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53 lines
1.7 KiB
R
53 lines
1.7 KiB
R
# FORESTS -----------------------------------------------------------------
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#' A abstract reference class to compute twin via random forests
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#'
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#' @include difft.R predict.R
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#'
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#' @import methods
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VT.forest <- setRefClass(
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Class = "VT.forest",
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contains = "VT.difft",
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methods = list(
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run = function(){
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"Compute twin1 and twin2 computation. Switch treatment if necessary."
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.self$computeTwin1()
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if(inherits(.self, "VT.forest.one")) .self$vt.object$switchTreatment() #if one forest
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.self$computeTwin2()
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if(inherits(.self, "VT.forest.one")) .self$vt.object$switchTreatment() #if one forest
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.self$computeDifft()
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.self$vt.object$computeDelta() # To see later
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return(invisible(.self))
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},
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checkModel = function(model){
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"Checking model class: Must be : train, RandomForest, randomForest"
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if(!(inherits(model, "train") | inherits(model, "RandomForest") | inherits(model, "randomForest"))){
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stop("Model is not recognized. Must be : train, RandomForest, randomForest")
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}
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},
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getFullData = function(){
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"Return twin1, twin2 and difft in column"
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if(length(.self$twin1) != nrow(.self$vt.object$data)) stop("Twin1 must have same length as data")
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if(length(.self$twin2) != nrow(.self$vt.object$data)) stop("Twin2 must have same length as data")
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if(length(.self$difft) != nrow(.self$vt.object$data)) stop("Difft must have same length as data")
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tmp <- cbind(.self$vt.object$data, .self$twin1, .self$twin2, .self$difft)
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colnames(tmp) <- c(colnames(.self$vt.object$data), "twin1", "twin2", "difft")
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return(tmp)
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}
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)
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)
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