a correct version of weighted rank via sort

gistfile1.py

import random

SAMPLES = 10000
NUM = 5
options = [(k, random.randint(0, 100)) for k in range(NUM)]

choices = list(options)
total_weight = float(sum([k[1] for k in choices]))
vs = []
for i in range(SAMPLES):
    choices.sort(key=lambda i: random.random())
    choices.sort(key=lambda i: [random.random() > (i[1] / total_weight) for k in range(NUM)])

    # if choices[0][0] == 'x':
    vs.append([k[0] for k in choices])

# print vs
print 'target distribution'
for c in options:
    print c[1] / total_weight,

print
print 'test distribution'

for c in options:
    print len([k for k in vs if k[0] == c[0]]) / float(SAMPLES),

print

kk = options[0][0]
sub_total_weight = float(sum([k[1] for k in choices[1:]]))
for c in options[1:]:
    print c[1] / sub_total_weight,
print

for c in options[1:]:
    print len([k for k in vs if k[1] == c[0] and k[0] == kk]) / float(len([k for k in vs if k[0] == kk])),