linalg.cond
Description
Compute the condition number of a matrix.
This function is capable of returning the condition number using one of seven different norms, depending on the value of p For details about the norm values, see Table 1.
Mandatory Input Parameters
Parameter |
Type |
Description |
|---|---|---|
x |
(…,M,N) array_like |
A matrix whose condition number is to be sought. |
Optional Input Parameters
Parameter |
Type |
Default Value |
Description |
|---|---|---|---|
p |
{None, 1, -1, 2, -2, inf, -inf, 'fro'} |
None |
Calculates the condition number with norms for matrices. |
Return Value
Type |
Description |
|---|---|
ndarray |
Condition number of the matrix. |
Examples
>>> import numpy as np
>>> a = np.array([[1,0,-1], [0,1,0], [1,0,1]])
>>> a
array([[ 1, 0, -1],
[ 0, 1, 0],
[ 1, 0, 1]])
>>> np.linalg.cond(a)
1.4142135623730951
>>> np.linalg.cond(a, 'fro')
3.1622776601683795
>>> np.linalg.cond(a, np.inf)
2.0
>>> np.linalg.cond(a, -np.inf)
1.0
>>> np.linalg.cond(a, 1)
2.0
>>> np.linalg.cond(a, -1)
1.0
>>> np.linalg.cond(a, 2)
1.4142135623730951
>>> np.linalg.cond(a, -2)
0.7071067811865475
>>> min(np.linalg.svd(a, compute_uv=False))*min(np.linalg.svd(np.linalg.inv(a), compute_uv=False))
0.7071067811865475
>>>
Parent topic: Linear Algebra Functions