scipy.linalg.
expm_cond#
- 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