Difference between revisions of "Config:SequentialDesign"

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== SampleSelector ==
 
== SampleSelector ==
−
+
 
 
=== empty ===
 
=== empty ===
 
Dont select any new samples, useful when modeling multiple outputs in paralel
 
Dont select any new samples, useful when modeling multiple outputs in paralel
−
<source 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
 
Each sampling iterations new samples are selected randomly
−
<source 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>
 
=== combo ===
 
=== combo ===
 
Allows you combine multiple sample selector algorithms
 
Allows you combine multiple sample selector algorithms
−
<source 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]] type="[[SampleSelector#RationalPoleSuppressionSampleSelector|RationalPoleSuppressionSampleSelector]]" combineOutputs="false"><!-- Currently no options are available, if the model is a rational model, and a
+
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#RationalPoleSuppressionSampleSelector|RationalPoleSuppressionSampleSelector]]" combineOutputs="false">
−
- - pole is found (using a simple search strategy), the pole is returned --></[[Config:SampleSelector|SampleSelector]]>
+
      <!-- Currently no options are available, if the model is a rational model, and a
−
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false"><!-- One of all, data -->
+
      - - pole is found (using a simple search strategy), the pole is returned -->
−
       <Option key="sampleSelect" value="all"/><!-- Integer between 2 and 20 -->
+
  </[[Config:SampleSelector|SampleSelector]]>
−
       <Option key="nLastModels" value="2"/><!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
+
 
−
       <Option key="scoreFunction" value="weightedLinear"/><!-- Weighting for weightedLinear -->
+
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false">
−
       <Option key="lambda" value="0.5"/><!-- Weighting for weightedGeometric -->
+
      <!-- One of all, data -->
−
       <Option key="mu" value="0.5"/><!-- One of none, max, cap, capmax -->
+
       <Option key="sampleSelect" value="all"/>
 +
      <!-- Integer between 2 and 20 -->
 +
       <Option key="nLastModels" value="2"/>
 +
      <!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
 +
       <Option key="scoreFunction" value="weightedLinear"/>
 +
      <!-- Weighting for weightedLinear -->
 +
       <Option key="lambda" value="0.5"/>
 +
      <!-- Weighting for weightedGeometric -->
 +
       <Option key="mu" value="0.5"/>
 +
      <!-- One of none, max, cap, capmax -->
 
       <Option key="volumeScaling" value="max"/>
 
       <Option key="volumeScaling" value="max"/>
−
       <Option key="differenceScaling" value="capmax"/><!-- Boolean flag, if set all points closer than snapThreshold to the boundary of  
+
       <Option key="differenceScaling" value="capmax"/>
−
- - the domain are clipped to the boundary -->
+
      <!-- Boolean flag, if set all points closer than snapThreshold to the boundary of  
 +
      - - the domain are clipped to the boundary -->
 
       <Option key="snapToEdge" value="enable"/>
 
       <Option key="snapToEdge" value="enable"/>
 
       <Option key="snapThreshold" value=".05"/>
 
       <Option key="snapThreshold" value=".05"/>
Line 33: Line 43:
 
=== delaunay ===
 
=== delaunay ===
 
An adaptive sample selection algorithm that does a trade-off between error and density
 
An adaptive sample selection algorithm that does a trade-off between error and density
−
<source lang="xml">
+
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
−
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false"><!-- One of all, data -->
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false">
−
   <Option key="sampleSelect" value="all"/><!-- Integer between 2 and 20 -->
+
  <!-- One of all, data -->
−
   <Option key="nLastModels" value="2"/><!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
+
   <Option key="sampleSelect" value="all"/>
 +
  <!-- Integer between 2 and 20 -->
 +
   <Option key="nLastModels" value="2"/>    
 +
  <!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
 
   <Option key="scoreFunction" value="weightedLinear"/>
 
   <Option key="scoreFunction" value="weightedLinear"/>
 
   <Option key="lambda" value="0.5"/>
 
   <Option key="lambda" value="0.5"/>
−
   <Option key="mu" value="0.5"/><!-- One of none, max, cap, capmax -->
+
   <Option key="mu" value="0.5"/>
 +
  <!-- One of none, max, cap, capmax -->
 
