python - 从 3D 数组中减去 2D 数组

Question

我有一个 3D 数组，其中包含许多 2D 数组。我还有一个二维数组。我想从 3D 数组的每个元素中减去这个 2D 数组。我这样做了(BT_19 是 3D 数组，Avg_19 是二维数组。A 是我创建的新数组)

A=[]
for i in len(range(BT_19)):
   ref = BT_19[i]-Avg_19
   A = np.concatenate((A,[ref]),axis=0)
   print A 

然后我得到了这个错误，

---

TypeError                                 Traceback (most recent call last)
<ipython-input-83-429b94e5b4d6> in <module>()
      1 A=[]
      2 abc=0
----> 3 for i in len(range(BT_19)):
      4     ref = BT_19[i]-Avg_19
      5     A = np.concatenate((A,[ref]),axis=0)

TypeError: only length-1 arrays can be converted to Python scalars

Answer 1

您可以使用 Numpy 的广播概念执行计算，因为您有一个 2D 矩阵，您的操作(减法)将按如下方式广播到 3D 矩阵:

In [1]: x = np.array([[1,1], [2,2]])
In [2]: x
Out[2]: 
array([[1, 1],
       [2, 2]])
In [3]: y = np.random.randint(0,10, size=(5,2,2))

In [4]: y.shape
Out[4]: (5, 2, 2)

In [5]: y
Out[5]: 
array([[[3, 2],
        [4, 6]],

       [[9, 9],
        [5, 8]],

       [[0, 9],
        [5, 2]],

       [[6, 3],
        [9, 5]],

       [[5, 6],
        [5, 0]]])

In [6]: y - x
Out[6]: 
array([[[ 2,  1],
        [ 2,  4]],

       [[ 8,  8],
        [ 3,  6]],

       [[-1,  8],
        [ 3,  0]],

       [[ 5,  2],
        [ 7,  3]],

       [[ 4,  5],
        [ 3, -2]]])