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@edoakes
Last active February 8, 2020 02:32
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import math
import random
import time
def sample(num_samples):
num_inside = 0
for _ in range(num_samples):
x, y = random.uniform(-1, 1), random.uniform(-1, 1)
if math.hypot(x, y) <= 1:
num_inside += 1
return num_inside
def approximate_pi_distributed(num_samples):
from ray.util.multiprocessing.pool import Pool # NOTE: Only the import statement is changed.
pool = Pool()
start = time.time()
num_inside = 0
sample_batch_size = 100000
for result in pool.map(sample, [sample_batch_size for _ in range(num_samples//sample_batch_size)]):
num_inside += result
print("pi ~= {}".format((4*num_inside)/num_samples))
print("Finished in: {:.2f}s".format(time.time()-start))
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