Config:SequentialDesign

This wiki page is based on version 6.2 of the SUMO Toolbox.

We are well aware that documentation is not always complete and possibly even out of date in some cases.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

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"/>

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]]>

lola

A highly adaptive sampling algorithm, error and density based

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

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.

<[[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]]>

rationalPoleSupression

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

<[[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 -->
   <[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
      <Option key="maxevals" value="1000"/>
      <Option key="maxits" value="300"/>
   </[[Config:Optimizer|Optimizer]]>

   <!--
   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"/>
</[[Config:SampleSelector|SampleSelector]]>

expectedImprovement

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

<[[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 -->
   <[[Config:Optimizer|Optimizer]] type="[[Optimizer#DirectOptimizer|DirectOptimizer]]">
      <Option key="maxevals" value="1000"/>
      <Option key="maxits" value="300"/>
   </[[Config:Optimizer|Optimizer]]>

   <!--
   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"/>
</[[Config:SampleSelector|SampleSelector]]>

extremaLOLA

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

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
   <!-- A highly adaptive sampling algorithm, error and density based -->
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLASampleSelector|LOLASampleSelector]]" combineOutputs="false">
      <!-- Integer between 2 and 20 -->
      <Option key="neighbourhoodSize" value="2"/>
   </[[Config:SampleSelector|SampleSelector]]>

   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
      <Option key="criterion" value="minmodel"/> <!-- generalized expected improvement -->

      <!-- Use the following optimization method. -->
      <[[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"/>
   </[[Config:SampleSelector|SampleSelector]]>

   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#OptimizeCriterion|OptimizeCriterion]]" combineOutputs="false">
      <Option key="criterion" value="maxmodel"/> <!-- generalized expected improvement -->

      <!-- Use the following optimization method. -->
      <[[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"/>
   </[[Config:SampleSelector|SampleSelector]]>

</[[Config:SampleSelector|SampleSelector]]>

default

LOLA sample selector combined with error based sample selector (default)

<[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#CombinedSampleSelector|CombinedSampleSelector]]" combineOutputs="false">
   <!-- A highly adaptive sampling algorithm, error and density based -->
   <[[Config:SampleSelector|SampleSelector]] type="[[SampleSelector#LOLASampleSelector|LOLASampleSelector]]" combineOutputs="false">
      <!-- Integer between 2 and 20 -->
      <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 -->
      <Option key="closenessThreshold" value="0.2"/>
      <!-- Set a % of the maximumSamples to randomly chosen -->
      <Option key="randomPercentage" value="0"/>
   </[[Config:SampleSelector|SampleSelector]]>
</[[Config:SampleSelector|SampleSelector]]>