Decomposition¶

The documentation of the decomposition module.

The pyts.decomposition module includes decomposition algorithms.

class pyts.decomposition.SSA(window_size, grouping=None)[source]¶

Singular Spectrum Analysis.

Parameters:	window_size : int The size of the sliding window. grouping : None, int or array-like (default = None) The way the elementary matrices are grouped. If None, no grouping is performed. If an integer, the number of groups is equal to this integer. If array-like, each element must be a array-like containing the indices for each group.

Methods

`fit`([X, y])	Pass.
`fit_transform`(X[, y])	Fit to data, then transform it.
`get_params`([deep])	Get parameters for this estimator.
`set_params`(**params)	Set the parameters of this estimator.
`transform`(X)	Transform the provided data.

fit(X=None, y=None)[source]¶

Pass.

Parameters:	X ignored y Ignored

transform(X)[source]¶

Transform the provided data.

Parameters:	X : array-like, shape = [n_samples, n_features]
Returns:	X_new : array-like, shape = [n_samples, n_splits, n_features] Transformed data. `n_splits` value depends on the value of `grouping`. If `grouping=None`, `n_splits` is equal to `window_size`. If `grouping` is an integer, `n_splits` is equal to `grouping`. If `grouping` is array-like, `n_splits` is equal to the length of `grouping`.