Vector division by a matrix different results when executed in Octave or Python

[Denis Lessard]

Hy I am trying to convert some of my Octaves programs to Python, but presently I am stoped by a very strange problem.

The results for a vector divided by a matrix on both system do not give me the same results.

Here is a simplified example of the problem:

On Python:

import numpy as np

a=np.array([10,10,10])

b=np.array([[1,1,1],[2,2,2],[3,3,3]])

print(a)

print(b)

c=np.divide(a,b)

print("np.divide(a,b) = ")

print (c)

the results:

a=[10 10 10]

b=[[1 1 1]
    [2 2 2]
    [3 3 3]]

np.divide(a,b) = 
 [[10.         10.         10.        ]
 [ 5.          5.          5.        ]
 [ 3.33333333  3.33333333  3.33333333]]

The results are the same if I used c=a/b

For octave I wrote the same small program (no numpy )

and when I use c=a/b the results are:

0.71429 , 1.42847 , 2.14286

The Octave results are the good one when I compare my program results with the web examples used 

to validate my program.

I did try different approach in Python like transpose etc but notting seems to approach the response given by Octave.

Thanks

Denis