Python---random library

Table of contents

Basic random number function():

rand.seed()

random()

Extended random number function():

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The random library contains two types of functions: basic random number functions and extended random number functions.

Basic random number functions: seed(), random()

Extended random number functions: randint, getrandbits(), uniform(), randrange(), choice(), shuffle()

Basic random number function():

rand.seed()

When random.seed() is called, it takes the incoming seed as a parameter and converts it into an integer value. This integer value is used to set the starting state of the random number generator. The random number generator generates a sequence of random numbers based on the starting state. These random numbers can be obtained through functions such as random.random().

Note: A seed is a starting value that is used as a starting point for generating a sequence of random numbers. The random number generator calculates the next random number based on the seed and passes that number as the seed to the next calculation.

random.seed(10)#Generate the sequence corresponding to seed 10

#By default, the system time will be used to initialize the seed of the random number generator.​ 

import numpy as np
 
num = 0
np.random.seed(0)
while (num < 5):
 
    print(np.random.rand(1,5))
    num += 1
 
print('-------------------------')

It can be found that after setting the random seed, the random number will be the same every time it is run.

If you annotate the random seed of your program:

import numpy as np
 
num = 0
#np.random.seed(0)
while (num < 5):
 
    print(np.random.rand(1,5))
    num += 1
 
print('-------------------------')

Then you can find that the random number of each execution result is different:

random()

Generate a random decimal between [0.0,1.0)

>>>random.random()

0.5714025946899135

Extended random number function():

function	describe
return(a, b)	Generate an integer between [a, b]
	>>>random.randint(10, 100)
	64
randrange(m, n[, k])	Generate a random integer between [m, n) with k as the step size
	>>>random.randrange(10, 100, 10)
	80
getrandbits(k)	Generate a k-bit long random integer
	>>>random.getrandbits(16)
	37885
uniform(a, b)	Generate a random decimal between [a, b]
	>>>random.uniform(10, 100)
	13.09632165
choice(seq)	Randomly select an element from the sequence seq
	>>>random.choice([1,2,3,4,5,6,7,8,9])
	8
shuffle(seq)	Randomly arrange the elements in the sequence seq and return the scrambled sequence
	>>>s=[1,2,3,4,5,6,7,8,9];random.shuffle(s);print(s)
	[3, 5, 8, 9, 6, 1, 2, 7, 4]