Perfomance comparison between np.sum vs np.count_nonzero

sum_vs_count.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import timeit
import sys
import numpy as np

SAMPLE = 10000
REP = 5

a = np.random.randn(SAMPLE, SAMPLE)

def test_sum():
    """ np.sum """
    r = np.sum(a > 0.0)
#    print r

def test_count():
    """ count_nonzero """
    r = np.count_nonzero(a > 0.0)
#    print r

if __name__ == '__main__':
    t = timeit.Timer("test_sum()", "from __main__ import test_sum")
    try:
        print >> sys.stderr, "sum:", t.timeit(REP)
    except:
        t.print_exc()

    t = timeit.Timer("test_count()", "from __main__ import test_count")
    try:
        print >> sys.stderr, "cnt:", t.timeit(REP)
    except:
        t.print_exc()

sum: 2.10800409317
cnt: 3.04244184494

With 20000:

sum: 4.14537286758
cnt: 2.55795407295