Hi John, I wanted to try matplotlib a few days ago, but first I had some trouble compiling it (my debian still uses gcc 2-95, which doesn't understand some 'std' namespace/template stuff) - and then it compiled, but segfaulted. Maybe I didn't get "set NUMERIX" stuff right - how do I know that it actually built _and_ uses the wx-backend ?
BTW, from the profiling/timing I did you can tell that wxPyPlot actually plots 25000 data points in 0.1 secs - so it's _really_ fast ... So it would be nice to get to the ground of this ...
Thanks for the comment, Sebastian
On Friday 25 June 2004 02:12 pm, John Hunter wrote:
"Sebastian" == Sebastian Haase firstname.lastname@example.org writes:
Sebastian> Hi, The long story is that I'm looking for a good/fast Sebastian> graph plotting programs; so I found WxPyPlot Sebastian> (http://www.cyberus.ca/~g_will/wxPython/wxpyplot.html) Sebastian> It uses wxPython and plots 25000 data points (with Sebastian> lines + square markers) in under one second - using Sebastian> Numeric that is.
Not an answer to your question ....
matplotlib has full numarray support (no need to rely on sequence API). You need to set NUMERIX='numarray' in setup.py before building it *and* set numerix : numarray in the matplotlib rc file. If you don't do both of these things, your numarray performance will suffer, sometimes dramatically.
With this test script
from matplotlib.matlab import * N = 25000 x = rand(N) y = rand(N) scatter(x,y, marker='s') #savefig('test') show()
You can do a scatter plot of squares, on my machine in under a second using numarray (wxagg or agg backend). Some fairly recent changes to matplotlib have moved this drawing into extension code, with an approx 10x performance boost from older versions. The latest version on the sf site (0.54.2) however, does have these changes.
To plot markers with lines, you would need
instead of scatter. This is considerably slower (approx 3s on my system), mainly because I haven't ported the new fast drawing of marker code to the line class. This is an easy fix, however, and will be added in short order.
This SF.Net email sponsored by Black Hat Briefings & Training. Attend Black Hat Briefings & Training, Las Vegas July 24-29 - digital self defense, top technical experts, no vendor pitches, unmatched networking opportunities. Visit www.blackhat.com _______________________________________________ Numpy-discussion mailing list Numpyemail@example.com https://lists.sourceforge.net/lists/listinfo/numpy-discussion