Transform an array to 1s and 0s using another array

user_10670712 0
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I have two arrays

arr1 = np.array([[4, 1, 3, 2, 5], [5, 2, 4, 1, 3]])
arr2 = np.array([[2], [1]])

I want to transform array 1 to a binary array using the elements of the array 2 in the following way

  • For row 1 of array 1, I want to use the row 1 of array 2 i.e. 2 - to make the top 2 values of array 1 as 1s and the rest as 0s
  • Similarly for row 2 of array 1, I want to use the row 2 of array 2 i.e. 1 - to make the top 1 value of array 1 as 1s and the rest as 0s

So arr1 would get transformed as follows

arr1_transformed = np.array([[1, 0, 0, 0, 1], [1, 0, 0, 0, 0]])

Here is what I tried.

arr1_sorted_indices = np.argosrt(-arr1)

This gave me the indices of the sorted array

array([[1, 3, 2, 0, 4],
       [3, 1, 4, 2, 0]])

Now I think I need to mask this array with the help of arr2 to get the desired output and I'm not sure how to do it.

numpy arrays python
2 Answers

this should do the job in the mentioned case:

def trasform_arr(arr1,arr2):
  for i in range(0,len(arr1)):
    if i >= len(arr2):
      arr1[i] = [0 for x in arr1[i]]
    else:
      sorted_arr = sorted(arr1[i])[-arr2[i][0]:]
      arr1[i] = [1 if x in sorted_arr else 0 for x in arr1[i]]

arr1 = [[4, 1, 3, 2, 5], [5, 2, 4, 1, 3]]
arr2 = [[2], [1]]

trasform_arr(arr1,arr2)
print(arr1)
user_175038890

You can try the following:

import numpy as np

arr1 = np.array([[4, 1, 3, 2, 5], [5, 2, 4, 1, 3]])
arr2 = np.array([[2],[1]])
 
r, c = arr1.shape
s = np.argsort(np.argsort(-arr1))
out = (np.arange(c) < arr2)[np.c_[0:r], s] * 1
print(out)

It gives:

[[1 0 0 0 1]
 [1 0 0 0 0]]
user_151877280
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