How to raise a numpy array to a power? (corresponding to repeated matrix multiplications, not elementwise)

Question

I want to raise a 2-dimensional numpy array, let's call it A, to the power of some number n, but I have thus far failed to find the function or operator to do that.

I'm aware that I could cast it to the matrix type and use the fact that then (similar to what would be the behaviour in Matlab), A**n does just what I want, (for array the same expression means elementwise exponentiation). Casting to matrix and back seems like a rather ugly workaround though.

Surely there must be a good way to perform that calculation while keeping the format to array?

Answer 1

I believe you want numpy.linalg.matrix_power

As a quick example:

import numpy as np x = np.arange(9).reshape(3,3) y = np.matrix(x)  a = y**3 b = np.linalg.matrix_power(x, 3)  print a print b assert np.all(a==b) 

This yields:

In [19]: a Out[19]:  matrix([[ 180,  234,  288],         [ 558,  720,  882],         [ 936, 1206, 1476]])  In [20]: b Out[20]:  array([[ 180,  234,  288],        [ 558,  720,  882],        [ 936, 1206, 1476]])