Johan Fredrik Ã˜hman wrote:

The first numbers in each of your three runs are 7.98493051529 , 7.98525762558 and 7.98623776436. They look like different numbers to me.

First, thanks for your answer Time. I do agree, they are different. But I wouldn't call it random. I didn't expect that the small difference in the initial seed would affect the first number with so little. Usually the seed numbers I have experienced other places have much more dramatic effect on the numbers, if you see what I mean...

OK, you need to use Konrad Hinsen's excellent RNG module which comes with Numeric Python: ################################# # Python Virtual clock import RNG dist = RNG.NormalDistribution(10, 2) rng = RNG.CreateGenerator(0, dist) for i in range(1000000,10000000,1000000): print "Clock at time:" , i/1000000, ":", rng.ranf() ################################## The above code gives 8.46183655136, 7.29889782477 and 5.58243682462 as the first values in three successive runs on my system. Hope this helps, Tim C

If you want the difference between initial values to be greater, you need to make the difference in your seeds greater. For example, if I run your code now, I get 8.29225027561, 8.29484963417 and 8.29744851589, but setting the seed to (1,2) gives an initial value of 5.69397783279. Remember, these are only pseudorandom numbers.

Yes, they are pseudorandom and that is OK. What I just want is some more initial difference between the runs without setting the seed number manually. But know I know this is not a flaw in the RNG, but "its the way it is supposed to be"

Thanks

-- Johan Fredrik Ohman

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