Nicolas ROUX wrote: > Hi, > > I need help ;-) > I have here a testcase which works much faster in Matlab than Numpy. > > The following code takes less than 0.9sec in Matlab, but 21sec in Python. > Numpy is 24 times slower than Matlab ! > The big trouble I have is a large team of people within my company is ready > to replace Matlab by Numpy/Scipy/Matplotlib, > but I have to demonstrate that this kind of Python Code is executed with the > same performance than Matlab, without writing C extension. > This is becoming a critical point for us. > > This is a testcase that people would like to see working without any code > restructuring. > The reasons are: > - this way of writing is fairly natural. > - the original code which showed me the matlab/Numpy performance differences > is much more complex, > and can't benefit from broadcasting or other numpy tips (I can later give > this code) > > ...So I really need to use the code below, without restructuring. > > Numpy/Python code: > ##################################################################### > import numpy > import time > > print "Start test \n" > > dim = 3000 > > a = numpy.zeros((dim,dim,3)) > > start = time.clock() > > for i in range(dim): > for j in range(dim): > a[i,j,0] = a[i,j,1] > a[i,j,2] = a[i,j,0] > a[i,j,1] = a[i,j,2] > > end = time.clock() - start > > print "Test done, %f sec" % end > ##################################################################### <SNIP> > Any idea on it ? > Did I missed something ?
I think you may have reduced the complexity a bit too much. The python code above sets all of the elements equal to a[i,j,1]. Is there any reason you can't use slicing to avoid the loops? Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
