plot optimized muso
This commit is contained in:
Roland Hollós
parent
760bbaef9a
commit
4b1c5fe5a3
@ -25,7 +25,7 @@
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#' @importFrom ggplot2 ggplot aes_string geom_point ggsave
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#' @importFrom magrittr '%>%'
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#' @importFrom gridExtra grid.arrange
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#' @export
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#' @export
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optiMuso <- function(measuredData, parameters = NULL, startDate,
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endDate, formatString = "%Y-%m-%d",
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leapYearHandling = TRUE,
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@ -44,8 +44,9 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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modelVar = 3009,
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postProcString = NULL)
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{
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mdata <- measuredData
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dataCol <- grep(dataVar, colnames(measuredData))
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if(is.null(parameters)){
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parameters <- tryCatch(read.csv("parameters.csv", stringsAsFactor=FALSE), error = function (e) {
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stop("You need to specify a path for the parameters.csv, or a matrix.")
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@ -56,26 +57,26 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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stop("Cannot find neither parameters file neither the parameters matrix")
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})
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}}
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outLoc <- normalizePath(outLoc)
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outLocPlain <- basename(outLoc)
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currDir <- getwd()
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if(!dir.exists(outLoc)){
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dir.create(outLoc)
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warning(paste(outLoc," is not exists, so it was created"))
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}
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outLoc <- normalizePath(outLoc)
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if(is.null(settings)){
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settings <- setupMuso()
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}
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parameterNames <- parameters[,1]
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pretag <- file.path(outLoc,preTag)
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npar <- length(settings$calibrationPar)
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##reading the original epc file at the specified
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## row numbers
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print("optiMuso is randomizing the epc parameters now...",quote = FALSE)
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@ -85,17 +86,17 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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} else {
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randVals <- musoRand(parameters = parameters,constrains = constrains, iterations = iterations)
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}
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origEpc <- readValuesFromFile(settings$epc[2],parameters[,2])
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## Prepare the preservedCalib matrix for the faster
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## run.
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pretag <- file.path(outLoc,preTag)
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## Creating function for generating separate
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## csv files for each run
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progBar <- txtProgressBar(1,iterations,style=3)
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colNumb <- which(settings$dailyVarCodes == modelVar)
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settings$iniInput[2] %>%
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@ -104,12 +105,13 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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randValues <- randVals[[2]]
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settings$calibrationPar <- randVals[[1]]
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list2env(alignData(measuredData,dataCol = dataCol,modellSettings = settings,startDate = startDate,endDate = endDate,leapYear = leapYearHandling, continious = continious),envir=environment())
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## modIndex and measuredData are created.
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modellOut <- numeric(iterations + 1) # single variable solution
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rmse <- numeric(iterations + 1)
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origModellOut <- calibMuso(settings=settings,silent=TRUE, skipSpinup = skipSpinup)
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write.csv(x=origModellOut, file=paste0(pretag,1,".csv"))
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modellOut[1] <- likelihood(measuredData,origModellOut[modIndex,colNumb])
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print("Running the model with the random epc values...", quote = FALSE)
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@ -117,13 +119,13 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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if(!is.null(postProcString)){
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colNumb <- length(settings$dailyVarCodes) + 1
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}
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for(i in 2:(iterations+1)){
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tmp <- tryCatch(calibMuso(settings = settings,
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parameters = randValues[(i-1),],
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silent= TRUE,
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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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rmse[i] <- sqrt(mean((measuredData-tmp)^2))
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write.csv(x=tmp, file=paste0(pretag,(i+1),".csv"))
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@ -133,13 +135,13 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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paramLines <- order(paramLines)
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randInd <- randVals[[1]][(randVals[[1]] %in% parameters[,2])]
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randInd <- order(randInd)
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epcStrip <- rbind(origEpc[order(parameters[,2])],
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randValues[,randVals[[1]] %in% parameters[,2]][,randInd])
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preservedCalib <- cbind(epcStrip,rmse,
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modellOut)
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columNames <- c(parameterNames[paramLines],"rmse", "likelihood")
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@ -149,12 +151,21 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
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preservedCalib <- preservedCalib[-1,]
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dontInclude <-c((ncol(preservedCalib)-1),ncol(preservedCalib))
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for(i in seq_along(colnames(preservedCalib)[-dontInclude])){
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p[[i]] <- ggplot(as.data.frame(preservedCalib),aes_string(colnames(preservedCalib)[i],"likelihood"))+geom_point(shape='.',size=1,alpha=0.8)
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p[[i]] <- ggplot(as.data.frame(preservedCalib),aes_string(colnames(preservedCalib)[i],"likelihood")) +
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geom_point(shape='.',size=1,alpha=0.8)
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}
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ggsave(plotName,grid.arrange(grobs = p, ncol = floor(sqrt(ncol(preservedCalib)-1))),dpi = 3000)
