Hello,
Let's say we have two arrays A and B of shapes (1, 2000) and (1,
4000).
If I do C=numpy.concatenate((A, B), axis=1), I get a new array of
dimension (1, 6000) with duplication of memory.
I am looking for a way to have a non contiguous array C in which the
left (1, 2000)
On Wed, Sep 02, 2009 at 09:40:49AM +0200, V. Armando Solé wrote:
Let's say we have two arrays A and B of shapes (1, 2000) and (1,
4000).
If I do C=numpy.concatenate((A, B), axis=1), I get a new array of
dimension (1, 6000) with duplication of memory.
I am looking for a way to
Gael Varoquaux wrote:
You cannot in the numpy memory model. The numpy memory model defines an
array as something that has regular strides to jump from an element to
the next one.
I expected problems in the suggested case (concatenating columns) but I
did not expect the problem would be so
V. Armando Solé skrev:
I am looking for a way to have a non contiguous array C in which the
left (1, 2000) elements point to A and the right (1, 4000)
elements point to B.
Any hint will be appreciated.
If you know in advance that A and B are going to be duplicated, you can
use
