En Mon, 27 Aug 2007 17:42:45 -0300, Ivan Voras <[EMAIL PROTECTED]>
escribi�:
> I have a list of items, and need to choose several elements from it,
> "almost random". The catch is that the elements from the beginning
> should have more chance of being selected than those at the end (how
> much more? I don't care how the "envelope" of probability looks like at
> this point - can be linear). I see that there are several functions in
> Python standard libraries for various distribution, but is there an easy
> pythonic way to make them do what I need?
Using a linear (or triangular) distribution:
--- begin ---
from random import randint
def biased_choice(values):
"""Choose a random element from values;
first elements are chosen more frequently than later ones.
Weights are linearly assigned; given n elements, the first
has weight n, second has n-1, ... last has weight 1.
"""
n = len(values)
sumw = ((n + 1) * n) // 2
x = randint(1, sumw)
F = 0
for i in xrange(1, n+1):
F += i
if x<=F: return values[-i]
# test
from collections import defaultdict
values = ["a", "b", "c", "d", "e"]
stats = defaultdict(int)
for i in xrange(150000):
stats[biased_choice(values)] += 1
for key in sorted(stats):
print key, stats[key]
--- end ---
Output:
a 50023
b 39869
c 30256
d 19784
e 10068
--
Gabriel Genellina
--
http://mail.python.org/mailman/listinfo/python-list