   <Option key="volumeScaling" value="max"/>
 
   <Option key="volumeScaling" value="max"/>
−
   <Option key="differenceScaling" value="capmax"/><!-- Boolean flag -->
+
   <Option key="differenceScaling" value="capmax"/>
 +
  <!-- Boolean flag -->
 
   <Option key="snapToEdge" value="enable"/>
 
   <Option key="snapToEdge" value="enable"/>
 
   <Option key="snapThreshold" value=".2"/>
 
   <Option key="snapThreshold" value=".2"/>
Line 48: Line 63:
 
=== density ===
 
=== density ===
 
A simple density based sample selection algorithm
 
A simple density based sample selection algorithm
−
<source 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#DensitySampleSelector|DensitySampleSelector]]" 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
−
<source lang="xml">
+
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
−
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#ErrorSampleSelector|ErrorSampleSelector]]" combineOutputs="false"><!-- Integer between 2 and 20 -->
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#ErrorSampleSelector|ErrorSampleSelector]]" combineOutputs="false">
−
   <Option key="nLastModels" value="4"/><!-- One of none, max, cap, capmax -->
+
  <!-- Integer between 2 and 20 -->
−
   <Option key="differenceScaling" value="none"/><!-- Gridsize to evaluate on, one of int or array of dimension length -->
+
   <Option key="nLastModels" value="4"/>    
−
   <Option key="gridSize" value="50"/><!-- Maximum total points to evaluate, distributed over dimensions -->
+
  <!-- One of none, max, cap, capmax -->
−
   <Option key="maxGridSize" value="100000"/><!-- Closeness threshold, Double -->
+
   <Option key="differenceScaling" value="none"/>
−
   <Option key="closenessThreshold" value="0.2"/><!-- Set a % of the maximumSamples to randomly chosen -->
+
  <!-- 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 -->
 +
   <Option key="closenessThreshold" value="0.2"/>
 +
  <!-- Set a % of the maximumSamples to randomly chosen -->
 
   <Option key="randomPercentage" value="20"/>
 
   <Option key="randomPercentage" value="20"/>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
Line 65: Line 86:
 
=== gradient ===
 
=== gradient ===
 
A highly adaptive sampling algorithm, error and density based
 
A highly adaptive sampling algorithm, error and density based
−
<source lang="xml">
+
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
−
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#GradientSampleSelector|GradientSampleSelector]]" combineOutputs="false"><!-- Integer between 2 and 20 -->
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#GradientSampleSelector|GradientSampleSelector]]" combineOutputs="false">
 +
  <!-- Integer between 2 and 20 -->
 
   <Option key="neighbourhoodSize" value="2"/>
 
   <Option key="neighbourhoodSize" value="2"/>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
Line 72: Line 94:
 
=== isc ===
 
=== isc ===
 
A sampling algorithm aimed at optimization problems
 
A sampling algorithm aimed at optimization problems
−
<source lang="xml">
+
<source xmlns:saxon="http://icl.com/saxon" lang="xml">
−
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#InfillSamplingCriterion|InfillSamplingCriterion]]" combineOutputs="false"><!-- A criterion determines the interesting regions to sample --><!-- Choose 1 from the following: -->
+
<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#InfillSamplingCriterion|InfillSamplingCriterion]]" combineOutputs="false">
−
   <Option key="criterion" value="gei"/><!-- generalized expected improvement -->
+
  <!-- A criterion determines the interesting regions to sample -->
−
   <Option key="g" value="1"/><!-- balanced local-global search --><!--<Option key="criterion" value="wei" />--><!-- weighted expected improvement --><!--<Option key="w" value="0.5" />--><!-- weight, 0 is global search, 1 is local search --><!--<Option key="criterion" value="ei" />--><!-- expected improvement --><!--<Option key="criterion" value="kushner" />--><!-- kushner --><!--<Option key="eps" value="0.001" />--><!--<Option key="criterion" value="lcb" />--><!-- lower confidence bound function --><!--<Option key="lcb" value="2.0" />--><!--<Option key="criterion" value="maxvar" />--><!-- maximizes variation --><!-- Watson and Barnes criterions --><!--<Option key="criterion" value="wb1" />--><!-- threshold-bounded extreme --><!--<Option key="criterion" value="wb2" />--><!-- regional extreme --><!--<Option key="criterion" value="crowdedness" />--><!-- crowdedness function --><!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
+
  <!-- Choose 1 from the following: -->
 +
   <Option key="criterion" value="gei"/> <!-- generalized expected improvement -->
 +
   <Option key="g" value="1"/> <!-- balanced local-global search -->
 +
 
