曾与蒿藜同雨露，한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.终随松柏到冰霜.かつては雑草やヨモギと共に雨や露を分かち合っていたが、今では松やヒノキと共に霜や雪に耐えている。曾与蒿藜同雨露，Once sharing rain and dew with weeds and wormwood, now enduring frost and snow with pines and cypresses.终随松柏到冰霜.曾与蒿藜同雨露한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.，终随松柏到冰霜.譖ｾ荳手珍阯懷酔髮ｨ髴ｲ�檎ｻ磯囂譚ｾ譟丞芦蜀ｰ髴�曾与蒿藜同雨露，鏇句笌钂胯棞鍚岄洦闇诧紝缁堥殢鏉炬煆鍒板啺闇�终随松柏到冰霜.曾与蒿藜同雨露，한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.终随松柏到冰霜.曾与蒿藜同雨露，终随松柏到冰霜. rahbord-ins.ir - GrazzMean-Shell
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name : bench.py 
from __future__ import division, print_function

import timeit
import numpy


###############################################################################
#                               Global variables                              #
###############################################################################


# Small arrays
xs = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
ys = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
zs = xs + 1j * ys
m1 = [[True, False, False], [False, False, True]]
m2 = [[True, False, True], [False, False, True]]
nmxs = numpy.ma.array(xs, mask=m1)
nmys = numpy.ma.array(ys, mask=m2)
nmzs = numpy.ma.array(zs, mask=m1)

# Big arrays
xl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
yl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
zl = xl + 1j * yl
maskx = xl > 0.8
masky = yl < -0.8
nmxl = numpy.ma.array(xl, mask=maskx)
nmyl = numpy.ma.array(yl, mask=masky)
nmzl = numpy.ma.array(zl, mask=maskx)


###############################################################################
#                                 Functions                                   #
###############################################################################


def timer(s, v='', nloop=500, nrep=3):
    units = ["s", "ms", "µs", "ns"]
    scaling = [1, 1e3, 1e6, 1e9]
    print("%s : %-50s : " % (v, s), end=' ')
    varnames = ["%ss,nm%ss,%sl,nm%sl" % tuple(x*4) for x in 'xyz']
    setup = 'from __main__ import numpy, ma, %s' % ','.join(varnames)
    Timer = timeit.Timer(stmt=s, setup=setup)
    best = min(Timer.repeat(nrep, nloop)) / nloop
    if best > 0.0:
        order = min(-int(numpy.floor(numpy.log10(best)) // 3), 3)
    else:
        order = 3
    print("%d loops, best of %d: %.*g %s per loop" % (nloop, nrep,
                                                      3,
                                                      best * scaling[order],
                                                      units[order]))


def compare_functions_1v(func, nloop=500,
                       xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    funcname = func.__name__
    print("-"*50)
    print("%s on small arrays" % funcname)
    module, data = "numpy.ma", "nmxs"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

    print("%s on large arrays" % funcname)
    module, data = "numpy.ma", "nmxl"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)
    return

def compare_methods(methodname, args, vars='x', nloop=500, test=True,
                    xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
    print("-"*50)
    print("%s on small arrays" % methodname)
    data, ver = "nm%ss" % vars, 'numpy.ma'
    timer("%(data)s.%(methodname)s(%(args)s)" % locals(), v=ver, nloop=nloop)

    print("%s on large arrays" % methodname)
    data, ver = "nm%sl" % vars, 'numpy.ma'
    timer("%(data)s.%(methodname)s(%(args)s)" % locals(), v=ver, nloop=nloop)
    return

def compare_functions_2v(func, nloop=500, test=True,
                       xs=xs, nmxs=nmxs,
                       ys=ys, nmys=nmys,
                       xl=xl, nmxl=nmxl,
                       yl=yl, nmyl=nmyl):
    funcname = func.__name__
    print("-"*50)
    print("%s on small arrays" % funcname)
    module, data = "numpy.ma", "nmxs,nmys"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)

    print("%s on large arrays" % funcname)
    module, data = "numpy.ma", "nmxl,nmyl"
    timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)
    return


if __name__ == '__main__':
    compare_functions_1v(numpy.sin)
    compare_functions_1v(numpy.log)
    compare_functions_1v(numpy.sqrt)

    compare_functions_2v(numpy.multiply)
    compare_functions_2v(numpy.divide)
    compare_functions_2v(numpy.power)

    compare_methods('ravel', '', nloop=1000)
    compare_methods('conjugate', '', 'z', nloop=1000)
    compare_methods('transpose', '', nloop=1000)
    compare_methods('compressed', '', nloop=1000)
    compare_methods('__getitem__', '0', nloop=1000)
    compare_methods('__getitem__', '(0,0)', nloop=1000)
    compare_methods('__getitem__', '[0,-1]', nloop=1000)
    compare_methods('__setitem__', '0, 17', nloop=1000, test=False)
    compare_methods('__setitem__', '(0,0), 17', nloop=1000, test=False)

    print("-"*50)
    print("__setitem__ on small arrays")
    timer('nmxs.__setitem__((-1,0),numpy.ma.masked)', 'numpy.ma   ', nloop=10000)

    print("-"*50)
    print("__setitem__ on large arrays")
    timer('nmxl.__setitem__((-1,0),numpy.ma.masked)', 'numpy.ma   ', nloop=10000)

    print("-"*50)
    print("where on small arrays")
    timer('numpy.ma.where(nmxs>2,nmxs,nmys)', 'numpy.ma   ', nloop=1000)
    print("-"*50)
    print("where on large arrays")
    timer('numpy.ma.where(nmxl>2,nmxl,nmyl)', 'numpy.ma   ', nloop=100)
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