第一种， np矩阵可以直接与标量运算

>>>import numpy as np
>>>arr1 = np.arange(12).reshape([2,2,3])
>>>arr1
array([[[ 0,  1,  2],
        [ 3,  4,  5]],
       [[ 6,  7,  8],
        [ 9, 10, 11]]])
>>>arr1*5
array([[[ 0,  5, 10],
        [15, 20, 25]],
       [[30, 35, 40],
        [45, 50, 55]]])
>>>arr1-5
array([[[-5, -4, -3],
        [-2, -1,  0]],
       [[ 1,  2,  3],
        [ 4,  5,  6]]])
>>>arr1**2
array([[[  0,   1,   4],
        [  9,  16,  25]],
       [[ 36,  49,  64],
        [ 81, 100, 121]]])

第二种，若arr1是高维数组，如果arr2的维度与arr1某个子数组维度相同，那么可以相互作运算。

PyDev console: starting.
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 16:52:21) 
[Clang 6.0 (clang-600.0.57)] on darwin
>>>import numpy as np
>>>arr1 = np.arange(12).reshape([2,2,3])
>>>arr1
array([[[ 0,  1,  2],
        [ 3,  4,  5]],
       [[ 6,  7,  8],
        [ 9, 10, 11]]])
>>>arr2 = np.array([2,2,2])
>>>arr2
array([2, 2, 2])
>>>arr1*arr2
array([[[ 0,  2,  4],
        [ 6,  8, 10]],
       [[12, 14, 16],
        [18, 20, 22]]])
>>>arr3 = np.arange(6).reshape([2,3])
>>>arr1*arr3
array([[[ 0,  1,  4],
        [ 9, 16, 25]],
       [[ 0,  7, 16],
        [27, 40, 55]]])