Hello Brent, thanks for your response. I'll surely give a try to matplotlib soon.
As for the rtree, the generated points are already within the bounding box, so I thought it wouldn't help, would it? Mario On Mon, May 11, 2009 at 5:32 PM, Brent Pedersen <bpede...@gmail.com> wrote: > On Mon, May 11, 2009 at 3:36 AM, Mario Ceresa > <mario.cer...@torrescalla.it> wrote: >> Hi everybody, >> I'd like to remove all the pixeles from an image which are inside a >> given polygon. The first idea that come into my mind was to generate >> all the points which are in the bounding box and then check if they >> actually are inside the polygon: >> >> b = poly.bounds >> xl = b[2] - b[0] >> yl = b[3] - b[1] >> points = (Point(i[0]+b[0],i[1]+b[1]) for i in numpy.ndindex((xl,yl))) >> ps = list((p.x,p.y) for p in points if poly.contains(p)) >> >> For this test b was (38.0, 1073.0, 679.0, 1977.0) which lead to 579464 >> points to be checked. >> >> Actually this is quite slow so I cannot use it on larger images: >> >> >> In [10]: %time a=list(iterops.contains(poly,points)) >> CPU times: user 43.82 s, sys: 0.21 s, total: 44.03 s >> Wall time: 44.10 s >> >> In [12]: %time a=list(iterops.disjoint(poly,points)) >> CPU times: user 42.64 s, sys: 0.20 s, total: 42.83 s >> Wall time: 42.89 s >> >> In [16]: %time a=[p for p in points if poly.contains(p)] >> CPU times: user 42.45 s, sys: 0.16 s, total: 42.61 s >> Wall time: 42.68 s >> >> In [18]: %time a=map(poly.contains,points) >> CPU times: user 37.98 s, sys: 0.15 s, total: 38.12 s >> Wall time: 38.21 s >> >> In [20]: %time a=map(poly.disjoint,points) >> CPU times: user 37.91 s, sys: 0.20 s, total: 38.10 s >> Wall time: 38.18 s >> >> Is there a better way to do the same? Do you happen to know if the new >> prepared geometry could help speeding up a little? >> >> Thanks and regards, >> >> Mario >> _______________________________________________ >> Community mailing list >> Community@lists.gispython.org >> http://lists.gispython.org/mailman/listinfo/community >> > > hi, i'd be interested to see how prepared geometries could speed that up. > but i've found this: > http://matplotlib.sourceforge.net/faq/howto_faq.html?highlight=nxutils#test-whether-a-point-is-inside-a-polygon > to be _extremely_ fast. > > you could also stick your points in an rtree > (http://pypi.python.org/pypi/Rtree/) and grab the points falling > within the bounds, then do the contains() test > on the points that pass that. > > -brent > _______________________________________________ > Community mailing list > Community@lists.gispython.org > http://lists.gispython.org/mailman/listinfo/community _______________________________________________ Community mailing list Community@lists.gispython.org http://lists.gispython.org/mailman/listinfo/community
