Andrea Gavana wrote: > By the way, about the solution Francesc posted: > > xyzReq = (xCent >= xMin) & (xCent <= xMax) & \ > (yCent >= yMin) & (yCent <= yMax) & \ > (zCent >= zMin) & (zCent <= zMax) > > xyzReq = numpy.nonzero(xyzReq)[0] > > Do you think is there any chance that a C extension (or something > similar) could be faster?
yep -- if I've be got this right, the above creates 7 temporary arrays. creating that many and pushing the data in and out of memory can be pretty slow for large arrays. In C, C++, Cython or Fortran, you can just do one loop, and one output array. It should be much faster for the big arrays. > Otherwise, I will try and implement it in Fortran and wrap it with > f2py, assuming I am able to do it correctly and the overhead of > calling an external extension is not killing the execution time. nope, that's one function call for the whole thing, negligible. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
