On 30/01/2008, Francesc Altet <[EMAIL PROTECTED]> wrote: > A Wednesday 30 January 2008, Nadav Horesh escrigué: > > In the following piece of code: > > >>> import numpy as N > > >>> R = N.arange(9).reshape(3,3) > > >>> ax = [1,2] > > >>> R > > > > array([[0, 1, 2], > > [3, 4, 5], > > [6, 7, 8]]) > > > > >>> R[ax,:][:,ax] = 100 > > >>> R > > > > array([[0, 1, 2], > > [3, 4, 5], > > [6, 7, 8]]) > > > > Why R is not updated? > > Because R[ax] is not a view of R, but another copy of the original > object (fancy indexing does return references to different objects). > In order to get views, you must specify only a slice of the original > array. For example:
This is not exactly correct. There are two kinds of fancy indexing in numpy, which behave similarly. There is normal fancy indexing, which produces a new array, not sharing data with the old array: a = N.random.normal(size=10) b = a[a>0] There is also fancy indexing of lvalues (to use a C term): a = N.random.normal(size=10) a[a<0] *= -1 Here no copy is made; instead, the data is modified in-place. This requires some clever hacks under the hood, since a[a<0] *can't* be a view of a. The problem the OP had is that they are going beyond what the clever hacks can deal with. That's why R[ax,:] = 100 works but R[ax,:][:,ax] = 100 doesn't. The problem is that you have two indexing operations in the second situation, and the inplace operators can't deal with that. Solutions include working on a flattened version of the array (for which a single indexing operation suffices), using the (not in-place) where() construct, or using the ix_ function: R[N.ix_(ax,ax)] = 100 N.ix_ is necessary because R[ax,ax] doesn't do what I, for one, would have expected: R[[1,2],[3,4]] yields [R[1,3],R[2,4]], not [[R[1,3],R[1,4]],[R[2,3],R[2,4]]]. But in any case, once you reduce it to a single fancy-indexing operation, you can successfully use it as an lvalue. Striding and views are not really the issue. Anne _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
