bundles / scipy latest / scipy / linalg / _expm_frechet / expm_cond
function
scipy.linalg._expm_frechet:expm_cond
Signature
def expm_cond ( A , check_finite = True ) Summary
Relative condition number of the matrix exponential in the Frobenius norm.
Extended Summary
The documentation is written assuming array arguments are of specified "core" shapes. However, array argument(s) of this function may have additional "batch" dimensions prepended to the core shape. In this case, the array is treated as a batch of lower-dimensional slices; see linalg_batch for details. Note that calls with zero-size batches are unsupported and will raise a ValueError.
Parameters
A: 2-D array_likeSquare input matrix with shape (N, N).
check_finite: bool, optionalWhether 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: floatThe relative condition number of the matrix exponential in the Frobenius norm
Notes
A faster estimate for the condition number in the 1-norm has been published but is not yet implemented in SciPy.
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
✗See also
- expm
Compute the exponential of a matrix.
- expm_frechet
Compute the Frechet derivative of the matrix exponential.
Aliases
-
scipy.linalg.expm_cond