Numpy copy non-zero elements from one array to another (3D array)

Question

my question is if there is an easy way to copy non zero values from one numpy 3d array to another. I wouldn't like to create 3 for loops for that...

Let's say I have an array a:

a = np.array([ [ [1,2,3], [4,5,6]],[[7,8,9], [10,11,12] ] ])
# to visualize it better:
# a = np.array([
#   [  
#     [1,2,3], 
#     [4,5,6]
#   ], 
#   [ 
#     [7,8,9], 
#     [10,11,12] 
#   ] 
# ])
#

then there is an array b:

b = np.array([ [[3,0,9], [0,0,0]], [[0,0,0], [45,46,47]] ])
# to visualize it better:
# b = np.array([
#   [  
#     [3,0,9], 
#     [0,0,0]
#   ], 
#   [ 
#     [0,0,0], 
#     [45,46,47] 
#   ] 
# ])
#

And I would like to merge those arrays to receive non-zero elements from b and other elements from a (these elements that are 0s in b) SO the output would look like:


# 
# np.array([
#   [  
#     [3,2,9], 
#     [4,5,6]
#   ], 
#   [ 
#     [7,8,9], 
#     [45,46,47] 
#   ] 
# ])
#

It doesn't have to be numpy, it can be openCV, but still I would like to know how to achieve this.

Please refresh page to see an update...

emsiiggy
– emsiiggy

2021-07-29 14:52:31 +00:00
Commented Jul 29, 2021 at 14:52 — emsiiggy
– emsiiggy, Commented Jul 29, 2021 at 14:52

sacuL · Accepted Answer · 2021-07-29 14:58:33Z

2

You can try using np.where to select from b with the condition b!=0, or else to select from a:

combined_array = np.where(b!=0, b, a)

>>> combined_array
array([[[ 3,  2,  9],
        [ 4,  5,  6]],

       [[ 7,  8,  9],
        [45, 46, 47]]])

edited Jul 29, 2021 at 14:58

answered Jul 29, 2021 at 14:57

sacuL

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2 Comments

Jack Roberts Over a year ago

Using a similar approach to my other answer, you could do combinied_array[combined_array==0] = new_value where new_value is whatever value you want to use in the case both a and b are 0.

Jack Roberts Over a year ago

Ah right, that's probably possible with np.where too but this works I think: c[np.all(b==0, axis=2)] = a[np.all(b==0, axis=2)] (same as my other answer but selecting elements where all values are 0 along the last axis)

Jack Roberts · Accepted Answer · 2021-07-29 15:00:34Z

1

This should do it:

import numpy as np

a = np.array([ [ [1,2,3], [4,5,6]],[[7,8,9], [10,11,12] ] ])
b = np.array([ [[3,0,9], [0,0,0]], [[0,0,0], [45,46,47]] ])

c = b.copy()
c[b==0] = a[b==0]
print(c)

#[[[ 3  2  9]
#  [ 4  5  6]]
#
# [[ 7  8  9]
#  [45 46 47]]]

Where b==0 is an array with the same shape as b where the elements are True if the corresponding element in b equals 0 and False otherwise. You can then use that to select the zero elements of b and replace them with the values at those indices in a.

Edit: The other answer with np.where is nicer.

answered Jul 29, 2021 at 15:00

Jack Roberts

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