mtk.evaluatorAddons: The 'mtk.evaluatorAddons' function
In mtk: Mexico ToolKit library (MTK)

Description Usage Arguments Details Value Author(s) References Examples

A function used to extend the "mtk" package with new models programmed as R functions. The mtk.evaluatorAddons function takes a R file as input and converts it into a mtk compliant class which can be seamlessly integrated into the mtk package.

mtk.evaluatorAddons(where = NULL, library = NULL, 
	authors = NULL, name = NULL, main = NULL, 
	summary = NULL, plot = NULL, 
	print = NULL)

`where`	NULL or a file holding the R function to convert.
`library`	NULL or the name of the library if the R function to convert is held in a library.
`authors`	NULL or information about the authors of the R function.
`name`	a string to name the model when used with the "mtk" package.
`main`	the R function which implements the model.
`summary`	NULL or a special version of the "summary" function provided with the model.
`plot`	NULL or a special version of the "plot" function provided with the model.
`print`	NULL or a special version of the "print" function provided with the model.

The new model must be programmed according to the following syntax:

main <- function(X, ...) where X is a data.frame holding the experiment design used to run the model simulation.

The function main returns a named list with two elements: main and information. The element main holds the result of the model simulation and the element information is optional, may be used to give supplementary information about the simulation process and its results.

Furthermore, users can redefine the following generic functions to report the results more precisely:

summary (object, ...), plot(x,y, ...), print(x, ...).

invisble()

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.

# an example implementation of the model "WW" is held  
# in the file "inst/extdata/wwdm.R"

	rFile <- "wwdm.R"
	rFile <- paste(path.package("mtk", quiet = TRUE),
		"/extdata/",rFile,sep = "")

# to covert the model "WW" to a S4 classes compliant with the "mtk" package.
# The generated "mtk" compliant class is called "mtkXXXEvaluator.R" where XXX corresponds
# to the name of the model.

	mtk.evaluatorAddons(where=rFile, authors="H. Monod,INRA", name="WW", main="wwdm.simule")

# to use the model evaluator "WW" with the package "mtk",
# just source the generated new files
	
	source("mtkWWEvaluator.R")

## Use the "mtkWWEvaluator" with the "mtk" package in a seamless way:

# 1) Define the factors

	Eb <- make.mtkFactor(name="Eb", distribName="unif", 
    	  nominal=1.85, distribPara=list(min=0.9, max=2.8))
	Eimax <- make.mtkFactor(name="Eimax", distribName="unif",
    	  nominal=0.94, distribPara=list(min=0.9, max=0.99))
	K <- make.mtkFactor(name="K", distribName="unif", nominal=0.7, 
     	 distribPara=list(min=0.6, max=0.8))
	Lmax <- make.mtkFactor(name="Lmax", distribName="unif", nominal=7.5,
     	 distribPara=list(min=3, max=12))
	A <- make.mtkFactor(name="A", distribName="unif", nominal=0.0065,
    	  distribPara=list(min=0.0035, max=0.01))
	B <- make.mtkFactor(name="B", distribName="unif", nominal=0.00205,
     	 distribPara=list(min=0.0011, max=0.0025))
	TI <- make.mtkFactor(name="TI", distribName="unif", nominal=900,
     	 distribPara=list(min=700, max=1100))

	WW.factors <- mtkExpFactors(list(Eb,Eimax,K,Lmax,A,B,TI))

# 2) Build a workflow  for the "WW" model

	exp <- mtkExperiment(expFactors=WW.factors,
		design="Morris",designInfo=list(type="oat",
			r=10, levels=5, grid.jump=3),
		model="WW", modelInfo=list(year=3),
		analyze="Morris", analyzeInfo=list(type="oat",
			r=10, levels=5, grid.jump=3))
			
## 3) Run the workflow and reports the results

	run(exp)
	summary(exp)