Is really matplotlib this slooow for displaying images ? (sorry again)

As John later alluded to, the time for the window to come

    > up is a one time cost if you are running from an
    > interactive prompt. It shouldn't be paid for subsequent
    > display updates.

I made some small changes which helped here - eg, deferring the
initialization of the LUTs until they are actually requested. This
shaved 0.3 s off startup time on my system. With Todd's help, I also
made some changes in the core "fromarray" in extension code which
delivered some speedups, and removed some extra checks in the
colormapping code which are not needed for data that are properly
normalized. I also think I found and fixed redundant calls to draw in
some backends due to improper event handling and hold handling that
crept into 0.65.

Here are my current numbers for a 1600x1600 image

# GTKAgg default normalization and colormapping
   matplotlib 0.65 figimage : 9.97s
   matplotlib 0.65 imshow : 9.91s
   matplotlib CVS figimage : 5.23s
   matplotlib CVS imshow : 5.18s

# GTKAgg prenormalized data and default ("hot") colormapping
   matplotlib 0.65 figimage : 3.46s
   matplotlib 0.65 imshow : 3.37s
   matplotlib CVS figimage : 1.95s
   matplotlib CVS imshow : 2.01s

# GTKAgg prenormalized data and custom grayscale colormapping
   matplotlib 0.65 figimage : 2.05s
   matplotlib 0.65 imshow : 1.95s
   matplotlib CVS figimage : 1.15s
   matplotlib CVS imshow : 1.21s

So the situation is improving. As I noted before, interaction with
plots via the toolbar should also be notably faster.

This would make a good FAQ....