Difference between revisions of "Config:SequentialDesign"

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'''Generated for SUMO toolbox version 6.1'''.
+
'''Generated for SUMO toolbox version 7.0'''.
 
''We are well aware that documentation is not always complete and possibly even out of date in some cases. We try to document everything as best we can but much is limited by available time and manpower. We are are a university research group after all. The most up to date documentation can always be found (if not here) in the default.xml configuration file and, of course, in the source files. If something is unclear please dont hesitate to [[Reporting problems|ask]].''
 
''We are well aware that documentation is not always complete and possibly even out of date in some cases. We try to document everything as best we can but much is limited by available time and manpower. We are are a university research group after all. The most up to date documentation can always be found (if not here) in the default.xml configuration file and, of course, in the source files. If something is unclear please dont hesitate to [[Reporting problems|ask]].''
 
== SampleSelector ==
 
== SampleSelector ==
   
 
=== empty ===
 
=== empty ===
Dont select any new samples, useful when modeling multiple outputs in paralel
+
Don't select any new samples, useful when modeling multiple outputs, and you don't want to involve one of these outputs in the sampling process.
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#EmptySampleSelector|EmptySampleSelector]]" combineOutputs="false"/>
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#EmptySampleSelector|EmptySampleSelector]]" combineOutputs="false"/>
 
</source>
 
</source>
 
=== random ===
 
=== random ===
Each sampling iterations new samples are selected randomly
+
Selects new samples randomly in the design space.
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#RandomSampleSelector|RandomSampleSelector]]" combineOutputs="false"/>
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#RandomSampleSelector|RandomSampleSelector]]" combineOutputs="false"/>
 
</source>
 
</source>
 
=== delaunay ===
 
=== delaunay ===
  +
This sample selector uses a Delaunay triangulation of the data to select samples in locations far from previous samples, or in locations where the estimated model error is largest. This algorithm uses QHull, which is very slow for high dimensions, so you should only use this sample selector for less than 6D and for less than 1000 samples.
An adaptive sample selection algorithm that does a trade-off between error and density
 
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false">
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#PipelineSampleSelector|PipelineSampleSelector]]" combineOutputs="false">
  +
<!-- One of all, data -->
 
  +
<[[Config:CandidateGenerator|CandidateGenerator]] type="[[CandidateGenerator#DelaunayCandidateGenerator|DelaunayCandidateGenerator]]"/>
<Option key="sampleSelect" value="all"/>
 
  +
<!-- Integer between 2 and 20 -->
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#modelDifference|modelDifference]]">
<Option key="nLastModels" value="2"/>
 
  +
<Option key="criterion_parameter" value="2"/>
<!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
 
  +
</[[Config:CandidateRanker|CandidateRanker]]>
<Option key="scoreFunction" value="weightedLinear"/>
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#delaunayVolume|delaunayVolume]]"/>
<Option key="lambda" value="0.5"/>
 
  +
<Option key="mu" value="0.5"/>
 
  +
<[[Config:MergeCriterion|MergeCriterion]] type="[[MergeCriterion#WeightedAverage|WeightedAverage]]" weights="[1 1]"/>
<!-- One of none, max, cap, capmax -->
 
  +
<Option key="volumeScaling" value="max"/>
 
<Option key="differenceScaling" value="capmax"/>
 
<!-- Boolean flag -->
 
<Option key="snapToEdge" value="enable"/>
 
<Option key="snapThreshold" value=".2"/>
 
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</source>
 
</source>
 
=== density ===
 
=== density ===
  +
A space-filling sampling algorithm which uses an approximation of the Voronoi tessellation of the design space. Will only sample within the "allowed" areas if constraints are specified.
A simple density based sample selection algorithm
 
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DensitySampleSelector|DensitySampleSelector]]" combineOutputs="false"/>
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#VoronoiSampleRanker|VoronoiSampleRanker]]" combineOutputs="false"/>
 
</source>
 
</source>
 
=== error ===
 
=== error ===
An adaptive sample selection algorithm (error based), driven by the evaluation of your model on a dense grid
+
An adaptive sample selection algorithm (error based), driven by the evaluation of your model on a dense grid, which selects samples in locations where the model error is estimated to be the largest.
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#ErrorSampleSelector|ErrorSampleSelector]]" combineOutputs="false">
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#PipelineSampleSelector|PipelineSampleSelector]]" combineOutputs="false">
  +
<!-- Integer between 2 and 20 -->
 
