mrkwjc - 7 months ago 51

Python Question

I have an array:

`A = np.array([0, 0, 0])`

and list of indices with repetitions:

`idx = [0, 0, 1, 1, 2, 2]`

and another array i would like to add to A using indices above:

`B = np.array([1, 1, 1, 1, 1, 1])`

The operation:

`A[idx] += B`

Gives the result:

`array([1, 1, 1])`

`B`

`array([2, 2, 2])`

Answer

for this numpy 1.8 added the `at`

reduction:

at(a, indices, b=None)

Performs unbuffered in place operation on operand 'a' for elements specified by 'indices'. For addition ufunc, this method is equivalent to

`a[indices] += b`

, except that results are accumulated for elements that are indexed more than once. For example,`a[[0,0]] += 1`

will only increment the first element once because of buffering, whereas`add.at(a, [0,0], 1)`

will increment the first element twice... versionadded:: 1.8.0

```
In [1]: A = np.array([0, 0, 0])
In [2]: B = np.array([1, 1, 1, 1, 1, 1])
In [3]: idx = [0, 0, 1, 1, 2, 2]
In [4]: np.add.at(A, idx, B)
In [5]: A
Out[5]: array([2, 2, 2])
```

Source (Stackoverflow)