Python numpy 2D array sum over certain indices

Question

There is a 2-d array like this:

img = [
  [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
  [[2, 2, 2], [3, 2, 3], [6, 7, 6]],
  [[9, 8, 1], [9, 8, 3], [9, 8, 5]]
]

And i just want to get the sum of certain indices which are like this:

indices = [[0, 0], [0, 1]] # which means img[0][0] and img[0][1]
# means here is represents

There was a similar ask about 1-d array in stackoverflow in this link, but it got a error when I tried to use print(img[indices]). Because I want to make it clear that the element of img are those which indicates by indices, and then get the ~~mean~~ sum of it.

Expected output

[5, 7, 9]

Just to be cleared, when you sum [0,0] and [0,1], the result would be [5, 7, 9], or total 5 +7 + 9 = 21? — Alfred Luu
– Alfred Luu, Commented Jan 18, 2021 at 3:00
Can you provide an example that uses actual arrays, not lists, shows the expected output, and indices that aren't transposeable? — Mad Physicist
– Mad Physicist, Commented Jan 18, 2021 at 3:18

Pablo C · Accepted Answer · 2021-01-18 03:17:29Z

3

Use NumPy:

import numpy as np

img = np.array(img)
img[tuple(indices)].sum(axis = 0)
#array([5, 7, 9])

edited Jan 18, 2021 at 3:17

answered Jan 18, 2021 at 3:00

Pablo C

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10 Comments

Pablo C Over a year ago

@MadPhysicist why?

luneice Over a year ago

I am sorry to say that i did not clear that img[0][0] + img[0][1] should be [5, 7, 9], so in this answer i got the right answer when i changed the axis = 1 to axis = 0.

Pablo C Over a year ago

@luneice edited. by the way, you want the sum or the mean?

Alfred Luu Over a year ago

He want the sum basically. The comment is quite confuse "# which means image[0][0] and image[0][1]", means here is represents

Mad Physicist Over a year ago

Also, you want to transpose the indices most likely

|

Alfred Luu · Accepted Answer · 2021-01-18 03:16:20Z

1

If the result would be [5, 7, 9] which is sum over the column of the list. Then easy:

img = np.asarray(img)
indices = [[0, 0], [0, 1]]
img[(indices)].sum(axis = 0)

Result:

array([5, 7, 9])

answered Jan 18, 2021 at 3:16

Alfred Luu

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Comments

Mad Physicist · Accepted Answer · 2021-01-18 03:22:49Z

1

When you supply a fancy index, each element of the index tuple represents a different axis. The shape of the index arrays broadcasts to the shape of the output you get.

In your case, the rows of indices.T are the indices in each axis. You can convert them into an index tuple and append slice(None), which is the programmatic equivalent of :. You can take the mean of the resulting 2D array directly:

img[tuple(indices.T) + (slice(None),)].sum(0)

Another way is to use the splat operator:

img[(*indices.T, slice(None))].sum(0)

edited Jan 18, 2021 at 3:22

answered Jan 18, 2021 at 3:07

Mad Physicist

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