Hi Matthew, I've been working on "rolling/windowed" libraries for quite a while.
I'm currently working on implementations for basic moment and rank statistics - they are pretty much done and I am trying to maneuver them into apache commons math for java. I am also interested in implementing these statistics for python/numpy and R. I have seen a little bit for R, but nothing yet for numpy. /brad On Nov 25, 2007 5:00 PM, Matthew Perry <[EMAIL PROTECTED]> wrote: > Hi all, > > I'm not sure if my terminology is familiar but I'm trying to do a > "moving window" analysis (ie a spatial filter or kernel) on a 2-D > array representing elevation. For example, a 3x3 window centered on > each cell is used to calculate the derivate slope of that cell. > > Can this easily be implemented using numpy? > > Currently I have tried implementing in pure python loops (too slow) > and c++ (fast but more difficult to compile, distribute, wrap in > python calls, etc). I think a good solution would be to leverage numpy > which is both fast and and easy package for end users to install. > > An example of the C++ code I'm trying to emulate is at > http://perrygeo.net/download/hillshade.html . Does anyone have any > tips or examples out there? Where should I start researching this? > > -- > Matthew T. Perry > http://www.perrygeo.net > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion >
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