API Documentation

Transformers

BatchCDL(n_atoms, n_times_atom[, reg, ...])	Batch algorithm for convolutional dictionary learning
GreedyCDL(n_atoms, n_times_atom[, reg, ...])	Greedy batch algorithm for convolutional dictionary learning
OnlineCDL(n_atoms, n_times_atom[, reg, ...])	Base class for convolutional dictionary learning algorithms.

Functions

Functions to learn atoms (d) and activations (z) from the signal

learn_d_z(X, n_atoms, n_times_atom[, ...])	Univariate Convolutional Sparse Coding.
learn_d_z_weighted(X, n_atoms, n_times_atom)	Univariate Convolutional Sparse Coding with an alpha-stable distribution

Utility functions (alphacsc.utils):

check_univariate_signal(X)	Return an array that can be used with alphacsc transformers for univariate signals.
check_multivariate_signal(X)	Return an array that can be used with alphacsc transformers for multivariate signals.
split_signal(X[, n_splits, apply_window])	Split the signal in n_splits chunks for faster training.

previous

SWM on simulated data

next

alphacsc.BatchCDL