Re: NxN random matrix much cheaper than N^2 random scalars

[Daniel Molina García]

Hi Andreas,

Because for loops are slow in octave. 

:( I though that it was due to a delay on the call, not in the "for" design.

It remembered me something what I experienced in fortran: initializing a rng takes a lot of time and if you include the call accidentally inside a loop instead of calling it only once at the begining the program becomes really slow.

> By the way, I found that specifying the 2 dimensions with a vector (as
> in the above example) instead of using two parameters is quicker.

How have you exactly measured this?

Just calling

$ time octave --silent program.m

several times. I don't have a better idea so I couldn't compare.

I found that normrnd is not a matlab function. I suppose the more similar is 'random' with "normal" as parameter, but it seems that "normrnd" is a bit faster. And btw, I found also that "rand" is much faster than "random" with "uniform" as parameter. I'd like to know if "random" has better statistical advantages for a rng, else I would continue using the alternatives. Here are some results I got changing the RNG line in my program:

random, "normal": real 0m12.596s
normrnd: real 0m23.645s
normrnd using [,] : real 0m11.166s !!!!
random, "uniform": real 0m11.136s
rand: real 0m5.184s