Dan Goodman <dg.gmane <at> thesamovar.net> writes:
...
> I got around 5x slower. Using numexpr 'dumbly' (i.e. just putting the
> expression in directly) was slower than the function above, but doing a
> hybrid between the two approaches worked well:
>
> def timefunc_numexpr_smart():
> _sin_term = sin(2.0*freq*pi*t)
> _exp_term = exp(-dt/tau)
> _a_term = (_sin_term-_sin_term*_exp_term)
> _const_term = -b*_exp_term + b
> v[:] = numexpr.evaluate('a*_a_term+v*_exp_term+_const_term')
> #numexpr.evaluate('a*_a_term+v*_exp_term+_const_term', out=v)
>
> This was about 3.5x slower than weave. If I used the commented out final
> line then it was only 1.5x slower than weave, but it also gives wrong
> results. I reported this as a bug in numexpr a long time ago but I guess it
> hasn't been fixed yet (or maybe I didn't upgrade my version recently).
I just upgraded numexpr to 2.2 where they did fix this bug, and now the
'smart' numexpr version runs exactly as fast as weave (so I guess there were
some performance enhancements in numexpr as well).
Fantastic!
Dan
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