On Sunday, April 29, 2012, Ignas Anikevičius wrote:
Hello everybody,

On 28 April 2012 12:13, julien tayon <julien@tayon.net> wrote:
First cpp stands for C Pre Processor, this tool usually does macro
substitution in c, objective c, c++. Hence Cpp in the object is pretty
much confusing when it seems to be talking about C++.

Sorry for my ignorance, will know it in the future
There is another simpler solution however :
Do everything in python : python is a very powerfull gluing langage,
the GIL ensuring that non thread-safe code is thread safe, it is very
forgiving with code not design for concurrency.

I wanted to write in Python as much code as possible, it is just some plot commands are quite slow in matplotlib. For example, I want to work in polar coordinate system to plot a function of 2 variables. For that I want to use the np.meshgrid function and the plot the results with the pcolor command from pyplot. The problem is that with a lot of data points it becomes very slow, which is not acceptable if one wants to draw a lot of plots using this function. Because the array is not ordered and points in space are at irregular intervals, I could not use imshow,  which is much much faster. So I was thinking if there is some internal C++ API which I could use and maybe speed up the plotting itself a bit.

It would actually be very nice if I could do that as most of the toolkits, which can interface with C/C++ do not have LaTeX capabilites. Gnuplot can be used in C/C++, but as far as I remember it is not the most elegant way of doing it...

Going back to the topic, is there any potential to speed up some commands (e.g. pcolor) by rewriting/extending them in Cython or C++? If yes, then maybe I might tinker with the code at some point, when I have more free time.

Anyway, thanks for such detailed answers.

All best,
Ignas A.

Use pcolormesh().  *much* faster if you can assume certain things about the domain.

Ben Root