[SciPy-user] scipy.stats.gaussian_kde for 2d kernel density estimation
Wed Jul 23 05:58:00 CDT 2008
I can't figure out how to do bivariate kernel density estimation with
the scipy.stats.gaussian_kde module .1D evaluation seems working, but 2D
evaluation escapes me.
I have two vectors representing x and y coordinates of points:
The problem is: how do I build the grid to evaluate the points? I would
expect that he wants an x range and a y range (something like
xrange=numpy.arange(0,100,1) ) from which he builds and evaluates the
grid. However this does not work, and I do not understand how to create
a proper 2d-grid that has the correct coordinate information.
Where can I look for information? The built-in documentation seems a bit
terse on this point.
Thanks a lot,
Massimo Sandal , Ph.D.
University of Bologna
Department of Biochemistry "G.Moruzzi"
Via Irnerio 48, 40126 Bologna, Italy
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