Here is an example of what I would like to do: Assume Array A
A = np.array([[0, 1, 3, 5, 9],
[2, 7, 5, 1, 4]])
And Array B
B = np.array([2, 4])
I am looking for an operation that will increment the element indexed by array B in each row of array A by 1. So the result A is:
A = np.array([[0, 1, 4, 5, 9],
[2, 7, 5, 1, 5]])
The index 2 of first row is increased by 1, and the index 4 of second row is increased by 1
You can achieve this by using advanced indexing in numpy:
A[np.arange(len(B)), B] += 1
This works by creating a 2D array with dimensions (len(B), len(B)) using np.arange(len(B)), which represents the row indices. The second index of the advanced indexing, B, represents the column indices. By adding 1 to A[np.arange(len(B)), B], you increment the elements in each row specified by B.
In numpy you can do by using arrange and shape of an array
import numpy as np
A = np.array([[0, 1, 3, 5, 9],
[2, 7, 5, 1, 4]])
B = np.array([2, 4])
A[np.arange(A.shape[0]), B] += 1
print(A)
np.arange(A.shape[0]) generates an array of integers from 0 to A.shape[0] - 1. A.shape[0] is basically rows
you can do with looping also..
import numpy as np
A = np.array([[0, 1, 3, 5, 9],
[2, 7, 5, 1, 4]])
B = np.array([2, 4])
for i, index in enumerate(B):
A[i][index] += 1
print(A)