Is there a numpy way to do the below without using a loop?
A = np.array([[1,1],[2,2],[3,3],[4,4],[5,5]])
I = np.array([0, 1, 0, 1, 1])
V = np.array([6, 6, 6, 6, 6])
I want to update A such that it has 6 in the corresponding index specified by I. So A becomes ...
A = np.array([[6,1],[2,6],[6,3],[4,6],[5,6]])
Tried the following, but they did not work..
A[I] = V
A[:,I] = V
Try: A[np.arange(len(A)), I] = V:
In [15]: import numpy as np
In [16]: A = np.array([[1,1],[2,2],[3,3],[4,4],[5,5]])
In [17]: I = np.array([0, 1, 0, 1, 1])
In [18]: V = np.array([6, 6, 6, 6, 6])
In [19]: A[np.arange(len(A)), I] = V
In [20]: A
Out[20]:
array([[6, 1],
[2, 6],
[6, 3],
[4, 6],
[5, 6]])
