Composite

(Source code, png)

../../_images/openturns-Composite-1.png
class Composite(*args)

Composite design of experiments.

Available constructor:

Composite(center, levels)

Composite(dimension, levels)

Parameters:
centersequence of float

Center of the design of experiments. If not specified, the design of experiments is centered on \vect{0} \in \Rset^n.

levelssequence of float of dimension n_{level}

The discretization of directions (the same for each one), without any consideration of unit.

dimensionpositive int

Dimension n of the space where the design of experiments is created.

Notes

Composite is a stratified design of experiments enabling to create a pattern as the union of an Axial pattern and a Factorial one. The number of points generated is 1 + n_{level}(2n+2^n).

In order to scale each direction and translate the grid structure onto the proper center, use the operator *= and += of Sample.

Examples

>>> import openturns as ot
>>> levels = [4.0, 2.0, 7.0]
>>> myCenteredReductedGrid = ot.Composite(2, levels)
>>> mySample = myCenteredReductedGrid.generate()
>>> # Translate the grid
>>> mySample+=4
>>> # Scale each direction
>>> mySample*=2

Methods

generate()

Generate points according to the type of the experiment.

getCenter()

Get the center of the stratified experiment.

getClassName()

Accessor to the object's name.

getLevels()

Get the levels of the stratified experiment.

getName()

Accessor to the object's name.

hasName()

Test if the object is named.

setCenter(center)

Set the center of the stratified experiment.

setLevels(levels)

Set the levels of the stratified experiment.

setName(name)

Accessor to the object's name.

__init__(*args)
generate()

Generate points according to the type of the experiment.

Returns:
sampleSample

The points which constitute the design of experiments. The sampling method is defined by the nature of the experiment.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> myExperiment = ot.Experiment(ot.MonteCarloExperiment(ot.Normal(2),5))
>>> print(myExperiment.generate())
    [ X0        X1        ]
0 : [  0.608202 -1.26617  ]
1 : [ -0.438266  1.20548  ]
2 : [ -2.18139   0.350042 ]
3 : [ -0.355007  1.43725  ]
4 : [  0.810668  0.793156 ]
getCenter()

Get the center of the stratified experiment.

Returns:
centerPoint

Sequence which has different meanings according to the nature of the stratified experiment: Axial, Composite, Factorial or Box (see corresponding documentation).

getClassName()

Accessor to the object’s name.

Returns:
class_namestr

The object class name (object.__class__.__name__).

getLevels()

Get the levels of the stratified experiment.

Returns:
levelsPoint

Sequence which has different meanings according to the nature of the stratified experiment: Axial, Composite, Factorial or Box (see corresponding documentation).

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

setCenter(center)

Set the center of the stratified experiment.

Parameters:
centersequence of float

Sequence which has different meanings according to the nature of the stratified experiment: Axial, Composite, Factorial or Box (see corresponding documentation).

setLevels(levels)

Set the levels of the stratified experiment.

Parameters:
levelssequence of float

Sequence which has different meanings according to the nature of the stratified experiment: Axial, Composite, Factorial or Box (see corresponding documentation).

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

Examples using the class

Create a composite design of experiments

Create a composite design of experiments

Deterministic design of experiments

Deterministic design of experiments

Create a deterministic design of experiments

Create a deterministic design of experiments