Composite¶

(Source code, 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.

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.

See also

StratifiedExperiment

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

__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: