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The SUMO configuration section allows you to configure the general settings of the SUMO Toolbox. Here you can for example set stop conditions of the modelling loop such as the maximum number of samples or maximum elapsed time.

This configuration section also allows you to adjust the way the toolbox handles the evaluation of samples. In general the SUMO Toolbox will determine the number of samples which will be evaluated prior to a modelling iteration based on the number of already available samples, the number of pending samples (which are selected by the sample selector but are not yet evaluated) and the number of available computation nodes. You can change this by for example choosing the maximum and minimum number of samples that the sample selector can pick. And by setting the the minimumAdaptiveSamples option you can choose the fraction of the selected samples that have to be evaluated before starting a new modelling iteration. This is handy if the evaluation of a sample takes a lot of time.

When modelling more than one output using an output-based sample selectors, the total number of allocated samples will be distributed evenly over the outputs.

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 We are well aware that documentation is not always complete and possibly even out of date in some cases.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


Custom Options

Available options:

<!--Should a movie be created of the model plots when the toolbox has terminated-->
   <Option key="createMovie" value="yes"/>
<!--The minimum amount of samples alotted to *EACH RUN*, dont stop untill we have at least this many samples-->
   <Option key="minimumTotalSamples" value="0"/>
<!--The maximum amount of samples alotted to *EACH RUN*, stop the run and proceed to the next if this number of samples is exceeded (set to Inf to disable)-->
   <Option key="maximumTotalSamples" value="1000"/>
<!--The amount of time (in minutes) alotted to *EACH RUN*, stop the run and proceed to the next if this number is exceeded (set to Inf to disable)-->
   <Option key="maximumTime" value="Inf"/>
<!--The maximum number of adaptive modeling iterations alotted to *EACH RUN*, stop the run and proceed to the next if this number is exceeded (set to Inf to disable).-->
   <Option key="maxModelingIterations" value="Inf"/>
<!--How should the random number generator files be seeded, 3 options: - default: do nothing, the same seed will be used each time matlab is started - random: random initial state - file: load the state from the file specified by the randomStateFile option-->
   <Option key="seedRandomState" value="default"/>
<!--Stop the main loop if a fatal error occurs in the sample evaluator, if set to false the toolbox will switch to adaptive modeling mode (further sampling is switched off).-->
   <Option key="stopOnError" value="true"/>
<!--Minimum amount of samples that are to be evaluated from the initial sample set before the modeling process starts. This can either be an absolute number (e.g., 23) or a percentage (e.g., 95%)-->
   <Option key="minimumInitialSamples" value="100%"/>
<!--Maximum number of pending samples allowed at any time in the toolbox.-->
   <Option key="maximumSamples" value="10"/>
<!--How many % samples should be at least retrieved every iteration (relative to the number of selected samples): 0 %: just takes what is finished and continue modeling 100 %: wait until all selected samples have been evaluated-->
   <Option key="minimumAdaptiveSamples" value="0"/>
<!--Must samples be checked against the constraints before they are submitted for evaluation?-->
   <Option key="newSamplesMustSatisfyConstraints" value="yes"/>
<!--Must the entire dataset be used in adaptive modeling mode or not? true: only the initial design is evaluated, and is used in adaptive modeling mode false: the entire dataset is loaded immediately and used in adaptive modeling mode-->
   <Option key="adaptiveModelingInitialDesignOnly" value="no"/>