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return(preservedCalib[preservedCalib[,"likelihood"]==max(preservedCalib[,"likelihood"],na.rm = TRUE),])
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ggsave(plotName,grid.arrange(grobs = p, ncol = floor(sqrt(ncol(preservedCalib)-1))),dpi = 300)
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maxLikelihoodPlace <- which(preservedCalib[,"likelihood"]==max(preservedCalib[,"likelihood"],na.rm = TRUE))
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resPlot <- plotMusoWithData(mdata = mdata, startDate = startDate, endDate = endDate,
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dataVar = dataVar, modelVar = modelVar, settings = settings, continious = continious) +
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plotMuso(settings = settings, parameters = randValues[maxLikelihoodPlace,],
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postProcString = postProcString, skipSpinup = FALSE, variable = colNumb, layerPlot = TRUE, colour = "green")
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print(resPlot)
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tempEpc <- paste0(tools::file_path_sans_ext(basename(settings$epcInput[2])),"-tmp.",tools::file_ext(settings$epcInput[2]))
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file.rename(tempEpc, "optimizedEpc.epc")
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return(preservedCalib[maxLikelihoodPlace,])
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}
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@ -59,17 +59,22 @@ musoDate <- function(startYear, endYears = NULL, numYears, combined = TRUE, leap
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#' This function align the data to the model and the model to the data
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#' @importFrom lubridate leap_year
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#' @keywords internal
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alignData <- function(mdata, dataCol, modellSettings = NULL, startDate=NULL, endDate=NULL, formatString = "%Y-%m-%d", leapYear = TRUE, continious = TRUE){
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alignData <- function(mdata, dataCol, modellSettings = NULL, startDate=NULL, endDate=NULL, formatString = "%Y-%m-%d", leapYear = TRUE, continious = FALSE){
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if(continious){
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if((is.null(startDate) | is.null(endDate))){
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stop("If your date is continuous, you have to provide both startDate and endDate. ")
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}
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startDate <- as.Date(startDate, format = formatString)
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endDate <- as.Date(endDate, format = formatString)
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}
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startDate <- as.Date(startDate, format = formatString)
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endDate <- as.Date(endDate, format = formatString)
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mdata <- as.data.frame(mdata)
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if(is.null(modellSettings)){
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modellSettings <- setupMuso()
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}
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mdata <- as.data.frame(mdata)
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if(continious){
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dates <- seq(startDate, to = endDate, by= "day")
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} else{
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@ -251,8 +251,12 @@ plotMuso <- function(settings = NULL, variable = 1,
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#' @importFrom ggplot2 ggplot geom_line geom_point aes aes_string labs theme element_blank
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#' @export
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plotMusoWithData <- function(mdata, plotName=NULL,
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startDate, endDate,
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colour=c("black","blue"),dataVar, modelVar, settings = setupMuso(), silent = TRUE, continious = TRUE){
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startDate = NULL, endDate = NULL,
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colour=c("black","blue"), dataVar, modelVar, settings = setupMuso(), silent = TRUE, continious = FALSE){
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if(continious & (is.null(startDate) | is.null(endDate))){
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stop("If your date is continuous, you have to provide both startDate and endDate. ")
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}
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dataCol<- grep(paste0("^",dataVar,"$"), colnames(mdata))
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selVar <- grep(modelVar,(settings$dailyVarCodes))+4
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@ -261,24 +265,36 @@ plotMusoWithData <- function(mdata, plotName=NULL,
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modellSettings = settings,
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startDate = startDate,
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endDate = endDate, leapYear = FALSE, continious = continious),envir=environment())
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mesData <- numeric(settings$numYears*365)
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k <- 1
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for(i in seq(mesData)){
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if(i %in% modIndex){
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mesData[i] <- measuredData[k]
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k <- k + 1
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} else {
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mesData[i] <- NA
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}
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}
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rm(k)
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# modIndex and measuredData are created.
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## measuredData is created
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baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)[modIndex,]
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## baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)[modIndex,]
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baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)
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baseData[,1] <- as.Date(baseData[,1],format = "%d.%m.%Y")
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selVarName <- colnames(baseData)[selVar]
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if(!all.equal(colnames(baseData),unique(colnames(baseData)))){
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notUnique <- setdiff((unlist(settings$dailyVarCodes)),unique(unlist(settings$dailyVarCodes)))
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stop(paste0("Error: daily output variable list in the ini file must contain unique numbers. Check your ini files! Not unique codes: ",notUnique))
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}
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mesData<-cbind.data.frame(baseData[,1],mesData)
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colnames(mesData) <- c("date", "measured")
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p <- baseData %>%
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ggplot(aes_string("date",selVarName)) +
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geom_line(colour=colour[1]) +
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geom_point(colour=colour[2], aes(date,measuredData)) +
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geom_point(data = mesData, colour=colour[2], aes(date,measured)) +
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labs(y = paste0(selVarName,"_measured"))+
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theme(axis.title.x = element_blank())
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if(!is.null(plotName)){
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if(!is.null(plotName)){
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ggsave(plotName,p)
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return(p)
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} else {
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