postProc in calibMuso
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@ -41,7 +41,8 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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exp(-sqrt(mean((x-y)^2)))
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exp(-sqrt(mean((x-y)^2)))
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},
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},
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continious,
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continious,
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modelVar = 3009)
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modelVar = 3009,
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postProcString = NULL)
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{
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{
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dataCol <- grep(dataVar, colnames(measuredData))
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dataCol <- grep(dataVar, colnames(measuredData))
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@ -112,11 +113,16 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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write.csv(x=origModellOut, file=paste0(pretag,1,".csv"))
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write.csv(x=origModellOut, file=paste0(pretag,1,".csv"))
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modellOut[1] <- likelihood(measuredData,origModellOut[modIndex,colNumb])
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modellOut[1] <- likelihood(measuredData,origModellOut[modIndex,colNumb])
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print("Running the model with the random epc values...", quote = FALSE)
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print("Running the model with the random epc values...", quote = FALSE)
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if(!is.null(postProcString)){
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colNumb <- length(settings$dailyVarCodes) + 1
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}
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for(i in 2:(iterations+1)){
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for(i in 2:(iterations+1)){
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tmp <- tryCatch(calibMuso(settings = settings,
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tmp <- tryCatch(calibMuso(settings = settings,
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parameters = randValues[(i-1),],
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parameters = randValues[(i-1),],
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silent= TRUE,
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silent= TRUE,
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skipSpinup = skipSpinup)[modIndex,colNumb], error = function (e) NA)
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skipSpinup = skipSpinup, postProcString = postProcString)[modIndex,colNumb], error = function (e) NA)
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modellOut[i]<- likelihood(measuredData,tmp)
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modellOut[i]<- likelihood(measuredData,tmp)
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rmse[i] <- sqrt(mean((measuredData-tmp)^2))
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rmse[i] <- sqrt(mean((measuredData-tmp)^2))
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