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:
I think there's an easier way to do this:
val = contour(xRange,yRange,delchi2,)
t = asarray(val.collections.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?