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expm_cond(A, check_finite=True)

Notes

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

versionadded

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

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.

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
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.linalg._expm_frechet.expm_cond scipy.linalg._expm_frechet.expm_frechet_kronform

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GitHub : /scipy/linalg/_expm_frechet.py#353
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