numpy.random.standard_cauchy() in 1Python

numpy.random.rayleigh() in python

Last Updated : 18 Aug, 2020

With the help of numpy.random.rayleigh() method, we can get the random samples from Rayleigh distribution and return the random samples.

Rayleigh distribution function

Syntax : numpy.random.rayleigh(scale=1.0, size=None)

Return : Return the random samples as numpy array.

Example #1 :

In this example we can see that by using numpy.random.rayleigh() method, we are able to get the rayleigh distribution and return the random samples.

Python3

# import numpy 
import numpy as np 
import matplotlib.pyplot as plt 
  
# Using rayleigh() method 
gfg = np.random.rayleigh(3.4, 50000) 
  
plt.figure() 
plt.hist(gfg, bins = 50, density = True) 
plt.show()

Output :

Example #2 :

Python3

# import numpy 
import numpy as np 
import matplotlib.pyplot as plt 
  
# Using rayleigh() method 
gfg = np.random.rayleigh(2 * np.sqrt(np.pi), 100000) 
  
plt.figure() 
plt.hist(gfg, bins = 50, density = True) 
plt.show()

Output :

numpy.random.standard_cauchy() in 1Python

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