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 import numpy as np import matplotlib.pyplot as plt # Using triangular() method gfg = np.random.triangular(-5, 0, 5, 5000) 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 triangular() method gfg = np.random.triangular(-10, 8, 10, 15000) plt.hist(gfg, bins = 100, density = True) plt.show() |
Output :
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