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

[Perry G. <pe...@st...>]

On Dec 20, 2004, at 3:55 AM, Eric Emsellem wrote:

>

Sorry to get into this discussion so late.

> sterday I tried with a 1600x1600 pixels image. NOTE: this is a very 
> reasonable
> size (and typical) in my work and I expect much much bigger ones in a 
> near future
> (up to 20 000 x 20 000).
>
Wow, I want your 20Kx20K image display! Seriously, it sounds like you 
do not intend to display the whole thing at once. In that case I would 
consider doing the slicing and reduction outside of matplotlib and then 
displaying the subsampled or sliced region using the size of the 
window. Applying color transformations on the whole image is going to 
result in a lot of wasted cpu time. I also recognize that 1.6K^2 
displays are not that unreasonable so reasonable performance with this 
size is something one wants to achieve.

> ==> Matplotlib takes ~20 seconds to display it !!!
>  (after 12 seconds the window opens, and then it takes
>  another 8 seconds to be displayed)
>
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.

> (as compared to less than .2 sec for Midas, Iraf and others so a 
> factor of 100 at least!!!
> and less than a second using the ppgplot routines).
>
For better understanding the comparison, when you use Midas, what are 
you displaying to? It's been a long, long, time since I've used Midas 
so I forget (or likely, it's changed) how image display is done. Are 
you using DS9, ximtool or SAOIMAGE? Or a different display mechanism?

By the way, we do have a module that allows displaying numarray images 
to DS9 and related image display programs (google numdisplay). But if 
you are hoping to combine matplotlib features with image display, this 
isn't going to help much. But if you are looking mainly to use DS9 or 
ximtool features, you can just use them directly and save yourself the 
trouble of trying to emulate them (not that wouldn't be a nice thing to 
have for matplotlib).


Perry