numpy.random.standard_cauchy() in 1Python
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 as np
import matplotlib.pyplot as plt
gfg = np.random.standard_cauchy( 100000 )
gfg = gfg[(gfg> - 25 ) & (gfg< 25 )]
plt.hist(gfg, bins = 100 , density = True )
plt.show()
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Output :
Example #2 :
Python3
import numpy as np
import matplotlib.pyplot as plt
gfg = np.random.standard_cauchy( 100000 )
gfg1 = np.random.power([gfg> 0 ], 100000 )
plt.hist(gfg1, bins = 100 , density = True )
plt.show()
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Output :
Last Updated :
18 Aug, 2020
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