Hi Darren,
If I remember correctly, the thinking under the current behavior is that it preserves similarity of results with histogramdd, where the histogram is oriented in the numpy order (columns, rows). I thought that making histogram2d(x,y) return something different than histogramdd([x,y]) was probably worst than satisfying the cartesian convention.
Regards,
David
2008/5/29 Darren Dale <
darren.dale@cornell.edu>:
I have a question about histogram2d. Say I do something like:
import numpy
from numpy import random
import pylab
x=random.rand(1000)-0.5
y=random.rand(1000)*10-5
xbins=numpy.linspace(-10,10,100)
ybins=numpy.linspace(-10,10,100)
h,x,y=numpy.histogram2d(x,y,bins=[xbins,ybins])
pylab.imshow(h,interpolation='nearest')
pylab.show()
The output is attached. I think I would have expected the transpose of what
numpy histogram2d returned, so the tight x distribution appears along the x
axis in the image. Maybe I am thinking about this incorrectly, or there is a
convention I am unfamiliar with. If the behavior is correct, could the
docstring include a comment explaining the orientation of the histogram
array?
Thanks,
Darren
--
Darren S. Dale, Ph.D.
Staff Scientist
Cornell High Energy Synchrotron Source
Cornell University
275 Wilson Lab
Rt. 366 & Pine Tree Road
Ithaca, NY 14853
darren.dale@cornell.edu
office: (607) 255-3819
fax: (607) 255-9001
http://www.chess.cornell.edu
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