simple but difficult numpy memory reference problem

import numpy as np

a = np.array([0,0,0,0,0,0,0,0])
b = np.array([4,2,3])
c = np.array([5,5,2])

for i, e in enumerate(c):
    a[e] += b[i]
print(a)
# [0 0 3 0 0 6 0 0]

a = np.array([0,0,0,0,0,0,0,0])
b = np.array([4,2,3])
c = np.array([5,5,2])

a[c] += b[np.arange(len(b))]
print(a)
# [0 0 3 0 0 2 0 0]

The actual length of c is incredibly long. The problem comes from here.

The python for loop is too slow.

So I want to replace this with numpy without python for loop, but I can’t find a way.

I think it’s because of the memory reference.
Is there a way to change the result value of this to the same?

>Solution :

You can try np.add.at:

cnt = np.arange(0, len(c))
np.add.at(a, c, b[cnt])

print(a)

Prints:

[0 0 3 0 0 6 0 0]