scipy.linalg.svdvals

scipy.linalg.svdvals(a, overwrite_a=False)[source]

Compute singular values of a matrix.

Parameters :

a : ndarray

Matrix to decompose, of shape (M, N).

overwrite_a : bool, optional

Whether to overwrite a; may improve performance. Default is False.

Returns :

s : ndarray

The singular values, sorted in decreasing order. Of shape (K,), with``K = min(M, N)``.

Raises :

LinAlgError :

If SVD computation does not converge.

See also

svd
Compute the full singular value decomposition of a matrix.
diagsvd
Construct the Sigma matrix, given the vector s.

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