 +
  <!--<Option key="criterion" value="wei" />--> <!-- weighted expected improvement -->
 +
  <!--<Option key="w" value="0.5" />--> <!-- weight, 0 is global search, 1 is local search -->
 +
 
 +
  <!--<Option key="criterion" value="ei" />--> <!-- expected improvement -->
 +
 
 +
  <!--<Option key="criterion" value="kushner" />--> <!-- kushner -->
 +
  <!--<Option key="eps" value="0.001" />-->
 +
 
 +
  <!--<Option key="criterion" value="lcb" />--> <!-- lower confidence bound function -->
 +
  <!--<Option key="lcb" value="2.0" />-->
 +
  <!--<Option key="criterion" value="maxvar" />--> <!-- maximizes variation -->
 +
 
 +
  <!-- Watson and Barnes criterions -->
 +
  <!--<Option key="criterion" value="wb1" />--> <!-- threshold-bounded extreme -->
 +
  <!--<Option key="criterion" value="wb2" />--> <!-- regional extreme -->
 +
 
 +
  <!--<Option key="criterion" value="crowdedness" />--> <!-- crowdedness function -->
 +
 
 +
  <!-- 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]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
 
       <Option key="maxevals" value="1000"/>
 
       <Option key="maxevals" value="1000"/>
 
       <Option key="maxits" value="300"/>
 
       <Option key="maxits" value="300"/>
−
   </[[Config:Optimizer|Optimizer]]><!--
+
   </[[Config:Optimizer|Optimizer]]>
−
<[[Config:Optimizer|Optimizer]] type="[[Optimizer#MatlabGA|MatlabGA]]">
+
 
−
    </[[Config:Optimizer|Optimizer]]>
+
  <!--
−
--><!-- when debug is 'on' a contour plot of the ISC function is drawn every iteration. --><!-- Together with the current samples and the chosen samples -->
+
  <[[Config:Optimizer|Optimizer]] type="[[Optimizer#MatlabGA|MatlabGA]]">
−
   <Option key="debug" value="off"/>
+
  </[[Config:Optimizer|Optimizer]]>
 +
  -->
 +
 
 +
  <!--
 +
  when debug is 'on' a contour plot of the ISC function is drawn every iteration.
 +
  Together with the current samples and the chosen samples
 +
  -->
 +
   <Option key="debug" value="on"/>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</[[Config:SampleSelector|SampleSelector]]>
 
</source>
 
</source>

Revision as of 13:56, 13 February 2008

SampleSelector

empty

Dont select any new samples, useful when modeling multiple outputs in paralel 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#EmptySampleSelector|EmptySampleSelector]]" combineOutputs="false"/>

random

Each sampling iterations new samples are selected randomly 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#RandomSampleSelector|RandomSampleSelector]]" combineOutputs="false"/>

combo

Allows you combine multiple sample selector algorithms 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#RationalPoleSuppressionSampleSelector|RationalPoleSuppressionSampleSelector]]" combineOutputs="false">
      <!-- Currently no options are available, if the model is a rational model, and a
       - - pole is found (using a simple search strategy), the pole is returned -->
   </[[Config:SampleSelector|SampleSelector]]>
   
