numpy.ufunc.at — NumPy v1.13 Manual (original) (raw)

ufunc. 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.

New in version 1.8.0.

Parameters:

a : array_like The array to perform in place operation on. indices : array_like or tuple Array like index object or slice object for indexing into first operand. If first operand has multiple dimensions, indices can be a tuple of array like index objects or slice objects. b : array_like Second operand for ufuncs requiring two operands. Operand must be broadcastable over first operand after indexing or slicing.

Examples

Set items 0 and 1 to their negative values:

a = np.array([1, 2, 3, 4]) np.negative.at(a, [0, 1]) print(a) array([-1, -2, 3, 4])

Increment items 0 and 1, and increment item 2 twice:

a = np.array([1, 2, 3, 4]) np.add.at(a, [0, 1, 2, 2], 1) print(a) array([2, 3, 5, 4])

Add items 0 and 1 in first array to second array, and store results in first array:

a = np.array([1, 2, 3, 4]) b = np.array([1, 2]) np.add.at(a, [0, 1], b) print(a) array([2, 4, 3, 4])