Eigen decomposition of two square matrix in python

Question

In matlab we have option to find eigen decomposition of two matrix, no matter there product is symmetric or non symmetric such as

A = [1 3; 4 9];
B = [4 7; 9 16];
[Vec,Val]=eig(A,B)

Vectors are

`[-1,-1;0.54,0.85]`

and value are

[-3.79,0;0,0.79]

I have checked in python numpy.linalg but there is no such option. All of the eig variation accept only one parameters. Is there way to deal with this in python

Possible duplicate of [Matlab VS Python - eig(A,B) VS sc.linalg.eig(A,B)](https://stackoverflow.com/questions/11691981/matlab-vs-python-eiga-b-vs-sc-linalg-eiga-b) — dallonsi, Jun 06 '19 at 09:21

jamesoh · Accepted Answer · 2019-06-06T09:26:58.730

1

You can use scipy.linalg.eig:

from scipy import linalg
linalg.eig(A, B)

where A = [[1,3],[4,9]] and B = [[4,7], [9,16]] are your two matrices.

edited Jun 06 '19 at 09:26

answered Jun 06 '19 at 09:19

jamesoh

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Eigen decomposition of two square matrix in python

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