Creation of a custom random vector

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 math as m

# 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)

	v0	v1
0	0.6298765566077771	2.8828052237192603
1	0.13527635081884104	2.032502751204385
2	0.3470570412135219	2.9694230211349892
3	0.9206795933570506	2.5030401514493823
4	0.06320607651305044	2.2927568937477316

# Get mean
randomVector.getMean()

[0.5,2.5]

# Compute the probability contained in an interval
randomVector.getCovariance()

[[ 1 0 ]
[ 0 1 ]]