Anne had it right -- much of the point of numpy is to use nd-arrays as the powerful objects they are - not just containers. Below is a version of your code for comparison.
Note to numpy devs: I like the array methods a lot -- is there any particular reason there is no ndarray.abs(), or has it just not been added? -Chris #!/usr/bin/env python """ Simple exmaple of normalizing an array """ import numpy as N from numpy import random mymatrix=random.uniform(-100, 100,(3,4)) print "before:", mymatrix mymatrix2 = mymatrix.copy() numrows,numcols=mymatrix.shape for i in range(numrows): temp=mymatrix[i].max() for j in range(numcols): mymatrix[i,j]=abs(mymatrix[i,j]/temp) print "old way:", mymatrix ## "vectorized" way: # the "reshape" is a bit awkward, but it makes the 1-d result the right shape to "broadcast" to the original array row_max = mymatrix2.max(axis=1).reshape((-1, 1)) print row_max mymatrix2 = N.absolute((mymatrix2 / row_max)) print "vectorized:", mymatrix2 if (mymatrix == mymatrix2).all(): print "They are the same" -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion