[FIXED] Read 3D array and plot it as 2D like a picture without converting from 3D to 2D like np.concatenate

Issue

x = np.array[[[8, 7, 1, 0, 3],
              [2, 8, 5, 5, 2],
              [1, 1, 1, 1, 1]],

             [[8, 4, 1, 0, 0],
              [6, 8, 5, 5, 2],
              [1, 1, 1, 1, 1]],

             [[2, 4, 0, 2, 3],
              [2, 5, 5, 3, 2],
              [1, 1, 1, 1, 1]],

             [[4, 7, 2, 8, 0],
              [1, 3, 6, 5, 2],
              [1, 1, 1, 1, 1]]]

I want to get an image from this NumPy file with the imshow() command of the matplotlib library but I shouldn't convert it to 3d array. Is there any way to read 3D array and plot it as 2D like this picture.

If I couldn't explain, I normally need to convert the array we have to 2D and draw it. Normally I can use commands like np.concatenate or np.append for this and get the following array.

x = np.array[[[8, 7, 1, 0, 3, 8, 4, 1, 0, 0, 2, 4, 0, 2, 3, 4, 7, 2, 8, 0],
              [2, 8, 5, 5, 2, 6, 8, 5, 5, 2, 2, 5, 5, 3, 2, 1, 3, 6, 5, 2],
              [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]

But I need to draw it without converting it to 2D.

Solution

Your image

depicts a 3 rows × 20 columns array and you start with a (4,3,5) shape, and from the 2D array you've printed

x = np.array([[8, 7, 1, 0, 3, 8, 4, 1, 0, 0, 2, 4, 0, 2, 3, 4, 7, 2, 8, 0],
              [2, 8, 5, 5, 2, 6, 8, 5, 5, 2, 2, 5, 5, 3, 2, 1, 3, 6, 5, 2],
              [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])

I see that you need to concatenate 4 matrices with 3 rows and 5 columns, hence the last dimension must stay untouched while the first two axes must be swapped, so I think the right incantation would be

...
plt.imshow(np.transpose(x, (1,0,2)).reshape(3,20))
...

that gives me

Answered By - gboffi