使用python从给定矩阵中随机选择特征

Question

I have a 6 by 6 matrix created using python. From the 36 values included in the matrix, i want to select any 10 values (it should select the values randomly, not by specifying the position) from the matrix which are non-zero and the selected 10 values should be printed at the end. Please help me with the code in python

 import numpy as np
 from numpy import random
 #import Dataframe.sample as df 
 rows = 6
 cols = 6 
 a = np.matrix(np.random.randint(220,376, size=(rows,cols)))
 print (a)

Answer 1

You can access a matrix with matrix[y][x] and generate random indexes with the package random. Random can be used with import random . After it is imported you can generate a random index with x = random.randint(0,5) .

A short example:

import random
for i in range(10): #10 times
    x = random.randint(0,5) #index X
    y = random.randint(0,5) #index Y
    value = matrix[y][x] #get the value
    print(value) #print the value

Please note the name of my matrix is matrix , yours is named a .

Answer 2

Consider a 6x6 matrix:

x = np.arange(36).reshape(6,6)

Then you can use random.choice() on the matrix collapsed into one dimension ( flatten() )

np.random.choice(x.flatten(), 10, replace=False)

to get 10 random elements.

---

For a np.matrix , like in your case it changes and I don't know a direct method. What you can do is as follows. You select the indices.

selected = np.random.choice(a.shape[0]*a.shape[1], 10, replace=False)
# e.g., array([[25, 19,  5,  4, 32, 33, 13,  1,  2, 16]]) 
# a.shape[0]*a.shape[1]=36 in your case

Finally, you take the elements corresponding to the selected indices on the flatten() matrix

a.flatten()[0,selected]

Edit

There is also a direct method based on numpy.matrix.A1

a = np.matrix(np.random.randint(220,376, size=(6,6)))
elements = np.random.choice(a.A1, 10, replace=False)