Create a random vectorΒΆ

In this example we are going to create a distribution or copula.

The way to go is inheriting the PythonRandomVector class and overload its methods:

  • getRealization

  • getSample

  • getMean

  • getCovariance

from __future__ import print_function
import openturns as ot
import openturns.viewer as viewer
from matplotlib import pylab as plt
import math as m
ot.Log.Show(ot.Log.NONE)

Inherit PythonRandomVector

class RVEC(ot.PythonRandomVector):

    def __init__(self):
        super(RVEC, self).__init__(2)
        self.setDescription(['R', 'S'])

    def getRealization(self):
        X = [ot.RandomGenerator.Generate(), 2.0 + ot.RandomGenerator.Generate()]
        return X

    def getSample(self, size):
        X = []
        for i in range(size):
            X.append(
                [ot.RandomGenerator.Generate(), 2.0 + ot.RandomGenerator.Generate()])
        return X

    def getMean(self):
        return [0.5, 2.5]

    def getCovariance(self):
        return [[1.0, 0.0], [0.0, 1.0]]

Instanciate our distribution

randomVector = ot.RandomVector(RVEC())

Get a sample

randomVector.getSample(5)
v0v1
00.36477832.877147
10.68228822.080219
20.01467382.321082
30.61123682.234876
40.67844992.590527


Get mean

randomVector.getMean()

[0.5,2.5]



Compute the probability contained in an interval

randomVector.getCovariance()

[[ 1 0 ]
[ 0 1 ]]



Total running time of the script: ( 0 minutes 0.004 seconds)

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