fast_logdet

sklearn.utils.extmath.fast_logdet(A)[source]

Compute logarithm of determinant of a square matrix.

The (natural) logarithm of the determinant of a square matrix is returned if det(A) is non-negative and well defined. If the determinant is zero or negative returns -Inf.

Equivalent to : np.log(np.det(A)) but more robust.

Parameters:

Aarray_like of shape (n, n)

The square matrix.

Returns:

logdetfloat

When det(A) is strictly positive, log(det(A)) is returned. When det(A) is non-positive or not defined, then -inf is returned.

See also

numpy.linalg.slogdet

Compute the sign and (natural) logarithm of the determinant of an array.

Examples

>>> import numpy as np
>>> from sklearn.utils.extmath import fast_logdet
>>> a = np.array([[5, 1], [2, 8]])
>>> fast_logdet(a)
np.float64(3.6375861597263857)