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# References:
#
# http://software.intel.com/en-us/intel-mkl
# https://github.com/pydata/numexpr/wiki/NumexprMKL
from __future__ import print_function
import datetime
import sys
import numpy as np
import numexpr as ne
from time import time
N = int(5e7)
x = np.linspace(0, 1, N)
y = np.linspace(0, 1, N)
z = np.empty(N, dtype=np.float64)
# Our working set is 3 vectors of N doubles each
working_set_GB = 3 * N * 8 / 2**30
print("NumPy version: %s" % (np.__version__,))
t0 = time()
z = 2*y + 4*x
t1 = time()
gbs = working_set_GB / (t1-t0)
print("Time for an algebraic expression: %.3f s / %.3f GB/s" % (t1-t0, gbs))
t0 = time()
z = np.sin(x)**2 + np.cos(y)**2
t1 = time()
gbs = working_set_GB / (t1-t0)
print("Time for a transcendental expression: %.3f s / %.3f GB/s" % (t1-t0, gbs))
print("Numexpr version: %s. Using MKL: %s" % (ne.__version__, ne.use_vml))
t0 = time()
ne.evaluate('2*y + 4*x', out = z)
t1 = time()
gbs = working_set_GB / (t1-t0)
print("Time for an algebraic expression: %.3f s / %.3f GB/s" % (t1-t0, gbs))
t0 = time()
ne.evaluate('sin(x)**2 + cos(y)**2', out = z)
t1 = time()
gbs = working_set_GB / (t1-t0)
print("Time for a transcendental expression: %.3f s / %.3f GB/s" % (t1-t0, gbs))