Hi, I'm trying to use the values of a contour plot to evaluate the min/max
along a given axis in order to marginalize a 2d distribution. This
effectively amounts to doing the same thing asked for in this post:
http://sourceforge.net/mailarchive/message.php?msg_id=47505681.8030306%40hawaii.edu
I think there's an easier way to do this:
val = contour(xRange,yRange,delchi2,[1])
t = asarray(val.collections[0].get_verts())
because the example given in the above post actually return a list, not a
numpy array (unless I did it wrong).
However, even though the above works, it was poorly documented and took
about an hour of googling / guess-and-checking to get to it. Either the
documentation should be improved a little (e.g. explain what "collections"
really means) or some more transparent means of returning the contour data
should be available.
So, the question: is there any easier way to do the above? Is this actually
the easy method?
Thanks,
Adam
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