  +
<[[Config:CandidateGenerator|CandidateGenerator]] type="[[CandidateGenerator#GridCandidateGenerator|GridCandidateGenerator]]"/>
<Option key="nLastModels" value="4"/>
 
  +
<!-- One of none, max, cap, capmax -->
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#modelDifference|modelDifference]]">
<Option key="differenceScaling" value="none"/>
 
  +
<Option key="criterion_parameter" value="4"/>
<!-- Gridsize to evaluate on, one of int or array of dimension length -->
 
  +
</[[Config:CandidateRanker|CandidateRanker]]>
<Option key="gridSize" value="50"/>
 
  +
<!-- Maximum total points to evaluate, distributed over dimensions -->
 
  +
<[[Config:MergeCriterion|MergeCriterion]] type="[[MergeCriterion#ClosenessThreshold|ClosenessThreshold]]">
<Option key="maxGridSize" value="100000"/>
 
  +
<!-- Closeness threshold, Double -->
 
  +
<!-- Closeness threshold, Double -->
<Option key="closenessThreshold" value="0.2"/>
 
  +
<Option key="closenessThreshold" value="0.05"/>
<!-- Set a % of the maximumSamples to randomly chosen -->
 
  +
<!-- Set a % of the maximumSamples to randomly chosen -->
<Option key="randomPercentage" value="20"/>
 
  +
<Option key="randomPercentage" value="20"/>
  +
  +
<Option key="debug" value="off"/>
  +
</[[Config:MergeCriterion|MergeCriterion]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</source>
 
</source>
=== lola ===
+
=== lola-voronoi ===
  +
A highly adaptive sampling algorithm which performs a trade-off between exploration (filling up the design space as equally as possible) and exploitation (selecting data points in highly nonlinear regions). lola-voronoi is the only sample selector which currently supports multiple outputs, auto-sampled inputs and constraints.
A highly adaptive sampling algorithm, error and density based
 
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLASampleSelector|LOLASampleSelector]]" combineOutputs="false">
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLAVoronoiSampleSelector|LOLAVoronoiSampleSelector]]" combineOutputs="false">
 
<!-- Integer between 2 and 20 -->
 
<!-- Integer between 2 and 20 -->
 
<Option key="neighbourhoodSize" value="2"/>
 
<Option key="neighbourhoodSize" value="2"/>
  +
<!-- Number of frequency values returned for each submitted sample. Only used with auto-sampled inputs. -->
</[[Config:SampleSelector|SampleSelector]]>
 
  +
<Option key="frequencies" value="11"/>
</source>
 
=== autoSampling ===
 
A wrapper around another sample selector that filters out the auto-sampled dimensions. This is useful if one or more inputs are sampled automatically by the simulator.
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#AutoSamplingSampleSelector|AutoSamplingSampleSelector]]" combineOutputs="false">
 
 
<!-- The filter function to use. Default = max. -->
 
<Option key="function" value="max"/>
 
 
<!-- The sample selector to use for non-auto sampled dimensions. -->
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLASampleSelector|LOLASampleSelector]]" combineOutputs="false">
 
<Option key="neighbourhoodSize" value="2"/>
 
</[[Config:SampleSelector|SampleSelector]]>
 
 
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</source>
 
</source>
 
=== rationalPoleSupression ===
 
=== rationalPoleSupression ===
A sampling algorithm aimed at supressing poles by sampling them (only for Rational models)
+
A sampling algorithm aimed at supressing poles in rational models by sampling them (only for Rational models)
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
<!-- A criterion determines the interesting regions to sample -->
 
<!-- Choose 1 from the following: -->
 
<Option key="criterion" value="rationalPoleSupression"/> <!-- supresses poles in a rational model by sampling at those locations -->
 
   
 
<!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
 
<!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
<[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
+
<[[Config:Optimizer|Optimizer]]>patternsearch</[[Config:Optimizer|Optimizer]]>
  +
<Option key="maxevals" value="1000"/>
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#rationalPoleSupression|rationalPoleSupression]]" scaling="none"/>
<Option key="maxits" value="300"/>
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#modelDifference|modelDifference]]" scaling="none"/>
</[[Config:Optimizer|Optimizer]]>
 
