Am I the only one thinking Jelle might know which bits of his function
are slow? :)
Jelle Feringa wrote:
> n=1
> for a in ogrid[ 0:1:complex(n_samples)].tolist():
> for b in ogrid[ 0:1:complex(n_samples)].tolist():
> curv = curvature( a, b )
> a_wrapped_datatype( n, curv )
> n+=1
> return a_wrapped_datatype
I think your loop might be doing unnecessary work. See if this helps:
cdef int a, b, arrlen
myarray = ogrid[ 0:1:complex(n_samples)]
arrlen = len(myarray)
for a from 0 <= a < arrlen:
for b from 0 <= b < arrlen:
curv = curvature( myarr[a], myarr[b])
The "cdef int" shouldn't give you any benefit right now, rather being
slower. If you can index the array (or its buffer) with non-Python
ints, it should be faster (look at numpy integration, Dag's work :).
If not, just avoiding the calls to tolist() in the inner loop could be
nice.
Check http://docs.cython.org/docs/numpy_tutorial.html
Now, if you could bypass the python layer in certain places, like
calling the real C++_curvature with a real float instead of a python
float, cdef'ing n to [numpy]int and a_wrapped_datatype to (int,
float?), you'd get things going faster without having to start a new
wrapper from zero.
Regards,
Daniel
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