OpenTURNS
SpaceFillingMinDist¶
- class SpaceFillingMinDist(*args)¶
Space filling minimal distance criterion.
Methods
evaluate(sample)Compute the MinDist criterion for a specific design.
Accessor to the object's name.
getName()Accessor to the object's name.
hasName()Test if the object is named.
Minimization flag accessor.
perturbLHS(oldDesign, oldCriterion, row1, ...)Elementary perturbation.
setName(name)Accessor to the object's name.
Notes
Compute the criterion based on the minimal distance of sample points:
If at least one of the sample points does not belong to the unit cube (i.e. not all components belong to the interval
![[0,1]](data:image/svg+xml;base64,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)
),
then the whole sample is rescaled.
Letting 
(resp. 
) denote the point
containing the component-wise maximum (resp. minimum) values of the sample,
the actual formula is in this case:
- __init__(*args)¶
- evaluate(sample)¶
Compute the MinDist criterion for a specific design.
- Parameters:
- design
Sampleor 2-d array like The design
- design
- Returns:
- critfloat
The MinDist criterion
Examples
>>> import openturns as ot >>> # Build an LHS using openturns class >>> lhs = ot.LHSExperiment(ot.Uniform(), 100) >>> design = lhs.generate() >>> # Compute the MinDist criterion >>> crit = ot.SpaceFillingMinDist().evaluate(design)
- getClassName()¶
Accessor to the object’s name.
- Returns:
- class_namestr
The object class name (object.__class__.__name__).
- 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.
- isMinimizationProblem()¶
Minimization flag accessor.
- Returns:
- isMinimizationbool
Whether the problem is a minimization.
- perturbLHS(oldDesign, oldCriterion, row1, row2, column)¶
Elementary perturbation.
- Parameters:
- design
Sample The design to perturb (in-place)
- oldCriterionfloat
The previous value of the criterion
- row1int
First row index
- row2int
Second row index
- design
- Returns:
- criterionfloat
The value of the criterion
- setName(name)¶
Accessor to the object’s name.
- Parameters:
- namestr
The name of the object.
