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plot optimized muso

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This commit is contained in:
Roland Hollós 2019-03-11 13:06:37 +01:00
parent 760bbaef9a
commit 4b1c5fe5a3
3 changed files with 72 additions and 40 deletions
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17
RBBGCMuso/R/calibration.R
View File

@ -44,6 +44,7 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
modelVar = 3009,
postProcString = NULL)
{
mdata <- measuredData
dataCol <- grep(dataVar, colnames(measuredData))
if(is.null(parameters)){
@ -104,6 +105,7 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
randValues <- randVals[[2]]
settings$calibrationPar <- randVals[[1]]
list2env(alignData(measuredData,dataCol = dataCol,modellSettings = settings,startDate = startDate,endDate = endDate,leapYear = leapYearHandling, continious = continious),envir=environment())
## modIndex and measuredData are created.
modellOut <- numeric(iterations + 1) # single variable solution
rmse <- numeric(iterations + 1)
@ -149,12 +151,21 @@ optiMuso <- function(measuredData, parameters = NULL, startDate,
preservedCalib <- preservedCalib[-1,]
dontInclude <-c((ncol(preservedCalib)-1),ncol(preservedCalib))
for(i in seq_along(colnames(preservedCalib)[-dontInclude])){
p[[i]] <- ggplot(as.data.frame(preservedCalib),aes_string(colnames(preservedCalib)[i],"likelihood"))+geom_point(shape='.',size=1,alpha=0.8)
p[[i]] <- ggplot(as.data.frame(preservedCalib),aes_string(colnames(preservedCalib)[i],"likelihood")) +
geom_point(shape='.',size=1,alpha=0.8)
}
ggsave(plotName,grid.arrange(grobs = p, ncol = floor(sqrt(ncol(preservedCalib)-1))),dpi = 3000)
ggsave(plotName,grid.arrange(grobs = p, ncol = floor(sqrt(ncol(preservedCalib)-1))),dpi = 300)
maxLikelihoodPlace <- which(preservedCalib[,"likelihood"]==max(preservedCalib[,"likelihood"],na.rm = TRUE))
resPlot <- plotMusoWithData(mdata = mdata, startDate = startDate, endDate = endDate,
dataVar = dataVar, modelVar = modelVar, settings = settings, continious = continious) +
plotMuso(settings = settings, parameters = randValues[maxLikelihoodPlace,],
postProcString = postProcString, skipSpinup = FALSE, variable = colNumb, layerPlot = TRUE, colour = "green")
return(preservedCalib[preservedCalib[,"likelihood"]==max(preservedCalib[,"likelihood"],na.rm = TRUE),])
print(resPlot)
tempEpc <- paste0(tools::file_path_sans_ext(basename(settings$epcInput[2])),"-tmp.",tools::file_ext(settings$epcInput[2]))
file.rename(tempEpc, "optimizedEpc.epc")
return(preservedCalib[maxLikelihoodPlace,])
}

11
RBBGCMuso/R/musoTime.R
View File

@ -59,17 +59,22 @@ musoDate <- function(startYear, endYears = NULL, numYears, combined = TRUE, leap
#' This function align the data to the model and the model to the data
#' @importFrom lubridate leap_year
#' @keywords internal
alignData <- function(mdata, dataCol, modellSettings = NULL, startDate=NULL, endDate=NULL, formatString = "%Y-%m-%d", leapYear = TRUE, continious = TRUE){
alignData <- function(mdata, dataCol, modellSettings = NULL, startDate=NULL, endDate=NULL, formatString = "%Y-%m-%d", leapYear = TRUE, continious = FALSE){
if(continious){
if((is.null(startDate) | is.null(endDate))){
stop("If your date is continuous, you have to provide both startDate and endDate. ")
}
startDate <- as.Date(startDate, format = formatString)
endDate <- as.Date(endDate, format = formatString)
mdata <- as.data.frame(mdata)
}
if(is.null(modellSettings)){
modellSettings <- setupMuso()
}
mdata <- as.data.frame(mdata)
if(continious){
dates <- seq(startDate, to = endDate, by= "day")
} else{

30
RBBGCMuso/R/plotMuso.R
View File

@ -251,8 +251,12 @@ plotMuso <- function(settings = NULL, variable = 1,
#' @importFrom ggplot2 ggplot geom_line geom_point aes aes_string labs theme element_blank
#' @export
plotMusoWithData <- function(mdata, plotName=NULL,
startDate, endDate,
colour=c("black","blue"),dataVar, modelVar, settings = setupMuso(), silent = TRUE, continious = TRUE){
startDate = NULL, endDate = NULL,
colour=c("black","blue"), dataVar, modelVar, settings = setupMuso(), silent = TRUE, continious = FALSE){
if(continious & (is.null(startDate) | is.null(endDate))){
stop("If your date is continuous, you have to provide both startDate and endDate. ")
}
dataCol<- grep(paste0("^",dataVar,"$"), colnames(mdata))
selVar <- grep(modelVar,(settings$dailyVarCodes))+4
@ -261,21 +265,33 @@ plotMusoWithData <- function(mdata, plotName=NULL,
modellSettings = settings,
startDate = startDate,
endDate = endDate, leapYear = FALSE, continious = continious),envir=environment())
mesData <- numeric(settings$numYears*365)
k <- 1
for(i in seq(mesData)){
if(i %in% modIndex){
mesData[i] <- measuredData[k]
k <- k + 1
} else {
mesData[i] <- NA
}
}
rm(k)
# modIndex and measuredData are created.
## measuredData is created
baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)[modIndex,]
## baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)[modIndex,]
baseData <- calibMuso(settings = settings, silent = silent, prettyOut = TRUE)
baseData[,1] <- as.Date(baseData[,1],format = "%d.%m.%Y")
selVarName <- colnames(baseData)[selVar]
if(!all.equal(colnames(baseData),unique(colnames(baseData)))){
notUnique <- setdiff((unlist(settings$dailyVarCodes)),unique(unlist(settings$dailyVarCodes)))
stop(paste0("Error: daily output variable list in the ini file must contain unique numbers. Check your ini files! Not unique codes: ",notUnique))
}
mesData<-cbind.data.frame(baseData[,1],mesData)
colnames(mesData) <- c("date", "measured")
p <- baseData %>%
ggplot(aes_string("date",selVarName)) +
geom_line(colour=colour[1]) +
geom_point(colour=colour[2], aes(date,measuredData)) +
geom_point(data = mesData, colour=colour[2], aes(date,measured)) +
labs(y = paste0(selVarName,"_measured"))+
theme(axis.title.x = element_blank())
if(!is.null(plotName)){