#!/usr/bin/env python3
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import timeit
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import numpy
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###############################################################################
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# Global variables #
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###############################################################################
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# Small arrays
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xs = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
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ys = numpy.random.uniform(-1, 1, 6).reshape(2, 3)
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zs = xs + 1j * ys
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m1 = [[True, False, False], [False, False, True]]
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m2 = [[True, False, True], [False, False, True]]
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nmxs = numpy.ma.array(xs, mask=m1)
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nmys = numpy.ma.array(ys, mask=m2)
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nmzs = numpy.ma.array(zs, mask=m1)
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# Big arrays
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xl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
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yl = numpy.random.uniform(-1, 1, 100*100).reshape(100, 100)
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zl = xl + 1j * yl
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maskx = xl > 0.8
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masky = yl < -0.8
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nmxl = numpy.ma.array(xl, mask=maskx)
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nmyl = numpy.ma.array(yl, mask=masky)
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nmzl = numpy.ma.array(zl, mask=maskx)
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###############################################################################
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# Functions #
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###############################################################################
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def timer(s, v='', nloop=500, nrep=3):
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units = ["s", "ms", "µs", "ns"]
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scaling = [1, 1e3, 1e6, 1e9]
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print("%s : %-50s : " % (v, s), end=' ')
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varnames = ["%ss,nm%ss,%sl,nm%sl" % tuple(x*4) for x in 'xyz']
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setup = 'from __main__ import numpy, ma, %s' % ','.join(varnames)
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Timer = timeit.Timer(stmt=s, setup=setup)
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best = min(Timer.repeat(nrep, nloop)) / nloop
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if best > 0.0:
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order = min(-int(numpy.floor(numpy.log10(best)) // 3), 3)
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else:
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order = 3
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print("%d loops, best of %d: %.*g %s per loop" % (nloop, nrep,
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3,
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best * scaling[order],
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units[order]))
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def compare_functions_1v(func, nloop=500,
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xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
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funcname = func.__name__
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print("-"*50)
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print(f'{funcname} on small arrays')
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module, data = "numpy.ma", "nmxs"
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timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)
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print("%s on large arrays" % funcname)
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module, data = "numpy.ma", "nmxl"
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timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)
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return
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def compare_methods(methodname, args, vars='x', nloop=500, test=True,
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xs=xs, nmxs=nmxs, xl=xl, nmxl=nmxl):
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print("-"*50)
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print(f'{methodname} on small arrays')
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data, ver = f'nm{vars}l', 'numpy.ma'
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timer("%(data)s.%(methodname)s(%(args)s)" % locals(), v=ver, nloop=nloop)
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print("%s on large arrays" % methodname)
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data, ver = "nm%sl" % vars, 'numpy.ma'
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timer("%(data)s.%(methodname)s(%(args)s)" % locals(), v=ver, nloop=nloop)
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return
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def compare_functions_2v(func, nloop=500, test=True,
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xs=xs, nmxs=nmxs,
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ys=ys, nmys=nmys,
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xl=xl, nmxl=nmxl,
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yl=yl, nmyl=nmyl):
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funcname = func.__name__
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print("-"*50)
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print(f'{funcname} on small arrays')
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module, data = "numpy.ma", "nmxs,nmys"
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timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)
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print(f'{funcname} on large arrays')
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module, data = "numpy.ma", "nmxl,nmyl"
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timer("%(module)s.%(funcname)s(%(data)s)" % locals(), v="%11s" % module, nloop=nloop)
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return
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if __name__ == '__main__':
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compare_functions_1v(numpy.sin)
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compare_functions_1v(numpy.log)
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compare_functions_1v(numpy.sqrt)
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compare_functions_2v(numpy.multiply)
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compare_functions_2v(numpy.divide)
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compare_functions_2v(numpy.power)
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compare_methods('ravel', '', nloop=1000)
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compare_methods('conjugate', '', 'z', nloop=1000)
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compare_methods('transpose', '', nloop=1000)
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compare_methods('compressed', '', nloop=1000)
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compare_methods('__getitem__', '0', nloop=1000)
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compare_methods('__getitem__', '(0,0)', nloop=1000)
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compare_methods('__getitem__', '[0,-1]', nloop=1000)
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compare_methods('__setitem__', '0, 17', nloop=1000, test=False)
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compare_methods('__setitem__', '(0,0), 17', nloop=1000, test=False)
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print("-"*50)
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print("__setitem__ on small arrays")
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timer('nmxs.__setitem__((-1,0),numpy.ma.masked)', 'numpy.ma ', nloop=10000)
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print("-"*50)
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print("__setitem__ on large arrays")
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timer('nmxl.__setitem__((-1,0),numpy.ma.masked)', 'numpy.ma ', nloop=10000)
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print("-"*50)
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print("where on small arrays")
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timer('numpy.ma.where(nmxs>2,nmxs,nmys)', 'numpy.ma ', nloop=1000)
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print("-"*50)
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print("where on large arrays")
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timer('numpy.ma.where(nmxl>2,nmxl,nmyl)', 'numpy.ma ', nloop=100)
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