I am now trying to switch from ppgplot to matplotlib and I
really like the latter for the much nicer plots and functionalities
(although limitations such as the absence of contour plots is a critical one).
There is progress being made on contour plots. We've implemented a basic
version that John Hunter is looking at now.
However, I just made a small script to plot 10 small subplots
on a single window repeatedly (going through slices of an array each time)
and it is bloody slooooooooow (a very large factor slower than anything
I can use to do the same thing with python and some graphical functions).
I personnally think this is a major limitation (with the contours) of
that piece of soft, and may discourage many (and myself).
Could you give some indication of what speed you are getting vs what you
have gotten under other plotting packages? How big is the slice (how many
points)? What kind of plot? Showing the actual script may help a lot in
understanding why it is so slow. There may be other ways that are faster,
or it will at least point to the main bottleneck that could stand improvement.
This complaint is too general to be helpful. I'm not sure it should be
matplotlib's goal to be the fastest package around, but it should be
fast enough for ordinary plotting (which means different things to
different people of course).
Is there a way to improve (dramatically) this? Is there a plan there?
thanks in advance,
P.S.: by the way I solved the cursor problem I posted (and got no answer)
by defining a new cursor class (something already hinted
by many on the web), if anyone is interested..
I missed this post (I'm too busy at the moment to read all posts).
Yes, having this functionality is important. Some of this is possible
now but John has this at his fingertips (I can't recall the details).
If I have time I'll see if I can dig this up.
On Dec 8, 2004, at 3:29 AM, Eric Emsellem wrote: