[Python study notes] Numpy example

Numpy example

1. Generate a one-dimensional array with a starting value of 5, an end value of 15, and 10 samples

   import numpy as np
   a=np.arange(5,15)
   #a=np.array([5,6,7,8,9,10,11,12,13,14])
   print(a)
   

   [ 5 6 7 8 9 10 11 12 13 14]

2. Output diagonal matrix

   #第一种方法
   import numpy as np
   a=np.zeros((3,3))
   for i in range(3):
       for j in range(3):
           if(i==j):
               a[i][i]=1.0
           elif(i!=j):
               a[i][j]=0.0
   print(a)
   

   [[ 1. 0. 0.]

   [ 0. 1. 0.]

   [ 0. 0. 1.]]

   #第二种方法
   import numpy as np
   b=np.identity(3)#也可以用eye函数
   print(b)
   

   [[ 1. 0. 0.]

   [ 0. 1. 0.]

   [ 0. 0. 1.]]

3. Create an array with a boundary value of 1 and internal 0

   #第一种方法
   import numpy as np
   a = np.zeros((10,10),dtype=float)
   for i in range(0,10):
       for j in range(0,10):
           if i == 0 or i == 9 or j == 0 or j == 9:
               a[i][j] = 1
   print(a)
   

   [[ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]]

   #第二种方法
   import numpy as np
   S = np.ones((10, 10))
   S[1:9, 1:9] = 0
   print(S)
   

   [[ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]

   [ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]]

4. Generate a random integer matrix of 5 rows and 10 columns, with numbers ranging from 0 to 100

   data1=np.random.randint(100,size=(5,10)) 
   print(data1)
   print(data1[:2,:])
   

   [[74 10 60 12 66 30 88 12 78 0]

   [10 71 54 62 51 0 47 82 3 67]

   [68 44 2 85 82 36 90 99 63 71]

   [95 25 7 19 85 49 7 15 7 15]

   [47 38 89 52 43 93 97 84 10 24]]

   [[74 10 60 12 66 30 88 12 78 0]

   [10 71 54 62 51 0 47 82 3 67]]

5. Knowing that the matrices A and B are as follows, find the addition and multiplication of the two matrices

   A=np.array([
       [1,2,3],
       [4,5,6],
       [7,8,9]
   ])
   B=np.array([
       [1,1,1],
       [1,1,1],
       [1,1,1]
   ])
   print(A+B)
   print(A.dot(B))
   

   [[ 2 3 4]

   [ 5 6 7]

   [ 8 9 10]]

   [[ 6 6 6]

   [15 15 15]

   [24 24 24]]

   import numpy as np
   
   A=[[1,2,3],[4,5,6],[7,8,9]]
   B=[[1,1,1],[1,1,1],[1,1,1]]
   A=np.array(A)
   B=np.array(B)
   print("和为：",A+B)
   print("乘积为：",A*B)
   

   The sum is: [[2 3 4]

   [ 5 6 7]

   [ 8 9 10]]

   The product is: [[1 2 3]

   [4 5 6]

   [7 8 9]]