I'm having a bit of trouble making sense of all the different numeric-array libraries that Matplotlib uses and allows. We're using Matplotlib as part of a larger application, and I want to make sure we use the best combination of libraries.
Is it a case of 'whichever you like' or is one of the numeric-array libraries clearly better and more stable than the others?
Also, what is Scipy doing these days? Is matplotlib still buried away inside it, as I believe it was, or have they switched to another plotting library altogether? I saw something about 'dynamic plots' but I wasn't sure it was at stable or development stage.
Finally, from the documentation of Matplotlib, I got the impression that it would 'sniff out' and find a suitable numeric-array library. Instead it seems that it only tries to include one ('numeric' as I recall), and if you want to use any other one it won't try for it, you have to manually tell it so using something like the following. Would some automated attempt to load the numeric-array libraries, in order of most preferred to least preferred, be appropriate in the matplotlib code?
matplotlib.rcParams['numerix'] = 'numarray' import pylab
If I want to "back the winning horse" here, which numeric library should I tell the users of our software to install?
Department of Mechanical and Manufacturing Engineering
University of New South Wales, Sydney, Australia