Hi, Please run the exact same code in Matlab that you are running in NumPy. Many of Matlab functions are very highly optimized so these are provided as binary functions. I think that you are running into this so you are not doing the correct comparison
So the ways around it are to write an extension in C or Fortran, use Pysco etc if possible, and vectorize your algorithm to remove the loops (especially the inner one). Bruce On 6/14/06, Sebastian Beca <[EMAIL PROTECTED]> wrote: > Hi, > I'm working with NumPy/SciPy on some algorithms and i've run into some > important speed differences wrt Matlab 7. I've narrowed the main speed > problem down to the operation of finding the euclidean distance > between two matrices that share one dimension rank (dist in Matlab): > > Python: > def dtest(): > A = random( [4,2]) > B = random( [1000,2]) > > d = zeros([4, 1000], dtype='f') > for i in range(4): > for j in range(1000): > d[i, j] = sqrt( sum( (A[i] - B[j])**2 ) ) > return d > > Matlab: > A = rand( [4,2]) > B = rand( [1000,2]) > d = dist(A, B') > > Running both of these 100 times, I've found the python version to run > between 10-20 times slower. My question is if there is a faster way to > do this? Perhaps I'm not using the correct functions/structures? Or > this is as good as it gets? > > Thanks on beforehand, > > Sebastian Beca > Department of Computer Science Engineering > University of Chile > > PD: I'm using NumPy 0.9.8, SciPy 0.4.8. I also understand I have > ATLAS, BLAS and LAPACK all installed, but I havn't confirmed that. > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
