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", "")
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", "")
```plt.show()