如何按元素將一維數組添加到二維數組以在 numpy 中獲取 3d 數組

Question

我有一個二維值數組，我想向這個二維數組元素明智地添加一個一維數組，這樣我會得到一個 3d 數組，其中每個元素都是原始二維數組加上一維數組的相應元素。 例如：

A = np.array([
    [10, 9, 8, 7, 6],
    [5, 4, 3, 2, 1]
])
B = np.array([1, 2, 3])

#What A + B should return:
np.array([
    [[11, 10, 9, 8, 7], [6, 5, 4, 3, 2]],
    [[12, 11, 10, 9, 8], [7, 6, 5, 4, 3]],
    [[13, 12, 11, 10, 9], [8, 7, 6, 5, 4]]
])

我能夠使用普通的 for 循環很容易地做到這一點，但這在純 numpy 中可能嗎？

Answer 1

我相信這會給你你想要的 output？

import numpy as np

A = np.array([
    [10, 9, 8, 7, 6],
    [5, 4, 3, 2, 1]
])
B = np.array([1, 2, 3])

A = A.reshape(1, 2, 5)
B = B.reshape(3, 1, 1)

for each in A + B:
    print (each)
    
# Result:
    # [[11 10  9  8  7]
    #  [ 6  5  4  3  2]]
    # [[12 11 10  9  8]
    #  [ 7  6  5  4  3]]
    # [[13 12 11 10  9]
    #  [ 8  7  6  5  4]]

Answer 2

import numpy as np


A = np.array([
    [10, 9, 8, 7, 6], [5, 4, 3, 2, 1]
])
B = np.array([1, 2, 3])

# What A + B should return:
# np.array([
#     [[11, 10, 9, 8, 7], [6, 5, 4, 3, 2]],
#     [[12, 11, 10, 9, 8], [7, 6, 5, 4, 3]],
#     [[13, 12, 11, 10, 9], [8, 7, 6, 5, 4]]
# ])


temp = np.array([A]*len(B)).flatten()
add = np.repeat(B, len(A.flatten()))

temp += add

result = temp.reshape((B.shape[0],)+A.shape)
print(result)

# np.array([
#     [[11, 10, 9, 8, 7], [6, 5, 4, 3, 2]],
#     [[12, 11, 10, 9, 8], [7, 6, 5, 4, 3]],
#     [[13, 12, 11, 10, 9], [8, 7, 6, 5, 4]]
# ])

Answer 3

你可以在這里享受列表理解的樂趣，並用一行代碼來完成

import numpy as np

A = np.array([
    [10, 9, 8, 7, 6],
    [5, 4, 3, 2, 1]
])
B = np.array([1, 2, 3])

r = np.array([A+b for b in B])
print(r)

# [[[11 10  9  8  7]
#   [ 6  5  4  3  2]]
# 
#  [[12 11 10  9  8]
#   [ 7  6  5  4  3]]
# 
#  [[13 12 11 10  9]
#   [ 8  7  6  5  4]]]