Create a random design of experiments

Abstract

Random designs of experiments can be generated from probability distributions.

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

ot.Log.Show(ot.Log.NONE)

We create the underlying distribution: a standard 2-dimensional normal distribution.

distribution = ot.Normal(2)
size = 50

The Monte Carlo design of experiments

We build the experiment with the MonteCarloExperiment class :

experiment = ot.MonteCarloExperiment(distribution, size)
sample = experiment.generate()

We draw the design of experiments as a Cloud

graph = ot.Graph("Monte Carlo design", r"$x_1$", r"$x_2$", True, "")
cloud = ot.Cloud(sample, "blue", "fsquare", "")
graph.add(cloud)
view = viewer.View(graph)

Latin Hypercube Sampling

We build the LHS design of experiments with the LHSExperiment class :

experiment = ot.LHSExperiment(distribution, size)
sample = experiment.generate()

We draw the LHS design of experiments as a cloud :

graph = ot.Graph("LHS design", r"$x_1$", r"$x_2$", True, "")
cloud = ot.Cloud(sample, "blue", "fsquare", "")
graph.add(cloud)
view = viewer.View(graph)

Display figures

plt.show()