Hi,
I noticed a behaviour which I found counter-intuitive at least when
using concatenate. I have a function which takes a numpy array of rank 2
as input, let's say foo(in):
a = N.randn((10, 2))
foo(a)
To test a ctype implementation of foo against the python version, my
test has something like
X1 = N.linspace(-2, 2, 10)[:, N.newaxis]
X2 = N.linspace(-1, 3, 10)[:, N.newaxis]
a = N.concatenate(([X1, X2]), 1)
which has Fortran storage (column major order), where as creating a as
a = N.zeros((10, 2))
a[:,0] = N.linspace(-2, 2, 10)
a[:,1] = N.linspace(-1, 3, 10)
has C storage (row major order).
What are the rules concerning storage with numpy ? I thought it was
always C, except if stated explicitly. I can obviously understand why
concatenate gives a Fortran order from an implementation point of view,
but this looks kind of strange to me,
David
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