Hamish wrote:
Jose Gómez-Dans wrote:
My take on this is to rasterize my vector data with gdal_rasterize (you
can have a look at the rasterisation code and see how it works, in case
you need to eg buffer your vector data), load it up in python, load my
dataset in python, and calculate whatever stats with scipy+numpy. If
you look at this thread, you'll find it is very fast:
<http://article.gmane.org/gmane.comp.python.scientific.user/19412>.
numpy is already requested by the new wxGUI*, so with numpy around anyway,
maybe some python module could be written for grass7, where python is a
full dependency?
* see gui/wxpython/gui_modules/profile.py
I think too that grass should provide a reasonably fast way to get this
kind of stats. You can still devise your own solution if you want, but
IMHO grass must be able to do this job reasonably fast and user-friendly.
Taking the risk of becoming annoying: with r.univar.zonal, everything
could be done in one pass: rasterize vector, no need for mapcalc, run
r.univar.zonal once (which itself needs only one pass), load stats to
attribute table, done. With the example that started this thread,
everything should be completed in very few minutes. Rasterizing the
vector might take the longest.
Anyway, when it comes to processing time, I'm a speed junky, and >5
hours is simply unacceptable if it can also be done in minutes or even
seconds, and grass should do that, not forcing users to come up with
their own workarounds for something that grass is supposed to do.
Markus M
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