   
 
<!--
 
<!--
Line 104: Line 88:
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
<!-- A criterion determines the interesting regions to sample -->
 
<!-- Choose 1 from the following: -->
 
<Option key="criterion" value="gExpectedImprovement"/> <!-- generalized expected improvement -->
 
<Option key="criterion_opts" value="1"/> <!-- balanced local-global search -->
 
   
 
<!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
 
<!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
<[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
+
<[[Config:Optimizer|Optimizer]]>patternsearch</[[Config:Optimizer|Optimizer]]>
  +
<Option key="maxevals" value="1000"/>
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#expectedImprovement|expectedImprovement]]" scaling="none">
<Option key="maxits" value="300"/>
 
</[[Config:Optimizer|Optimizer]]>
+
</[[Config:CandidateRanker|CandidateRanker]]>
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#maxvar|maxvar]]" scaling="none"/>
   
 
<!--
 
<!--
Line 123: Line 104:
 
</source>
 
</source>
 
=== extremaLOLA ===
 
=== extremaLOLA ===
LOLA sample selector supplemented with 1 sample at the minimum and maximum
+
LOLA-Voronoi sample selector supplemented with 1 sample at the minimum and maximum
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
 
<!-- A highly adaptive sampling algorithm, error and density based -->
 
<!-- A highly adaptive sampling algorithm, error and density based -->
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLASampleSelector|LOLASampleSelector]]" combineOutputs="false">
+
<[[Config:SampleSelector|SampleSelector]] weight="0.8">lola-voronoi</[[Config:SampleSelector|SampleSelector]]>
  +
<[[Config:SampleSelector|SampleSelector]] weight="0.1">sampleMinimum</[[Config:SampleSelector|SampleSelector]]>
<!-- Integer between 2 and 20 -->
 
  +
<[[Config:SampleSelector|SampleSelector]] weight="0.1">sampleMaximum</[[Config:SampleSelector|SampleSelector]]>
<Option key="neighbourhoodSize" value="2"/>
 
  +
</[[Config:SampleSelector|SampleSelector]]>
 
  +
<[[Config:MergeCriterion|MergeCriterion]] type="[[MergeCriterion#ClosenessThreshold|ClosenessThreshold]]">
 
  +
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
 
  +
<!-- Closeness threshold, Double -->
<Option key="criterion" value="minmodel"/> <!-- generalized expected improvement -->
 
  +
<Option key="closenessThreshold" value="0.05"/>
 
<!-- Use the following optimization method. -->
+
<!-- Set a % of the maximumSamples to randomly chosen -->
  +
<Option key="randomPercentage" value="0"/>
<[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
 
  +
<Option key="maxevals" value="1000"/>
 
<Option key="maxits" value="300"/>
 
</[[Config:Optimizer|Optimizer]]>
 
 
 
<Option key="debug" value="off"/>
 
<Option key="debug" value="off"/>
</[[Config:SampleSelector|SampleSelector]]>
+
</[[Config:MergeCriterion|MergeCriterion]]>
  +
</[[Config:SampleSelector|SampleSelector]]>
 
  +
</source>
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
 
  +
=== sampleMinimum ===
<Option key="criterion" value="maxmodel"/> <!-- generalized expected improvement -->
 
  +
Selects one sample at the minimum of the model.
 
  +
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
<!-- Use the following optimization method. -->
 
<[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
  +
<[[Config:Optimizer|Optimizer]]>patternsearch</[[Config:Optimizer|Optimizer]]>
<Option key="maxevals" value="1000"/>
 
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#minmodel|minmodel]]" scaling="none"/>
<Option key="maxits" value="300"/>
 
</[[Config:Optimizer|Optimizer]]>
+
</[[Config:SampleSelector|SampleSelector]]>
  +
</source>
 
  +
=== sampleMaximum ===
<Option key="debug" value="off"/>
 
  +
Selects one sample at the maximum of the model.
</[[Config:SampleSelector|SampleSelector]]>
 
  +
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
  +
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
  +
<[[Config:Optimizer|Optimizer]]>patternsearch</[[Config:Optimizer|Optimizer]]>
  +
<[[Config:CandidateRanker|CandidateRanker]] type="[[CandidateRanker#maxmodel|maxmodel]]" scaling="none"/>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</source>
 
