pyssaBSS.spssa

Functions

SPSSA_COMB(data, coords, partition[, ...])

SPSSA_LCOR(data, coords, partition[, ...])

SPSSA_SAVE(data, coords, partition[, s, r])

SPSSA_SIR(data, coords, partition[, s, r])

Classes

SPSSA(data, coords, partition, scatter[, ...])

Spatial Stationary Subspace Analysis (SPSSA)
class pyssaBSS.spssa.SPSSA(data, coords, partition, scatter, dim_estimator=None)[source]

Bases: SSA

Spatial Stationary Subspace Analysis (SPSSA)

Examples

Initialize the model:

model = SPSSA(data, coords, scatter=scatter, partition=partition)

Optionally estimate the rank of the nonstationary subspace:

q = model.estimate_rank()

Extract stationary and nonstationary subspaces:

ss, ns = model.subspaces(q)
Parameters:

  • data (ndarray of shape (n_signals, n_samples)) – Observed data matrix. Decomposition is performed immediately on construction.

  • coords (ndarray, optional) – Spatial coordinates passed to the segmentation function. Required when no pre-computed partition are provided.

  • partition (ndarray, optional) – Pre-computed segment labels.

  • scatter (dict, list, or scatter object) – Scatter matrices or operators for subspace analysis.

  • dim_estimator (AugmentationRankEstimator, optional) – An object to compute an estimate of the nonstationary dimension. Currently only support one kind of estimator but could be easily extended to include different estimators.

whitener_

Whitening matrix from data standardization.

Type:

ndarray

diagonalizer_

Matrix that diagonalizes the scatter matrices.

Type:

ndarray

eigenvalues_

Eigenvalues from the diagonalization.

Type:

ndarray

individual_models_

Decomposed models for individual scatters.

Type:

dict[str, SPSSA]

estimated_rank_

Rank estimated by estimate_rank(), if called.

Type:

int or None

pyssaBSS.spssa.SPSSA_COMB(data, coords, partition, kernel=None, s=10, r=10, **kwargs)[source]
Return type:

SPSSA

pyssaBSS.spssa.SPSSA_LCOR(data, coords, partition, kernel=None, s=10, r=10, **kwargs)[source]
Return type:

SPSSA

pyssaBSS.spssa.SPSSA_SAVE(data, coords, partition, s=10, r=10, **kwargs)[source]
Return type:

SPSSA

pyssaBSS.spssa.SPSSA_SIR(data, coords, partition, s=10, r=10, **kwargs)[source]
Return type:

SPSSA