Hi all, Thank you for your replies ... my question was initially unclear in that I knew that using normal slicing would do the trick, but it was rather a list of indices that couldn't be represented as a slice that was bugging me. Luckily, Robert's solution solves this problem for the general case.
Thanks for the help, -steve On Jan 30, 2007, at 12:09 AM, Robert Kern wrote: > Steve Lianoglou wrote: >> === >> import numpy as N >> mat = N.zeros((10,10)) >> rows = [0,1,2] >> cols = [4,5,6] >> >> for row in rows: >> mat[row,cols] += 1 >> >> ==== >> >> I found something on the lists from a few years back that was in >> reference to numeric or numarray that suggested doing some gymnastics >> with take/put, but it still seemed as if there was no way to slice >> out this view of a matrix w/o making a copy. > > Actually, it's pretty easy these days to handle the general case > (the other > posts have sufficiently covered the case where your rows and > columns are > representable by slices). Just make sure that the index arrays row > and cols are > the right shape. Since you want mat[rows, cols] to be an array of > shape > (len(rows), len(cols)), each index should be of that shape *or* > they need to > broadcast to that shape. Thus, you could either have this: > > rows = [[0, 0, 0], > [1, 1, 1], > [2, 2, 2]] > cols = [[4, 5, 6], > [4, 5, 6], > [4, 5, 6]] > > or you could have this: > > rows = [[0], [1], [2]] > cols = [4, 5, 6] > > Here is a slightly more complicated example: > > > In [25]: from numpy import * > > In [26]: A = arange(6*6).reshape((6,6)) > > In [27]: rows = array([0, 2, 3])[:,newaxis] > > In [28]: cols = array([5, 4, 1]) > > In [29]: A[rows, cols] > Out[29]: > array([[ 5, 4, 1], > [17, 16, 13], > [23, 22, 19]]) > > In [30]: A > Out[30]: > array([[ 0, 1, 2, 3, 4, 5], > [ 6, 7, 8, 9, 10, 11], > [12, 13, 14, 15, 16, 17], > [18, 19, 20, 21, 22, 23], > [24, 25, 26, 27, 28, 29], > [30, 31, 32, 33, 34, 35]]) > > -- > 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 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
