For this to work at all you have to know a priori that there are the same
number of non-zero entries in each row of your mask. Given that you know
that, isn't it just a matter of calling reshape on the second array?
On 14 Oct 2014 20:37, "Neal Becker" wrote:
> I'm using np.nonzero to construct th
I'm using np.nonzero to construct the tuple:
(array([0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2]), array([1, 3, 5, 7, 2, 3, 6, 7, 4,
5, 6, 7]))
Now what I want is the 2-D index array:
[1,3,5,7,
2,3,6,7,
4,5,6,7]
Any ideas?
--
-- Those who don't understand recursion are doomed to repeat it
__
2008/11/14 Catherine Moroney <[EMAIL PROTECTED]>:
> I have three arrays, with dimensions:
>
> A[np]
> L[np]
> S[np]
>
> where L and S indicate the line, smp co-ordinates for each of the
> "np" rows.
> I want to reconstruct the contents of [A] as a 2-dimensional matrix.
>
> The brain-dead version of
Hello,
I know that there must be a fast way of solving this problem, but I
don't know
what it is.
I have three arrays, with dimensions:
A[np]
L[np]
S[np]
where L and S indicate the line, smp co-ordinates for each of the
"np" rows.
I want to reconstruct the contents of [A] as a 2-dimensional