</source>
 
=== default ===
 
=== default ===
LOLA sample selector combined with error based sample selector (default)
+
LOLA sample selector combined with error based sample selector
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
  +
<[[Config:SampleSelector|SampleSelector]] weight="0.7">lola-voronoi</[[Config:SampleSelector|SampleSelector]]>
<!-- A highly adaptive sampling algorithm, error and density based -->
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLASampleSelector|LOLASampleSelector]]" combineOutputs="false">
+
<[[Config:SampleSelector|SampleSelector]] weight="0.3">error</[[Config:SampleSelector|SampleSelector]]>
  +
<!-- Integer between 2 and 20 -->
 
  +
<[[Config:MergeCriterion|MergeCriterion]] type="[[MergeCriterion#ClosenessThreshold|ClosenessThreshold]]">
<Option key="neighbourhoodSize" value="2"/>
 
</[[Config:SampleSelector|SampleSelector]]>
 
 
<!-- An adaptive sample selection algorithm (error based), driven by the evaluation of your model on a dense grid -->
 
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#ErrorSampleSelector|ErrorSampleSelector]]" combineOutputs="false">
 
<!-- Integer between 2 and 20 -->
 
<Option key="nLastModels" value="4"/>
 
<!-- One of none, max, cap, capmax -->
 
<Option key="differenceScaling" value="none"/>
 
<!-- Gridsize to evaluate on, one of int or array of dimension length -->
 
<Option key="gridSize" value="50"/>
 
<!-- Maximum total points to evaluate, distributed over dimensions -->
 
<Option key="maxGridSize" value="100000"/>
 
 
<!-- Closeness threshold, Double -->
 
<!-- Closeness threshold, Double -->
<Option key="closenessThreshold" value="0.2"/>
+
<Option key="closenessThreshold" value="0.05"/>
 
<!-- Set a % of the maximumSamples to randomly chosen -->
 
<!-- Set a % of the maximumSamples to randomly chosen -->
 
<Option key="randomPercentage" value="0"/>
 
<Option key="randomPercentage" value="0"/>
  +
</[[Config:SampleSelector|SampleSelector]]>
 
  +
<Option key="debug" value="off"/>
  +
</[[Config:MergeCriterion|MergeCriterion]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</source>
 
</source>

Latest revision as of 17:23, 27 February 2014

Generated for SUMO toolbox version 7.0. We are well aware that documentation is not always complete and possibly even out of date in some cases. We try to document everything as best we can but much is limited by available time and manpower. We are are a university research group after all. The most up to date documentation can always be found (if not here) in the default.xml configuration file and, of course, in the source files. If something is unclear please dont hesitate to ask.

SampleSelector

empty

Don't select any new samples, useful when modeling multiple outputs, and you don't want to involve one of these outputs in the sampling process.

<SampleSelector type="EmptySampleSelector" combineOutputs="false"/>

random

Selects new samples randomly in the design space.

<SampleSelector type="RandomSampleSelector" combineOutputs="false"/>

delaunay

This sample selector uses a Delaunay triangulation of the data to select samples in locations far from previous samples, or in locations where the estimated model error is largest. This algorithm uses QHull, which is very slow for high dimensions, so you should only use this sample selector for less than 6D and for less than 1000 samples.

<SampleSelector type="PipelineSampleSelector" combineOutputs="false">
 
   <CandidateGenerator type="DelaunayCandidateGenerator"/>
 
        <CandidateRanker type="modelDifference">
           <Option key="criterion_parameter" value="2"/>
        </CandidateRanker>
        <CandidateRanker type="delaunayVolume"/>
 
        <MergeCriterion type="WeightedAverage" weights="[1 1]"/>
 
</SampleSelector>

density

A space-filling sampling algorithm which uses an approximation of the Voronoi tessellation of the design space. Will only sample within the "allowed" areas if constraints are specified.

<SampleSelector type="VoronoiSampleRanker" combineOutputs="false"/>

error

An adaptive sample selection algorithm (error based), driven by the evaluation of your model on a dense grid, which selects samples in locations where the model error is estimated to be the largest.

