Matthieu Brucher wrote: > > It is a real problem in some communities like astronomers and images > processing people but the lack of documentation is the first one, > that > is true. > > > Even in those communities, I think that a lot could be done at a > higher level, as what IPython1 does (tasks parallelism). > > Matthieu
Well it is not that easy. We have several numpy code following like this : 1) open an large data file to get a numpy array 2) perform computations on this array (I'm only talking of the numpy part here. scipy is something else) 3) Write the result is another large file It is so simple to write using numpy :) Now, if I want to have several exe, step 3 is often a problem. The only simple way to speed this up is to slit step 2 into threads (assuming that there is no other possible optimisation like sse which is false but out of the scope of numpy users). Using C, we can do that using OpenMP pragma. It may not be optimal but it radio speedup/time_to_code is very large :) Now, we are switching from C to numpy because we cannot spend that much time to play with gdb/pointers to open an image anymore. Xavier ps : I have seen your blog and you can send me an email off line about this topic and what you are doing :) _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
