如何在 np.average() 時簡單地傳遞權重

Question

我對將權重傳遞給 np.average() function 感到困惑。 下面的例子：

import numpy as np

weights = [0.35, 0.05, 0.6]
abc = list()

a = [[ 0.5,  1],
   [ 5,  7],
   [ 3,  8]]

b = [[ 10,  1],
   [ 0.5,  1],
   [ 0.7,  0.2]]

c = [[ 10,  12],
   [ 0.5,  13],
   [ 5,  0.7]]

abc.append(a)
abc.append(b)
abc.append(c)

print(np.average(np.array(abc), weights=[weights], axis=0))

OUT:
TypeError: 1D weights expected when shapes of a and weights differ.

我知道形狀不同，但是如何簡單地添加權重列表而不做

np.average(np.array(abc), weights=[weights[0], weights[1], weights[2]], ..., axis=0)

因為我正在執行一個循環，其中權重因大小而異，最大為 30 。

Output：加權數組，如下所示：

OUT:
[[6.675,  7.6],
[ 2.075,  10.3],
[ 4.085,  3.23]]

*average(a * weights[0] + b * weights[1] + c * weights[2])*

歡迎任何其他解決方案。

Answer 1

不確定第一個元素如何是 4.675？

weights = [0.35, 0.05, 0.6]


a = [[ 0.5,  1],
   [ 5,  7],
   [ 3,  8]]

b = [[ 10,  1],
   [ 0.5,  1],
   [ 0.7,  0.2]]

c = [[ 10,  12],
   [ 0.5,  13],
   [ 5,  0.7]]

abc=[a, b, c]

print(np.average(np.array(abc), weights=weights,axis=0))

Answer 2

您的abc數組具有形狀 (1, 3, 3, 2)。 所以要么改變axis=1要么像@BingWang 建議的那樣使用abc = [a, b, c] 。