> I would call it doomed by design. If you use it from Python, I don't
> think
> you can beat direct iteration through __getitem__ *of the object*
> that you
> iterate over by introducing another level of indirection that
> introduces a
> method call. I tried islice() and it's still a bit faster than the
> class
> you presented.
Given that islice does the same thing better definitely doomed ;')
> Maybe you could give us some more insight into your actual use case,
> that
> might allow us to come up with better alternatives.
Thanks, that's very kind.
Thing is that currently I'm working on sampling b-spline surfaces, and
compute the curvature of such a surface.
Basically that comes down to making a 500*500 grid of curvature samples.
Computing the curvature is really quick ( call to a SWIG wrapped
object ).
My code looks like:
for a in xrange(1, 500):
for b in xrange(1, 500):
do_curvature()
When I place pass instead of do_curvature() I notice that the time for
such a loop is basically the same, which is why I'm interested in
moving the for loops to cython.
This is a pattern that is happens often in my code, hence it would be
lovely to make a function something like:
loop_fast2d( do_curvature, (1,500), (1,500) )
What makes this pattern hard is that you would have to loop again
through the results, which reduces the time saved by a fast
loop_fast2d function by half.
So perhaps this pattern is more effective:
loop_fast2d( do_curvature, do_result, (1,500), (1,500) )
What do you think? Is this pattern generic enough to be sped up in
Cython?
Thanks,
-jelle
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