numpy.random.triangular() in Python
With the help of numpy.random.triangular() method, we can get the random samples from triangular distribution from interval [left, right] and return the random samples by using this method.
Syntax : numpy.random.triangular(left, mode, right, size=None)
Parameters :
1) left – lower limit of the triangle.
2) mode – peak value of the distribution.
3) right – upper limit of the triangle.
4) size – total number of samples required.
Return : Return the random samples as numpy array.
Example #1 :
In this example we can see that by using numpy.random.triangular() method, we are able to get the random samples of triangular distribution and return the numpy array.
Python3
import numpy as np
import matplotlib.pyplot as plt
gfg = np.random.triangular( - 5 , 0 , 5 , 5000 )
plt.hist(gfg, bins = 50 , density = True )
plt.show()
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Output :
Example #2 :
Python3
import numpy as np
import matplotlib.pyplot as plt
gfg = np.random.triangular( - 10 , 8 , 10 , 15000 )
plt.hist(gfg, bins = 100 , density = True )
plt.show()
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Output :
Last Updated :
18 Aug, 2020
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