This isn't pretty, but it might do the job:
julia> np.mgrid[:__getitem__]((pybuiltin(:slice)(0,5),
pybuiltin(:slice)(0,5)))
2x5x5 Array{Int64,3}:
[:, :, 1] =
0 1 2 3 4
0 0 0 0 0
[:, :, 2] =
0 1 2 3 4
1 1 1 1 1
[:, :, 3] =
0 1 2 3 4
2 2 2 2 2
[:, :, 4] =
0 1 2 3 4
3 3 3 3 3
[:, :, 5] =
0 1 2 3 4
4 4 4 4 4
It's just a deconstruction of the actual call that happens in python:
In [7]: np.mgrid.__getitem__((slice(0,5), slice(0,5)))
Out[7]:
array([[[0, 0, 0, 0, 0],
[1, 1, 1, 1, 1],
[2, 2, 2, 2, 2],
[3, 3, 3, 3, 3],
[4, 4, 4, 4, 4]],
[[0, 1, 2, 3, 4],
[0, 1, 2, 3, 4],
[0, 1, 2, 3, 4],
[0, 1, 2, 3, 4],
[0, 1, 2, 3, 4]]])
On Tuesday, March 15, 2016 at 12:01:06 PM UTC-4, Chris wrote:
>
> I'm trying to use numpy's mgrid (
> https://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.mgrid.html)
> via PyCall, but I can't figure out what the syntax should be. I've tried
> every permutation I can think of, could someone help me out?
>
> The python call looks like:
>
> >>> np.mgrid[0:5,0:5]array([[[0, 0, 0, 0, 0], [1, 1, 1, 1, 1],
> >>> [2, 2, 2, 2, 2], [3, 3, 3, 3, 3], [4, 4, 4, 4, 4]],
> >>> [[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4],
> >>> [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]])
>
>
> Thanks in advance.
>
