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() |
Output :