Description Usage Arguments Value Details Author(s) See Also Examples
Plots graphically the results produced by the process.
1 |
x |
the underlying object of class |
y |
see |
... |
see |
invisble()
The behavior of the plot
depends on the sub-class where the method is implemented.
See the documentation of the particular sub-class for details of what is produced. Use methods("plot")
to get all the methods for the plot
generic.
See par
for details about the graphical parameter arguments.
Juhui WANG, MIA-Jouy, Inra, Juhui.Wang@jouy.inra.fr
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | # Create a designer and an analyser avec the method "Morris"
# to analyze the model "Ishigami":
# Specify the factors to analyze:
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))
# Build the processes:
# 1) the experimental design process with the method "Morris".
exp1.designer <- mtkNativeDesigner(design="Morris",
information=list(r=20,type="oat",levels=4,grid.jump=2))
# 2) the model simulation process with the model "Ishigami".
exp1.evaluator <- mtkNativeEvaluator(model="Ishigami")
# # 3) the analysis process with the default method.
# Here, it is the Morris method.
exp1.analyser <- mtkDefaultAnalyser()
# Build the workflow with the processes defined previously.
exp1 <- mtkExpWorkflow(expFactors=factors,
processesVector = c(design=exp1.designer,
evaluate=exp1.evaluator, analyze=exp1.analyser))
# Run the workflow and plot the results.
run(exp1)
plot(exp1)
# Extract a process and report its results
p <- getProcess(exp1, "analyze")
plot(p)
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