The correlation of a large data (about 250k points) v can be checked via correlate(v,v,mode='full')
and ought to give the same result as the matlab function xcorr(v) FFT might speed up the evaluation ... In my specific case: xcorr takes about 0.2 seconds. correlate takes about 70 seconds. fftconvolve takes about 400 seconds. on the irc channel a second person happened to run into the same problem using mathcad and data consisting of about 300k points: correl takes about 1 second correlate takes 127 seconds fftconvolve was aborded because it took to long These tests were checked and confirmed by two other persons on the irc channel. The computers involved were 32bit as well as 64bit machines. All 4 persons are sure that lapack/atlas libraries are properly installed. Could someone please investigate why correlate and especially fftconvolve are orders of magnitude slower? Should more details / sample data be required, please let me know. Thanks, q ---------------------- executed code: tic=time.time() cor_c1=correlate(c1data[:,1],c1data[:,1],mode='full') toc=time.time() tic=time.time() cor_c1=fftconvolve(c1data[:,1],c1data[:,1],mode='full') toc=time.time() xcorr(data) -- The king who needs to remind his people of his rank, is no king. A beggar's mistake harms no one but the beggar. A king's mistake, however, harms everyone but the king. Too often, the measure of power lies not in the number who obey your will, but in the number who suffer your stupidity. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion