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###################################################################
# Numexpr - Fast numerical array expression evaluator for NumPy.
#
# License: MIT
# Author: See AUTHORS.txt
#
# See LICENSE.txt and LICENSES/*.txt for details about copyright and
# rights to use.
####################################################################
#######################################################################
# This script compares the speed of the computation of a polynomial
# for different (numpy and numexpr) in-memory paradigms.
#
# Author: Francesc Alted
# Date: 2010-07-06
#######################################################################
from __future__ import print_function
import sys
from time import time
import numpy as np
import numexpr as ne
#expr = ".25*x**3 + .75*x**2 - 1.5*x - 2" # the polynomial to compute
expr = "((.25*x + .75)*x - 1.5)*x - 2" # a computer-friendly polynomial
N = 10*1000*1000 # the number of points to compute expression
x = np.linspace(-1, 1, N) # the x in range [-1, 1]
#what = "numpy" # uses numpy for computations
what = "numexpr" # uses numexpr for computations
def compute():
"""Compute the polynomial."""
if what == "numpy":
y = eval(expr)
else:
y = ne.evaluate(expr)
return len(y)
if __name__ == '__main__':
if len(sys.argv) > 1: # first arg is the package to use
what = sys.argv[1]
if len(sys.argv) > 2: # second arg is the number of threads to use
nthreads = int(sys.argv[2])
if "ncores" in dir(ne):
ne.set_num_threads(nthreads)
if what not in ("numpy", "numexpr"):
print("Unrecognized module:", what)
sys.exit(0)
print("Computing: '%s' using %s with %d points" % (expr, what, N))
t0 = time()
result = compute()
ts = round(time() - t0, 3)
print("*** Time elapsed:", ts)
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