Is it possible to reproduce randn() of MATLAB with NumPy?

Question

I wonder if it is possible to exactly reproduce the whole sequence of randn() of MATLAB with NumPy. I coded my own routine with Python/Numpy, and it is giving me a little bit di

Answer 1

The user asked if it was possible to reproduce the output of randn() of Matlab, not rand. I have not been able to set the algorithm or seed to reproduce the exact number for randn(), but the solution below works for me.

In Matlab: Generate your normal distributed random numbers as follows:

rng(1);
norminv(rand(1,5),0,1)
ans = 
   -0.2095    0.5838   -3.6849   -0.5177   -1.0504

In Python: Generate your normal distributed random numbers as follows:

import numpy as np
from scipy.stats import norm
np.random.seed(1)
norm.ppf(np.random.rand(1,5))
array([[-0.2095,  0.5838, -3.6849, -0.5177,-1.0504]])

It is quite convenient to have functions, which can reproduce equal random numbers, when moving from Matlab to Python or vice versa.