archetype analysis implemented in PyTorch.

BiAA(k, m, n[, device])

Biarchetype analysis implemented in PyTorch.

NAA(n_archetypes, shape[, relations, ...])

N-Archetype analysis implemented in PyTorch.


simplex(points[, origin, show_points, ...])

A simplex plot of points with multiple optional parameters to obtain a customized visualization.

bisimplex(alphas, archetypes[, ax])

A plot of archetypes with its corresponding alphas in simplex coordinates.

heatmap(data[, labels, n_archetypes, scores, ax])

Plot a heatmap of the data.


make_archetypal_dataset(archetypes, shape[, ...])

Generate a dataset from archetypes.

permute_dataset(data[, perms])

Permute a dataset along each dimension.

shuffle_dataset(data[, generator])

Shuffle a dataset along each dimension.

sort_by_archetype_similarity(data, alphas, ...)

Sort a dataset using the archetypal spaces previously computed.

sort_by_labels(data, labels)

Sort a dataset using the labels.



Check if generator is an int, a Generator or None and return a Generator.