Question

are there any numpy function or clever use of views to accomplish what the following function do?

 import numpy as np

 def permuteIndexes(array, perm):
     newarray = np.empty_like(array)
     max_i, max_j = newarray.shape
     for i in xrange(max_i):
         for j in xrange(max_j):
             newarray[i,j] = array[perm[i], perm[j]]
     return newarray

That is, for a given permutation of the indexes of the matrix in a list perm, this function calculates the result of applying this permutation to the indexes of a matrix.

Answer 1

def permutateIndexes(array, perm):
    return array[perm][:, perm]

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Actually, this is better as it does it in a single go:

def permutateIndexes(array, perm):
    return array[np.ix_(perm, perm)]

To work with non-square arrays:

def permutateIndexes(array, perm):
    return array[np.ix_(*(perm[:s] for s in array.shape))]