[SciPy-user] random number
elcorto at gmx.net
Tue Jun 29 15:53:57 CDT 2004
> Steve Schmerler wrote:
> >>You're right. Wasn't seed changing but truly out of bound call.
> >>Why do you need to generate uniform variate (0,1e38) ?
> >>Curious about applications !
> >I'm testing an evolution strategy (similar to a genetic algorithm) for
> >parameter fitting. I need to construct parameter vectors
> > p = [p, ..., p[n]]
> >where each p[i] sould be a random number from 0 to 1e200.
> >I found that the module 'random' works with the 1e39-thing.
> > >>> from random import *
> > >>> uniform(0,1e39)
> > 2.3437216521520377e+038
> > >>> uniform(0,1e200)
> > 2.7167859425411156e+199
> >But there is another downside here.
> > >>> x=[uniform(0,1e200) for i in range(1000)]
> >gives nearly 1000 rn's like
> > 2.3107981948610023e+199
> >All rn's have an order of magnitude of 1e199, but I want also things like
> > 1e23, 1e45, 1e2, ....
> >Any idea how to do this??? (google should do it :) )
> >It seems as if 'uniform(min, max)' is implemented as
> > random()*max
> >where 'random()' is a random float out of [0,1).
> I was going to suggest random()*1e39, but it seems that that is not
> really what you want.
Yes. The problem is that the minimal random numbers are mostly only 1e1
smaller (1e199) than the max value (1e200 in my case).
> A uniformly distributed collection of numbers between (0, 1e38) is going
> to have very few members between (0, 1e3). Or (0, 1e24). Or (0,
> 1e35). Only 1 in 10 will be in the range (0, 1e37). It sounds like
> you may be looking for logarithmically distributed numbers.
> How about 10**x where x is a random number in (0, 38).
Yeah, I tried something similar:
from Numeric import *
def alloverRand(min, max):
# e.g. max = x*10**y = exp(max_exponent)
max_exponent = log(max)
This gives log-like distribution. Though it's not uniformly I'll test if it
works since it covers _all_ numbers from (nearly 0) to 'max'.
> Caveat: I'm no expert in random numbers. I'm just following my nose,
me neither, so do I :)
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