Python：Numpy学习

 1 import numpy as np
 2 # 基础属性
 3 array = np.array([[[1,2,3], [0,0,1]], [[1,2,3], [0,0,1]]],
 4                  dtype = np.int64)
 5 
 6 print(array)
 7 print(array.ndim)  # number of dim
 8 print(array.shape) # shape
 9 print(array.size)  # number of elements
10 print(array.dtype)
11 
12 # 创建array
13 a = np.array([1,2,3,4]) # 1 dim
14 
15 b = np.array([[1,2,3,4]]) # row vector, 2 dim
16 c = np.array([[1], [2], [3] ,[4]]) # column vector, 2 dim
17 print(a.shape, b.shape, c.shape)
18 
19 a = np.zeros( (2,3), dtype = np.float) 
20 a = np.ones( (2,3), dtype = np.float)
21 a = np.empty( (2,3), dtype = np.float)
22 a = np.arange(10, 20) # alike function range
23 a = np.linspace(1, 10, 5) # interval 
24 print(a)
25 
26 # 基础运算（向量式运算）
27 ‘‘‘向量‘‘‘
28 a = np.array([10, 20, 30, 40])
29 b = np.arange(4)
30 print( a + b) 
31 print( a**2) 
32 print( a < 20) 
33 
34 ‘‘‘矩阵‘‘‘
35 a = np.array([[1,1],
36               [0,1]])
37 b = np.arange(4).reshape((2,2))
38 print( a*b )
39 print( np.dot(a, b) ) # equal a.dot(b)
40 
41 print(np.argmax(a)) 
42 print(np.argmin(a)) 
43 
44 A = np.arange(14, 2, -1).reshape((3,4))
45 print(np.clip(A, 5, 9))
46 
47 ‘‘‘随机数‘‘‘ # module: np.random
48 a = np.random.random((2,4))
49 print(a)
50 print(np.sum(a, axis = 1))
51 print(np.min(a, axis = 0))
52 
53 # 索引
54 ‘‘‘一维array‘‘‘
55 A = np.arange(3, 15)
56 print(A[2])
57 print(A[0:5:2])
58 
59 ‘‘‘二维array‘‘‘
60 A = np.arange(3, 15).reshape(3, 4)
61 print(A[2])
62 print(A[2,:])
63 
64 print(A[2][1])
65 print(A[2, 1])
66 
67 # array合并
68 A = np.array([1,1,1])
69 B = np.array([2,2,2])
70 
71 print(np.vstack((A,B))) # vertival stack
72 print(np.hstack((A,B))) # horizontal stack
73 
74 A[np.newaxis, :] # 1 * 3
75 A[:, np.newaxis] # 3 * 1
76 
77 a = np.array([[1, 2], [3, 4]])
78 b = np.array([[5, 6]])
79 
80 # array分割
81 A = np.arange(12).reshape((3,4))
82 
83 print(np.split(A, 2, axis = 1))
84 print(np.array_split(A, 3, axis = 1))
85 print(np.split(A, 3, axis = 0))
86 
87 print(np.vsplit(A, 3))
88 print(np.hsplit(A, 2))
89 
90 # copy and deep copy
91 a = np.array([1,2,3,10])
92 b = a
93 c = a
94 d = b
95 
96 b = a.copy()
97 a[3] = 44
98 print(a)
99 print(b)