[yom]

Quote:

Originally Posted by Tannz0rz In this case, speed honestly shouldn't be a reason as to why you wouldn't want to use this. The randoms with Mersenne are, pardon my lack of words, more "random", while the pawn-generated version is a tad bit sad.

The real question is, is it REALLY worth using this plugin? I'm sorry if you take my posts as offensive, cyber_punk, but i like discussing this sort of things and i like testing/comparing things, and also giving proofs, not just saying. We are here to progress isn't it?

I did a small code to compare probabilities of each functions:

pawn Code:

#define TESTS  20  //How many times to reproduce the test
#define CALLS  3  //How many function calls
#define MAX   3  //Numbers from 0 to MAX (not included)

//Obviously..
#if CALLS < MAX
  #undef CALLS
  #define CALLS MAX
#endif

pawn Code:

new a[MAX][2], i, j;

public OnFilterScriptInit()
{
  for (i = 0; i < TESTS; i++)
  {
    for (j = 0; j < CALLS; j++)
    {
      a[ random(MAX)  ][0]++;
      a[ MRandom(MAX-1) ][1]++;
    }
    for (j = 0; j < MAX; j++)
    {
      printf("Probability of %4d -> random: %3.2f%% - MRandom: %3.2f%%",j, (a[j][0]/CALLS.0)*100,(a[j][1]/CALLS.0)*100);
      a[j][0] = 0;
      a[j][1] = 0;
    }
    print(" ");
  }
}

This gives those results:

Code:

Probability of  0 -> random: 33.33% - MRandom: 33.33%
Probability of  1 -> random:  0.00% - MRandom: 33.33%
Probability of  2 -> random: 66.66% - MRandom: 33.33%

Probability of  0 -> random:  0.00% - MRandom: 66.66%
Probability of  1 -> random: 100.00% - MRandom:  0.00%
Probability of  2 -> random:  0.00% - MRandom: 33.33%

Probability of  0 -> random: 100.00% - MRandom: 33.33%
Probability of  1 -> random:  0.00% - MRandom: 33.33%
Probability of  2 -> random:  0.00% - MRandom: 33.33%

Probability of  0 -> random: 33.33% - MRandom: 33.33%
Probability of  1 -> random: 33.33% - MRandom: 66.66%
Probability of  2 -> random: 33.33% - MRandom:  0.00%

Probability of  0 -> random: 33.33% - MRandom: 66.66%
Probability of  1 -> random:  0.00% - MRandom: 33.33%
Probability of  2 -> random: 66.66% - MRandom:  0.00%

Probability of  0 -> random:  0.00% - MRandom: 66.66%
Probability of  1 -> random: 33.33% - MRandom:  0.00%
Probability of  2 -> random: 66.66% - MRandom: 33.33%

Probability of  0 -> random: 66.66% - MRandom: 66.66%
Probability of  1 -> random:  0.00% - MRandom:  0.00%
Probability of  2 -> random: 33.33% - MRandom: 33.33%

Probability of  0 -> random:  0.00% - MRandom: 33.33%
Probability of  1 -> random: 33.33% - MRandom:  0.00%
Probability of  2 -> random: 66.66% - MRandom: 66.66%

Probability of  0 -> random: 33.33% - MRandom: 33.33%
Probability of  1 -> random: 33.33% - MRandom:  0.00%
Probability of  2 -> random: 33.33% - MRandom: 66.66%

Probability of  0 -> random:  0.00% - MRandom: 66.66%
Probability of  1 -> random: 66.66% - MRandom: 33.33%
Probability of  2 -> random: 33.33% - MRandom:  0.00%

Probability of  0 -> random:  0.00% - MRandom: 100.00%
Probability of  1 -> random: 66.66% - MRandom:  0.00%
Probability of  2 -> random: 33.33% - MRandom:  0.00%

Probability of  0 -> random: 66.66% - MRandom: 33.33%
Probability of  1 -> random:  0.00% - MRandom:  0.00%
Probability of  2 -> random: 33.33% - MRandom: 66.66%

Probability of  0 -> random: 33.33% - MRandom:  0.00%
Probability of  1 -> random: 33.33% - MRandom: 33.33%
Probability of  2 -> random: 33.33% - MRandom: 66.66%

Probability of  0 -> random: 66.66% - MRandom:  0.00%
Probability of  1 -> random: 33.33% - MRandom: 100.00%
Probability of  2 -> random:  0.00% - MRandom:  0.00%

Probability of  0 -> random: 33.33% - MRandom:  0.00%
Probability of  1 -> random: 33.33% - MRandom: 33.33%
Probability of  2 -> random: 33.33% - MRandom: 66.66%

Probability of  0 -> random: 100.00% - MRandom: 33.33%
Probability of  1 -> random:  0.00% - MRandom: 66.66%
Probability of  2 -> random:  0.00% - MRandom:  0.00%

Probability of  0 -> random: 66.66% - MRandom:  0.00%
Probability of  1 -> random:  0.00% - MRandom:  0.00%
Probability of  2 -> random: 33.33% - MRandom: 100.00%

Probability of  0 -> random: 33.33% - MRandom: 33.33%
Probability of  1 -> random: 33.33% - MRandom: 33.33%
Probability of  2 -> random: 33.33% - MRandom: 33.33%

Probability of  0 -> random: 66.66% - MRandom: 33.33%
Probability of  1 -> random:  0.00% - MRandom: 33.33%
Probability of  2 -> random: 33.33% - MRandom: 33.33%

Probability of  0 -> random:  0.00% - MRandom: 33.33%
Probability of  1 -> random: 66.66% - MRandom:  0.00%
Probability of  2 -> random: 33.33% - MRandom: 66.66%

As you can see, even for a random number between 0, 1, and 2, the random() function (which suck for small values, i agree) give pretty similar results compared to MRandom(). A perfect random generator should always give 33% for each of these tests, but i guess it's impossible. You could try increase MAX and see what happen: results are more and more similar as MAX is increased.

I agree that this MRandom() give sometimes more randomized numbers than random(), at least for small values, but for me it's really not worth using it.