<SampleSelector type="PipelineSampleSelector" combineOutputs="false">
 
   <CandidateGenerator type="GridCandidateGenerator"/>
 
   <CandidateRanker type="modelDifference">
           <Option key="criterion_parameter" value="4"/>
        </CandidateRanker>
 
        <MergeCriterion type="ClosenessThreshold">
 
      <!-- Closeness threshold, Double -->
      <Option key="closenessThreshold" value="0.05"/>
      <!-- Set a % of the maximumSamples to randomly chosen -->
      <Option key="randomPercentage" value="20"/>
 
      <Option key="debug" value="off"/>
   </MergeCriterion>
</SampleSelector>

lola-voronoi

A highly adaptive sampling algorithm which performs a trade-off between exploration (filling up the design space as equally as possible) and exploitation (selecting data points in highly nonlinear regions). lola-voronoi is the only sample selector which currently supports multiple outputs, auto-sampled inputs and constraints.

<SampleSelector type="LOLAVoronoiSampleSelector" combineOutputs="false">
   <!-- Integer between 2 and 20 -->
   <Option key="neighbourhoodSize" value="2"/>
   <!-- Number of frequency values returned for each submitted sample. Only used with auto-sampled inputs. -->
   <Option key="frequencies" value="11"/>
</SampleSelector>

rationalPoleSupression

A sampling algorithm aimed at supressing poles in rational models by sampling them (only for Rational models)

<SampleSelector type="OptimizeCriterion" combineOutputs="false">
 
   <!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
   <Optimizer>patternsearch</Optimizer>
 
   <CandidateRanker type="rationalPoleSupression" scaling="none"/>
   <CandidateRanker type="modelDifference" scaling="none"/>
 
   <!--
   when debug is 'on' a contour plot of the criterion function is drawn every iteration.
   Together with the current samples and the chosen samples
   -->
   <Option key="debug" value="off"/>
</SampleSelector>

expectedImprovement

A sampling algorithm aimed at optimization problems (only for Kriging and RBF)

<SampleSelector type="OptimizeCriterion" combineOutputs="false">
 
   <!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
   <Optimizer>patternsearch</Optimizer>
 
   <CandidateRanker type="expectedImprovement" scaling="none">
   </CandidateRanker>
   <CandidateRanker type="maxvar" scaling="none"/>
 
   <!--
   when debug is 'on' a contour plot of the criterion function is drawn every iteration.
   Together with the current samples and the chosen samples
   -->
   <Option key="debug" value="off"/>
</SampleSelector>

extremaLOLA

LOLA-Voronoi sample selector supplemented with 1 sample at the minimum and maximum

<SampleSelector type="CombinedSampleSelector" combineOutputs="false">
   <!-- A highly adaptive sampling algorithm, error and density based -->
   <SampleSelector weight="0.8">lola-voronoi</SampleSelector>
   <SampleSelector weight="0.1">sampleMinimum</SampleSelector>
   <SampleSelector weight="0.1">sampleMaximum</SampleSelector>
 
   <MergeCriterion type="ClosenessThreshold">
 
      <!-- Closeness threshold, Double -->
      <Option key="closenessThreshold" value="0.05"/>
      <!-- Set a % of the maximumSamples to randomly chosen -->
      <Option key="randomPercentage" value="0"/>
 
      <Option key="debug" value="off"/>
   </MergeCriterion>
</SampleSelector>

sampleMinimum

Selects one sample at the minimum of the model.

<SampleSelector type="OptimizeCriterion" combineOutputs="false">
   <Optimizer>patternsearch</Optimizer>
   <CandidateRanker type="minmodel" scaling="none"/>
</SampleSelector>

sampleMaximum

Selects one sample at the maximum of the model.

<SampleSelector type="OptimizeCriterion" combineOutputs="false">
   <Optimizer>patternsearch</Optimizer>
   <CandidateRanker type="maxmodel" scaling="none"/>
</SampleSelector>

default

LOLA sample selector combined with error based sample selector

<SampleSelector type="CombinedSampleSelector" combineOutputs="false">
   <SampleSelector weight="0.7">lola-voronoi</SampleSelector>
   <SampleSelector weight="0.3">error</SampleSelector>
 
   <MergeCriterion type="ClosenessThreshold">   
      <!-- Closeness threshold, Double -->
      <Option key="closenessThreshold" value="0.05"/>
      <!-- Set a % of the maximumSamples to randomly chosen -->
      <Option key="randomPercentage" value="0"/>
 
      <Option key="debug" value="off"/>
   </MergeCriterion>
</SampleSelector>