RosettaCodeData/Task/Monte-Carlo-methods/Python/monte-carlo-methods-1.py

17 lines
566 B
Python

>>> import random, math
>>> throws = 1000
>>> 4.0 * sum(math.hypot(*[random.random()*2-1
for q in [0,1]]) < 1
for p in xrange(throws)) / float(throws)
3.1520000000000001
>>> throws = 1000000
>>> 4.0 * sum(math.hypot(*[random.random()*2-1
for q in [0,1]]) < 1
for p in xrange(throws)) / float(throws)
3.1396359999999999
>>> throws = 100000000
>>> 4.0 * sum(math.hypot(*[random.random()*2-1
for q in [0,1]]) < 1
for p in xrange(throws)) / float(throws)
3.1415666400000002