Description Class Hierarchy Constructor Slots Methods Author(s) References Examples
The class mtkExperiment
is a sub-class of the class mtkExpWorkflow
. It provides more facilities and more flexible use for interactive manipulation of the workflow.
Different behaviors may be expected by appropriately combining the parameters: design
– the method used for the experiment design; model
– the model used for the simulation;
analyze
– the method used for calculating the sensitivity index; XY
– argument used to provide with data produced off-line;
For example, 1) if the experiment design is produced off-line, it will be imported with the help of the parameter "XY$X" ; 2) if the model simulation is produced off-line, it will be imported through the parameter "XY$Y";
mtkExpWorkflow
mtkExperiment
signature(expFactors, design=NULL, designInfo=NULL, model=NULL, modelInfo=NULL, analyze=NULL, analyzeInfo=NULL, XY=NULL)
expFactors
:(mtkExpFactors
) an object of the mtkExpFactors
class.
processesVector
:(vector
) a vector of objects from the class mtkProcess
or its sub-classes.
addProcess
signature(this = "mtkExperiment", p = "mtkProcess", name = "character"): Adds a process to the workflow.
deleteProcess
signature(this = "mtkExperiment", name = "character"): Deletes a process from the workflow.
setProcess
signature(this = "mtkExperiment", p = "mtkProcess", name = "character"): Replaces a process into the workflow.
getProcess
signature(this = "mtkExperiment", name = "character"): Gets a process from the workflow.
extractData
signature(this = "mtkExperiment", name = "list"): Returns the results produced by the workflow as a data.frame. According to the processes specified with the argument "name", we can fetch the results produced by the process "design", "evaluate" or "analyze". i.e. name=c("design") gives the experimental design produced by the process "design" and name=c("design","evaluate") gives both the experimental design and the model simulation, etc.
reevaluate
signature(this = "mtkExperiment", name = "character"): Re-evaluate the processes of the workflow to know if they should be re-run. This should be done after changing a process of the workflow. According to the order "design", evaluate", "analyze", only the processes after the one given by the argument "name" will be re-evaluated.
run
signature(this = "mtkExperiment", context= "missing"): Runs the ExpWorkflow.
serializeOn
signature(this = "mtkExperiment"): Returns all data managed by the workflow as a named list.
summary
signature(object = "mtkExperiment"): Provides a summary of the results produced by the workflow.
print
signature(x = "mtkExperiment"): Prints a report of the results produced by the workflow.
plot
signature(x = "mtkExperiment"): Plots the results produced by the workflow.
report
signature(this = "mtkExperiment"): Reports the results produced by the workflow.
Juhui WANG, MIA-Jouy, Inra, Juhui.Wang@jouy.inra.fr
J. Wang, H. Richard, R. Faivre, H. Monod (2013). Le package mtk
, une bibliothèque R pour l'exploration numérique des modèles.
In: Analyse de sensibilité et exploration de modèles : Application aux sciences de la nature et de l'environnement
(R. Faivre, B. Iooss, S. Mahévas, D. Makowski, H. Monod, Eds). Editions Quae, Versailles.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | # Compute the sensitivity index with the method "Regression"
# over the model "Ishigami" according to an experiment design
# generated with the method "BasicMonteCarlo"
x1 <- make.mtkFactor(name="x1", distribName="unif",
distribPara=list(min=-pi, max=pi))
x2 <- make.mtkFactor(name="x2", distribName="unif",
distribPara=list(min=-pi, max=pi))
x3 <- make.mtkFactor(name="x3", distribName="unif",
distribPara=list(min=-pi, max=pi))
factors <- mtkExpFactors(list(x1,x2,x3))
exp <- mtkExperiment(
factors,
design = 'BasicMonteCarlo',
designInfo=list(size=20),
model = 'Ishigami',
analyze = 'Regression',
analyzeInfo = list(ntboot=20)
)
run(exp)
summary(exp)
|
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