Gradient Maps


GradientMaps([n_components, approach, …]) Gradient maps.


Embedding([n_components]) Base class for embedding approaches.
DiffusionMaps([n_components, alpha, …]) Diffusion maps.
LaplacianEigenmaps([n_components, …]) Laplacian eigenmaps.
PCAMaps([n_components, random_state]) Principal component analysis.
diffusion_mapping(adj[, n_components, …]) Compute diffusion map of affinity matrix.
laplacian_eigenmaps(adj[, n_components, …]) Compute embedding using Laplacian eigenmaps.


ProcrustesAlignment([n_iter, tol, verbose]) Iterative alignment using generalized procrustes analysis.
procrustes_alignment(data[, reference, …]) Iterative alignment using generalized procrustes analysis.
procrustes(source, target[, center, scale]) Align source to target using procrustes analysis.


compute_affinity(x[, kernel, sparsity, …]) Compute affinity matrix.

Utility functions

dominant_set(s, k[, is_thresh, norm, copy, …]) Keep largest elements for each row.
is_symmetric(x[, tol]) Check if input is symmetric.
make_symmetric(x[, check, tol, copy, …]) Make array symmetric.