numpy.random.standard_cauchy() in 1Python

0 0 1 minute read

With the help of numpy.random.standard_cauchy() method, we can see get the random samples from a standard cauchy distribution and return the random samples.

Standard cauchy distribution

Syntax : numpy.random.standard_cauchy(size=None)

Return : Return the random samples as numpy array.

Example #1 :

In this example we can see that by using numpy.random.standard_cauchy() method, we are able to get the random samples of standard cauchy distribution and generate the random samples from it.

Python3

# import numpy 
import numpy as np 
import matplotlib.pyplot as plt 
  
# Using standard_cauchy() method 
gfg = np.random.standard_cauchy(100000) 
  
gfg = gfg[(gfg>-25) & (gfg<25)] 
plt.hist(gfg, bins = 100, density = True) 
plt.show()

Output :

Example #2 :

Python3

# import numpy 
import numpy as np 
import matplotlib.pyplot as plt 
  
# Using standard_cauchy() method 
gfg = np.random.standard_cauchy(100000) 
gfg1 = np.random.power([gfg>0], 100000) 
  
plt.hist(gfg1, bins = 100, density = True) 
plt.show()