NumPy参考 >通用功能（ufunc） > numpy.ufunc.at
method
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.
The array to perform in place operation on.
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.
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])
>>> 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)
>>> 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)
>>> a
array([2, 4, 3, 4])