mrkwjc mrkwjc - 16 days ago 10
Python Question

numpy.array.__iadd__ and repeated indices

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])
, so obviously values from
B
were not summed up. What is the best way to get as a result
array([2, 2, 2])
? Do I have to iterate over indices?

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])