Thanks for your reply. The simplified code is as follows. It takes 7 seconds to process 1000 rows, which is tolerable, but I wonder why it takes so long. Isn't vectorized operation supposed to run very quickly.
from numpy import * componentcount = 300000 currSum = zeros(componentcount) row = zeros(componentcount) #current row rowcount = 50000 for i in range(1,rowcount): row[:] = 1 currSum = currSum + row; On 11/30/06, Robert Kern <[EMAIL PROTECTED]> wrote:
Fang Fang wrote: > Hi, > > I am writing code to sort the columns according to the sum of each > column. The dataset is huge (50k rows x 300k cols), so i have to read > line by line and do the summation to avoid the out-of-memory problem. > But I don't know why it runs very slow, and part of the code is as > follows. Can anyone point out what needs to be modified to make it run > fast? thanks in advance! Nothing leaps out. Generally, it's difficult (or impossible) to answer such questions without running code. Can you distill the time-consuming part into a small, self-contained script with fake data that we can run? -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
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