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false">
      <!-- One of all, data -->
      <Option key="sampleSelect" value="all"/>
      <!-- Integer between 2 and 20 -->
      <Option key="nLastModels" value="2"/>
      <!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
      <Option key="scoreFunction" value="weightedLinear"/>
      <!-- Weighting for weightedLinear -->
      <Option key="lambda" value="0.5"/>
      <!-- Weighting for weightedGeometric -->
      <Option key="mu" value="0.5"/>
      <!-- One of none, max, cap, capmax -->
      <Option key="volumeScaling" value="max"/>
      <Option key="differenceScaling" value="capmax"/>
      <!-- Boolean flag, if set all points closer than snapThreshold to the boundary of 
       - - the domain are clipped to the boundary -->
      <Option key="snapToEdge" value="enable"/>
      <Option key="snapThreshold" value=".05"/>
   </[[Config:SampleSelector|SampleSelector]]>
</[[Config:SampleSelector|SampleSelector]]>

delaunay

An adaptive sample selection algorithm that does a trade-off between error and density 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DelaunaySampleSelector|DelaunaySampleSelector]]" combineOutputs="false">
   <!-- One of all, data -->
   <Option key="sampleSelect" value="all"/>
   <!-- Integer between 2 and 20 -->
   <Option key="nLastModels" value="2"/>      
   <!-- One of densityBased, differenceBased, weightedLinear, weightedGeometric -->
   <Option key="scoreFunction" value="weightedLinear"/>
   <Option key="lambda" value="0.5"/>
   <Option key="mu" value="0.5"/>
   <!-- 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]]>

density

A simple density based sample selection algorithm 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#DensitySampleSelector|DensitySampleSelector]]" combineOutputs="false"/>

error

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 -->
   <Option key="closenessThreshold" value="0.2"/>
   <!-- Set a % of the maximumSamples to randomly chosen -->
   <Option key="randomPercentage" value="20"/>
</[[Config:SampleSelector|SampleSelector]]>

gradient

A highly adaptive sampling algorithm, error and density based 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#GradientSampleSelector|GradientSampleSelector]]" combineOutputs="false">
   <!-- Integer between 2 and 20 -->
   <Option key="neighbourhoodSize" value="2"/>
</[[Config:SampleSelector|SampleSelector]]>

isc

A sampling algorithm aimed at optimization problems 

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#InfillSamplingCriterion|InfillSamplingCriterion]]" combineOutputs="false">
   <!-- A criterion determines the interesting regions to sample -->
   <!-- Choose 1 from the following: -->
   <Option key="criterion" value="gei"/> <!-- generalized expected improvement -->
   <Option key="g" value="1"/> <!-- balanced local-global search -->

   <!--<Option key="criterion" value="wei" />--> <!-- weighted expected improvement -->
   <!--<Option key="w" value="0.5" />--> <!-- weight, 0 is global search, 1 is local search -->

   <!--<Option key="criterion" value="ei" />--> <!-- expected improvement -->
   
   <!--<Option key="criterion" value="kushner" />--> <!-- kushner -->
   <!--<Option key="eps" value="0.001" />-->
   
   <!--<Option key="criterion" value="lcb" />--> <!-- lower confidence bound function -->
   <!--<Option key="lcb" value="2.0" />-->
   <!--<Option key="criterion" value="maxvar" />--> <!-- maximizes variation -->

   <!-- Watson and Barnes criterions -->
   <!--<Option key="criterion" value="wb1" />--> <!-- threshold-bounded extreme -->
   <!--<Option key="criterion" value="wb2" />--> <!-- regional extreme -->

   <!--<Option key="criterion" value="crowdedness" />--> <!-- crowdedness function -->

   <!-- This criterion has to be solved to choose new samples, one can choose the optimizer used here -->
   <[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
      <Option key="maxevals" value="1000"/>
      <Option key="maxits" value="300"/>
   </[[Config:Optimizer|Optimizer]]>

   <!--
   <[[Config:Optimizer|Optimizer]] type="[[Optimizer#MatlabGA|MatlabGA]]">
   </[[Config:Optimizer|Optimizer]]>
   -->

   <!--
   when debug is 'on' a contour plot of the ISC function is drawn every iteration.
   Together with the current samples and the chosen samples
   -->
   <Option key="debug" value="on"/>
</[[Config:SampleSelector|SampleSelector]]>
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