Question

I am generating data in R and Matlab for 2 separate analyses and I want to determine if the results in the two systems are equivalent. Between the 2 sets of code there is inherent variability due to the random number generator. If possible, I would like to remove this source of variability. Does anyone know of a way to set the same starting seed in both Matlab and R? I provide some demo code below.

%Matlab code
seed=rng %save seed
matlabtime1=randn(1,5) %generate 5 random numbers from standard normal 
rng(seed) %get saved seed
matlabtime2=randn(1,5) %generates same output as matlabtime1

#R code
set.seed(3) #save seed
r.time1=rnorm(5) #generate 5 random numbers from standard normal 
set.seed(3) #get saved seed
r.time2=rnorm(5) #generates same output as r.time1

Essentially, I want the results from matlabtime2 and r.time2 to match exactly. (The code I am using is more complex than this illustrative demo so rewriting in one language only is not really a feasible option.)

Answer 1

I’m finding it difficult to get the same random numbers in R and
MATLAB – even using the same seed for the same algorithm (Mersenne
Twister).

I guess it’s about how they are implemented – even with the same seed, they have different initial states (you can print and inspect the states both in R and MATLAB).

In the past when I’ve needed this, I generated random input, saved it as a file on disk, and fed it to both MATLAB and R.

Another option is to write C wrappers for a random number generator (there are many of these in C/C++) both for R and MATLAB and invoke those instead of the built-in ones.