Muscat.LinAlg.SVD module

CheckIntegrity(GUI: bool = False)[source]
TruncatedSVDSymLower(matrix, epsilon: float64 | None = None, nbModes: int64 | None = None)[source]

Computes a truncated singular value decomposition of a symmetric definite matrix in scipy.sparse.csr format. Only the lower triangular part needs to be defined

Parameters:

  • matrix (scipy.sparse.csr) – the input matrix

  • epsilon (float) – the truncation tolerance, determining the number of keeps eigenvalues

  • nbModes (int) – the number of keeps eigenvalues

Returns:

  • np.ndarray – kept eigenvalues, of size (numberOfEigenvalues)

  • np.ndarray – kept eigenvectors, of size (numberOfEigenvalues, numberOfSnapshots)