From SUMOwiki
Revision as of 11:55, 16 January 2009 by Kcrombec (talk | contribs)

Latin Hypercube Design

Choose an initial sampleset in such a way that they form a latin hypercube.

option values default
points positive integer 30
The amount of samples that will be taken.

Dataset Design

Reads an initial design from a dataset. Each row should contain one sample. The inputvalues come first. The outputvalues, if there are any, come second.

If only input values are supplied (hasOutputs=false), each value has to be in the fixed [-1,1] range (model space). The samples are later automatically transformed to their original range before they are passed to the sample evaluator. This is done to easily support different ranges for variables without having to change the initial dataset design.

If, however, output values are also provided (hasOutputs=true), the samples are instantly fed to the toolbox for modelling, since they don't have to be evaluated anymore. Because of this property, the inputs have to be in the original range defined in the simulator xml file, instead of the fixed [-1,1] range.

option values default
filename path none
Path of the file that contains the dataset. This option is required!
hasOutputs boolean true
Does the datasetfile contain evaluated samples or just sample locations?

Combined Design

Combines two other initial designs.

node required?
InitialDesign one or more
Configuration for each InitialDesign Method.

Factorial Design

Choose an initial sampleset in such a way that they form an uniform grid

option values default
levels vector of positive integers > 1 [5,...,5]
vector specifying for each dimension the number of samples. Sampling level1*level2*...*leveln points. If a scalar s is specified, The toolbox assumes [s s ... s].