Difference Between Matlab / Octave Solve and Numpy Solve

Question

I am trying to solve a linear system on Python for a problem which I ported from Octave. I have the following code for Octave

A=[    -1    -2    -4    -2    -3    -4;
       -2    -4    -4    -3    -4    -5;
       -1    -1    -1    -5    -5    -3;
       -2    -3    -5   100    -0    -0;
       -3    -4    -5    -0   100    -0;
       -4    -5    -3    -0    -0   100];

b = [3.9000;
     4.2000;
     4.3000;
     -9.0000;
     -9.0000;
     -9.0000];

A \ b

This gives

ans =

  -3.51998
   1.83663
  -0.66828
  -0.13871
  -0.15555
  -0.15902

On Python I have

import numpy as np
import numpy.linalg as lin

A = [[ -1.,  -2.,  -4.,  -2.,  -3.,  -4.],
     [ -2.,  -3.,  -4.,  -3.,  -4.,  -5.],
     [ -1.,  -1.,  -1.,  -5.,  -5.,  -3.],
     [ -2.,  -3.,  -5., 100.,  -0.,  -0.],
     [ -3.,  -4.,  -5.,  -0., 100.,  -0.],
     [ -4.,  -5.,  -3.,  -0.,  -0., 100.]]

b = [[ 3.9],
     [ 4.2],
     [ 4.3],
     [-9. ],
     [-9. ],
     [-9. ]]

A = np.array(A)
b = np.array(b)

print (lin.solve(A,b))

which gives

[[-7.70634652]
 [ 7.78318125]
 [-2.67111771]
 [-0.14418738]
 [-0.14341903]
 [-0.08922833]]

I am seeing different results.. I wonder why they are different?

Thanks,

Answer 1

The $(2,2)$ entries of $A$ disagree.