Create a conditional distribution

In this example we are going to build the distribution of the random vector X conditioned by the random variable Theta

with Theta obtained with the random variable Y through a function f

import openturns as ot
import openturns.viewer as viewer
from matplotlib import pylab as plt

create the Y distribution

YDist = ot.Uniform(-1.0, 1.0)

create Theta=f(y)

f = ot.SymbolicFunction(["y"], ["y", "1+y^2"])

create the X|Theta distribution

XgivenThetaDist = ot.Uniform()

create the distribution

XDist = ot.ConditionalDistribution(XgivenThetaDist, YDist, f)
XDist.setDescription(["X|Theta=f(y)"])
XDist

ConditionalDistribution

• name=ConditionalDistribution
• dimension=1
• weight=1
• range=[-0.999956, 1.99991]
• description=[X|Theta=f(y)]
• isParallel=true
• isCopula=false

Get a sample

XDist.getSample(5)

	X|Theta=f(y)
0	1.431419
1	1.072163
2	0.362335
3	0.1600886
4	1.028835

draw PDF

graph = XDist.drawPDF()
view = viewer.View(graph)
plt.show()