Config:SequentialDesign

From SUMOwiki
Revision as of 10:16, 8 February 2008 by Icouckuy (talk | contribs)
Jump to navigationJump to search
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

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="off"/>
</[[Config:SampleSelector|SampleSelector]]>