# scipy.linalg.expm_cond

scipy.linalg.expm_cond(A, check_finite=True)

  Relative condition number of the matrix exponential in the Frobenius norm.

  Parameters
    A 2-D array_like

      Square input matrix with shape (N, N).

    check_finite bool, optional

      Whether to check that the input matrix contains only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.

  Returns
    kappa float

      The relative condition number of the matrix exponential in the Frobenius norm

  See also

  `expm`

    Compute the exponential of a matrix.

  `expm_frechet`

    Compute the Frechet derivative of the matrix exponential.

  Notes

  A faster estimate for the condition number in the 1-norm has been published but is not yet implemented in SciPy.

  New in version 0.14.0.

  Examples

      >>> from scipy.linalg import expm_cond
      >>> A = np.array([[-0.3, 0.2, 0.6], [0.6, 0.3, -0.1], [-0.7, 1.2, 0.9]])
      >>> k = expm_cond(A)
      >>> k
      1.7787805864469866

scipy.linalg.expm_frechet scipy.linalg.fractional_matrix_power