Summing array values by repeating index for an array

Question

I want to sum the values in vals into elements of a smaller array a specified in an index list idx.

import numpy as np

a = np.zeros((1,3))
vals = np.array([1,2,3,4])
idx = np.array([0,1,2,2])

a[0,idx] += vals

This produces the result [[ 1. 2. 4.]] but I want the result [[ 1. 2. 7.]], because it should add the 3 from vals and 4 from vals into the 2nd element of a.

I can achieve what I want with:

import numpy as np

a = np.zeros((1,3))
vals = np.array([1,2,3,4])
idx = np.array([0,1,2,2])

for i in np.unique(idx):
    fidx = (idx==i).astype(int)
    psum = (vals * fidx).sum()
    a[0,i] = psum 

print(a)

Is there a way to do this with numpy without using a for loop?

cs95 · Accepted Answer · 2018-02-15 12:32:36Z

4

Possible with np.add.at as long as the shapes align, i.e., a will need to be 1D here.

a = a.squeeze()
np.add.at(a, idx, vals)

a
array([1., 2., 7.])

answered Feb 15, 2018 at 12:32

cs95

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1 Comment

Kasravnd Over a year ago

Or without squeezing you can just pass the specific row. np.add.at(a[0], idx, vals).

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