expm_cond — SciPy v1.15.2 Manual (original) (raw)

scipy.linalg.

scipy.linalg.expm_cond(A, check_finite=True)[source]#

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

Parameters:

A2-D array_like

Square input matrix with shape (N, N).

check_finitebool, 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:

kappafloat

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.

Added in version 0.14.0.

Examples

import numpy as np 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