Re: [Matplotlib-users] Is really matplotlib this slooow for displaying images ? (sorry again)

[John H. <jdh...@ac...>]

>>>>> "John" == John Hunter <jdh...@ac...> writes:

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

Well, Xavier Gnata just pointed out to me off list that almost half
the cost of the default image handling was in the normalization calls
to min and max.  After a little poking around, I discovered we were
using python's min and max here, which means sequence API.  Ouch!

So we get another 2x speedup on top of the numbers I just posted using
default normalization and colormapping.

# GTKAgg default normalization and colormapping

   # 0.65
   matplotlib 0.65 figimage : 9.97s    
   matplotlib 0.65 imshow   : 9.91s    

   # optimization numbers in my last post
   matplotlib figimage  : 5.23s    
   matplotlib imshow    : 5.18s    

   # as above but using nxmin and nxmax
   matplotlib figimage  : 2.21s    
   matplotlib imshow    : 2.24s    

So out of the box the next matplotlib will be more than 4x faster than
the last release for images.  A long way from MIDAS and IRAF, but
still satisfying for a day's work.

JDH