上一主题

numpy.ufunc.reduceat

下一主题

numpy.ufunc.at

numpy.ufunc.outer

ufunc.outer(A, B)

将ufunc op应用于所有对(a,b),其中a在A和b在B

M = A.ndimN B.ndim然后,op.outer(A, B)的结果C是维度M + N,使得:

对于AB一维,这等价于:

r = empty(len(A),len(B))
for i in range(len(A)):
    for j in range(len(B)):
        r[i,j] = op(A[i], B[j]) # op = ufunc in question
参数:

A:array_like

第一数组

B:array_like

第二数组

返回:

r:ndarray

输出数组

也可以看看

numpy.outer

例子

>>> np.multiply.outer([1, 2, 3], [4, 5, 6])
array([[ 4,  5,  6],
       [ 8, 10, 12],
       [12, 15, 18]])

多维例子:

>>> A = np.array([[1, 2, 3], [4, 5, 6]])
>>> A.shape
(2, 3)
>>> B = np.array([[1, 2, 3, 4]])
>>> B.shape
(1, 4)
>>> C = np.multiply.outer(A, B)
>>> C.shape; C
(2, 3, 1, 4)
array([[[[ 1,  2,  3,  4]],
        [[ 2,  4,  6,  8]],
        [[ 3,  6,  9, 12]]],
       [[[ 4,  8, 12, 16]],
        [[ 5, 10, 15, 20]],
        [[ 6, 12, 18, 24]]]])