#!/usr/bin/python

#######################################################

# Copyright (c) 2015, ArrayFire

# All rights reserved.

#

# This file is distributed under 3-clause BSD license.

# The complete license agreement can be obtained at:

# http://arrayfire.com/licenses/BSD-3-Clause

########################################################

from random import random

from time import time

import arrayfire as af

import sys

try:

import numpy as np

except:

np = None

#alias range / xrange because xrange is faster than range in python2

try:

frange = xrange #Python2

except NameError:

frange = range #Python3

# Having the function outside is faster than the lambda inside

def in_circle(x, y):

return (x*x + y*y) < 1

def calc_pi_device(samples):

x = af.randu(samples)

y = af.randu(samples)

return 4 * af.sum(in_circle(x, y)) / samples

def calc_pi_numpy(samples):

np.random.seed(1)

x = np.random.rand(samples).astype(np.float32)

y = np.random.rand(samples).astype(np.float32)

return 4. * np.sum(in_circle(x, y)) / samples

def calc_pi_host(samples):

count = sum(1 for k in frange(samples) if in_circle(random(), random()))

return 4 * float(count) / samples

def bench(calc_pi, samples=1000000, iters=25):

func_name = calc_pi.__name__[8:]

print("Monte carlo estimate of pi on %s with %d million samples: %f" % \

(func_name, samples/1e6, calc_pi(samples)))

start = time()

for k in frange(iters):

calc_pi(samples)

end = time()

print("Average time taken: %f ms" % (1000 * (end - start) / iters))

if __name__ == "__main__":

if (len(sys.argv) > 1):

af.set_device(int(sys.argv[1]))

af.info()

bench(calc_pi_device)

if np:

bench(calc_pi_numpy)

bench(calc_pi_host)