add numpy subarray to numpy array based on condition

Question

I have a 2d numpy array and a 2d numpy subarray that I want to add to the original array based on a condition. I know that you can add the 2d subarray to the array like this:

original_array[start_x:end_x, start_y:end_y] = sub_array

but I dont know how to efficiently add only values of the sub_array that are bigger than 0?

Example:

orginal_array = np.array([2,2],[2,2],[2,2],[2,2])
sub_array = np.array([0,0],[1,1],[0,1],[0,0])
expected_result = np.array([2,2], [1,1], [2,1], [2,2])

Please update the question with 1) an example of the array, 2) an example of the sub array and 3) an example of the expected output. Cheers. — s3dev
– s3dev, Commented Oct 9, 2020 at 8:21

akilat90 · Accepted Answer · 2020-10-09 08:40:11Z

1

You can index based on the condition >,< 0 and add the arrays.

orginal_array * (sub_array <= 0) + sub_array * (sub_array > 0)

array([[2, 2],
       [1, 1],
       [2, 1],
       [2, 2]])

answered Oct 9, 2020 at 8:40

akilat90

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s3dev · Accepted Answer · 2020-10-09 09:46:55Z

1

Another approach is to use the np.where function as:

np.where(sub_array > 0, sub_array, original_array)

Output:

array([[2, 2], 
       [1, 1], 
       [2, 1], 
       [2, 2]])

answered Oct 9, 2020 at 9:46

s3dev

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NNN · Accepted Answer · 2020-10-09 08:26:47Z

-1

Try,

sub_array2 = np.select([sub_array>0],[sub_array])
original_array[start_x:end_x, start_y:end_y] = sub_array2

answered Oct 9, 2020 at 8:26

NNN

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1 Comment

Danii Kilian Over a year ago

Unfortunately that does not work as expected. I want the values in the original array stay the same, if the values in the subarray are 0 or less than 0. Look at my updated question

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