Matrix multiplication resulting in different values in MATLAB and NUMPY(?) [duplicate]

Question

This question already has an answer here:

• Matrix multiplication problems - Numpy vs Matlab? 2 answers

Here's the matrix

>> x = [2 7 5 9 2; 8 3 1 6 10; 4 7 3 10 1; 6 7 10 1 8;2 8 2 5 9]

Matlab gives me

>> mtimes(x',x)
ans =

   124   124    94   122   154
   124   220   145   198   179
    94   145   139   101   121
   122   198   101   243   141
   154   179   121   141   250

However, the same operation(on same data) in python(numpy) produces different result. I'm unable to understand why?

import numpy as np
a = [[2, 7, 5, 9, 2],[8,3,1,6,10],[4,7,3,10,1],[6,7,10,1,8],[2,8,2,5,9]]
x = np.array(a)
print 'A : ',type(x),'\n',x,'\n\n'
# print np.transpose(A)
X = np.multiply(np.transpose(x),x)
print "A'*A",type(X),'\n',X

produces

A :  <type 'numpy.ndarray'> 
[[ 2  7  5  9  2]
 [ 8  3  1  6 10]
 [ 4  7  3 10  1]
 [ 6  7 10  1  8]
 [ 2  8  2  5  9]] 


A'*A <type 'numpy.ndarray'> 
[[  4  56  20  54   4]
 [ 56   9   7  42  80]
 [ 20   7   9 100   2]
 [ 54  42 100   1  40]
 [  4  80   2  40  81]]

Answer 1

Numpy documentation states that the operator you apply performs element-wise multiplication.

However, mtimes in MATLAB does matrix multiplication.

To verify, MATLAB syntax for element-wise multiplication produces the same result you see in numpy:

disp(x.'.*x)

     4    56    20    54     4
    56     9     7    42    80
    20     7     9   100     2
    54    42   100     1    40
     4    80     2    40    81