One minor thing is you should use xrange rather than range. Although it will probably only make a difference for the empty loop ;)
Otherwise, from what I can see, tests where numpy is really much worse are: - 1, 2, 3, 15, 18: Not numpy but Python related: for loops are not efficient - 6, 10: Maybe numpy.roll is indeed not efficiently implemented - 21: Same for this scipy function -=- Olivier 2011/9/26 Keith Hughitt <keith.hugh...@gmail.com> > Hi all, > > Myself and several colleagues have recently started work on a Python > library for solar physics <http://www.sunpy.org/>, in order to provide an > alternative to the current mainstay for solar > physics<http://www.lmsal.com/solarsoft/>, > which is written in IDL. > > One of the first steps we have taken is to create a Python > port<https://github.com/sunpy/sunpy/blob/master/benchmarks/time_test3.py>of a > popular benchmark for IDL (time_test3) which measures performance for a > variety of (primarily matrix) operations. In our initial attempt, however, > Python performs significantly poorer than IDL for several of the tests. I > have attached a graph which shows the results for one machine: the x-axis is > the test # being compared, and the y-axis is the time it took to complete > the test, in milliseconds. While it is possible that this is simply due to > limitations in Python/Numpy, I suspect that this is due at least in part to > our lack in familiarity with NumPy and SciPy. > > So my question is, does anyone see any places where we are doing things > very inefficiently in Python? > > In order to try and ensure a fair comparison between IDL and Python there > are some things (e.g. the style of timing and output) which we have > deliberately chosen to do a certain way. In other cases, however, it is > likely that we just didn't know a better method. > > Any feedback or suggestions people have would be greatly appreciated. > Unfortunately, due to the proprietary nature of IDL, we cannot share the > original version of time_test3, but hopefully the comments in time_test3.py > will be clear enough. > > Thanks! > Keith > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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