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numpy.random.triangular() in Python
  • Last Updated : 18 Aug, 2020

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.

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# 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()

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Output :

Example #2 :

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# 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()

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Output :

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