I'm working with 3D numpy arrays and having trouble stacking two of them. Here’s what I’m trying to do:
import numpy as np
grid = np.arange(16).reshape((1, 4, 4))
grid2 = grid[:, :-1, ::-1].copy()
I expected to be able to stack grid and grid2 with np.concatenate on axis=0, like this:
np.concatenate((grid, grid2), axis=0)
But it doesn’t work, nor do np.vstack or np.dstack (I observed that vstack only works on 1D and 2D arrays). I’ve checked the shapes, and I thought they’d align since they’re both derived from grid, but it’s not cooperating.
The goal here is not to reverse all rows and columns, but to only use the first 3 rows of the original grid array, with just the columns reversed. That's why I used grid[:, :-1, ::-1].copy() to keep the rows intact while only switching the columns.
Attempting to concatenate grid and grid2 along axis=0 fails with a ValueError:
ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 4 and the array at index 1 has size 3
Here's an example of a simpler concatenation that does work as expected:
x = np.arange(1, 9).reshape((2, 4))
y = np.arange(4)
np.vstack((x, y)) # Works perfectly
Why does stacking grid and grid2 fail, while simpler cases like x and y work fine? Is there a specific rule or limitation in numpy that I’m missing here?
In this particular case, you could use hstack:
np.hstack([grid, grid2])
For a generic case you should concatenate on axis=1 (all other dimensions must be equal):
np.concatenate([grid, grid2], axis=1)
Output:
array([[[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11],
[12, 13, 14, 15],
[ 3, 2, 1, 0],
[ 7, 6, 5, 4],
[11, 10, 9, 8]]])
Equality of dimensions for concatenate:
grid.shape # (1, 4, 4)
grid2.shape # (1, 3, 4)
# └──── only possible dimension for concatenate
NB. as noted in comments, if your input is really:
grid = np.arange(16).reshape((1, 4, 4))
grid2 = grid[:, ::-1, ::-1].copy()
Then concatenate on axis=0 can work since the other dimensions are now equal:
np.concatenate([grid, grid2], axis=0)
array([[[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11],
[12, 13, 14, 15]],
[[15, 14, 13, 12],
[11, 10, 9, 8],
[ 7, 6, 5, 4],
[ 3, 2, 1, 0]]])
grid.shape # (1, 4, 4)
grid2.shape # (1, 4, 4) # any axis can be used to concatenate