深度学习（二）Numpy入门 数组与矩阵运算,Array常用函数

数组运算

import numpy as np
a = np.random.randint(1,10,size=12).reshape(3,4)
b = np.random.randint(1,10,size=12).reshape(3,4)
print ("a is %s" %(a))
print ("b is %s" %(b))
print ("a+b is %s" %(a+b))
print ("a-b is %s" %(a-b))
print ("a*b is %s" %(a*b))
print ("a/b is %s" %(a/b))

a is [[9 6 9 8]
 [1 7 8 7]
 [9 3 3 1]]
b is [[7 2 6 5]
 [2 8 7 5]
 [3 6 2 6]]
a+b is [[16  8 15 13]
 [ 3 15 15 12]
 [12  9  5  7]]
a-b is [[ 2  4  3  3]
 [-1 -1  1  2]
 [ 6 -3  1 -5]]
a*b is [[63 12 54 40]
 [ 2 56 56 35]
 [27 18  6  6]]
a/b is [[1.28571429 3.         1.5        1.6       ]
 [0.5        0.875      1.14285714 1.4       ]
 [3.         0.5        1.5        0.16666667]]

矩阵运算

np.mat([[1,2,3],[4,5,6]])
Out[15]: 
matrix([[1, 2, 3],
        [4, 5, 6]])

import numpy as np
a = np.random.randint(1,10,size=12).reshape(3,4)
b = np.random.randint(1,10,size=12).reshape(3,4)
A = np.mat(a)
B = np.mat(b)
print ("A is %s" %(A))
print ("B is %s" %(B))
print ("A+B is %s" %(A+B))
print ("A-B is %s" %(A-B))
C = np.mat(np.random.randint(1,10,size=12).reshape(3,4))
D = np.mat(np.random.randint(1,10,size=12).reshape(4,3))
print ("C*D is %s" %(C*D))#A矩阵的行数要跟B矩阵的列数相同

A is [[5 3 2 3]
 [6 2 7 2]
 [1 4 6 1]]
B is [[3 6 5 5]
 [9 2 8 1]
 [4 1 9 1]]
A+B is [[ 8  9  7  8]
 [15  4 15  3]
 [ 5  5 15  2]]
A-B is [[ 2 -3 -3 -2]
 [-3  0 -1  1]
 [-3  3 -3  0]]
C*D is [[ 31  57  53]
 [ 62 103 126]
 [ 44  81 104]]

Arrray常用函数

a = np.random.randint(1,10,size=12).reshape(3,4)
print ("a is %s" %(a))
print ("数组a的总和 %s" %(np.sum(a)))
print ("数组a的第0行总和 %s" %(np.sum(a[0])))
print ("数组a的第0列总和 %s" %(np.sum(a[:,0])))
print ("数组a的最大值 %s" %(np.max(a)))
print ("数组a第0行的最大值 %s" %(np.max(a[0])))
print ("数组a第0列的最大值 %s" %(np.max(a[:,0])))

a is [[5 4 2 9]
 [3 5 9 3]
 [4 6 1 7]]
数组a的总和 58
数组a的第0行总和 20
数组a的第0列总和 12
数组a的最大值 9
数组a第0行的最大值 9
数组a第0列的最大值 5