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scikit-learn 1.3.2
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# `sklearn.utils.extmath`.fast_logdet

sklearn.utils.extmath.fast_logdet(A)

  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:
    A array_like of shape (n, n)

      The square matrix.

  Returns:
    logdet float

      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)
      3.6375861597263857