LHSResult

class LHSResult(*args)

Summarize the results of an LHS optimization.

Parameters:

spaceFillingSpaceFilling

The space filling criteria used by optimization algorithm

nRestartint

The number of restarts performed by optimization algorithm

Methods

drawHistoryCriterion(*args)	Draw criterion history.
drawHistoryProbability(*args)	Draw probability history.
drawHistoryTemperature(*args)	Draw temperature history.
getAlgoHistory(*args)	Accessor to the internal values computed during optimization algorithm.
getC2(*args)	Accessor to the C2 criterion evaluated on the optimal design.
getClassName()	Accessor to the object's name.
getMinDist(*args)	Minimum distance accessor.
getName()	Accessor to the object's name.
getNumberOfRestarts()	Restart number accessor.
getOptimalDesign(*args)	Accessor to the optimal design.
getOptimalValue(*args)	Optimal value accessor.
getPhiP(*args)	Accessor the PhiP criterion evaluated on the optimal design.
hasName()	Test if the object is named.
setName(name)	Accessor to the object's name.

Notes

This class is not intendeted to be built by hand, but returned by optimization algorithms.

Examples

>>> import openturns as ot
>>> lhs = ot.LHSExperiment(ot.JointDistribution([ot.Uniform(0.0, 1.0)]*3), 100)
>>> lhs.setAlwaysShuffle(True) # randomized
>>> profile = ot.GeometricProfile()
>>> spaceFilling = ot.SpaceFillingC2()
>>> # Optim algo
>>> algo = ot.SimulatedAnnealingLHS(lhs, spaceFilling, profile)
>>> # first, generate a design
>>> design = algo.generate()
>>> # then, get the result
>>> result = algo.getResult()

__init__(*args)

drawHistoryCriterion(*args)

Draw criterion history.

Parameters:

restartint (optional)

The restart index.

titlestr (optional)

Graph title.

Returns:

graphGraph

The resulting graph.

drawHistoryProbability(*args)

Draw probability history.

Parameters:

restartint (optional)

The restart index.

titlestr (optional)

Graph title.

Returns:

graphGraph

The resulting graph.

drawHistoryTemperature(*args)

Draw temperature history.

Parameters:

restartint (optional)

The restart index.

titlestr (optional)

Graph title.

Returns:

graphGraph

The resulting graph.

getAlgoHistory(*args)

Accessor to the internal values computed during optimization algorithm.

Returns:

historyPoint

Some internal values computed during optimization algorithm. SimulatedAnnealingLHS stores criterion value, temperature and probability at each iteration.

getC2(*args)

Accessor to the C2 criterion evaluated on the optimal design.

Returns:

c2float

The C2 criterion.

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

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

getMinDist(*args)

Minimum distance accessor.

Parameters:

restartint (optional)

The restart index.

Returns:

minDistfloat

The minimum distance of sample points.

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getNumberOfRestarts()

Restart number accessor.

Returns:

restartint (optional)

The number of restart.

getOptimalDesign(*args)

Accessor to the optimal design.

Returns:

designSample

The design that optimizes the criterion.

getOptimalValue(*args)

Optimal value accessor.

Returns:

valuefloat (optional)

The optimal value.

getPhiP(*args)

Accessor the PhiP criterion evaluated on the optimal design.

Returns:

phiPfloat

The PhiP criterion.

hasName()

Test if the object is named.

Returns:

hasNamebool

True if the name is not empty.

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

Examples using the class

Kriging: configure the optimization solver

Kriging: configure the optimization solver

Optimize an LHS design of experiments

Optimize an LHS design of experiments