Cross-cuts of conditional distributions in 2-d

import openturns as ot
import otbenchmark as otb

Create a Funky distribution

corr = ot.CorrelationMatrix(2)
corr[0, 1] = 0.2
copula = ot.NormalCopula(corr)
x1 = ot.Normal(-1.0, 1.0)
x2 = ot.Normal(2.0, 1.0)
x_funk = ot.ComposedDistribution([x1, x2], copula)

Create a Punk distribution

x1 = ot.Normal(1.0, 1.0)
x2 = ot.Normal(-2.0, 1.0)
x_punk = ot.ComposedDistribution([x1, x2], copula)

distribution = ot.Mixture([x_funk, x_punk], [0.5, 1.0])

referencePoint = distribution.getMean()

Plot cross-cuts of the distribution

crossCut = otb.CrossCutDistribution(distribution)
_ = crossCut.drawConditionalPDF(referencePoint)

Descr =  1 0

_ = crossCut.drawMarginalPDF()