Note
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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()