inst/PQRUT/server.R
In valeriyafilipova/StochasticPQRUT: Functions for Stochastic PQRUT
#
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(shinyFiles)
library(StochasticPQRUT)
set.seed(567)
shinyServer( function(input, output) {
my_data=reactive({
inFile <- input$PJ
P <- read.csv(inFile$datapath)
# print(head(P))
}
)
aR<-eventReactive(input$do1,{
withProgress(message = 'progress ', value = 0, {
inFile <- input$QJ
QJ<- read.csv(inFile$datapath)
# print(head(QJ))
P=my_data()
incProgress(amount = 2/5)
criticalduration(Q=QJ,P = P,qtT=input$qT,intEvent = 7,PDFplots = FALSE,writeResults = FALSE)
})
})
observeEvent(input$do1, {
output$plot1 <- renderPlot({
inFile <- input$QJ
QJ<- read.csv(inFile$datapath)
print(head(QJ))
P=my_data()
print(head(P))
qtT=input$qT
criticalduration(Q=QJ,P = P,qtT=qtT,intEvent = 7,PDFplots = FALSE,writeResults = FALSE)
})
})
observeEvent(input$do1,{
output$text1 <- renderText({
# pathmain=input$stn
a=aR()
#print(a)
paste("critical duration=",a$d)
})
})
hR<-eventReactive(input$do3,{
withProgress(message = 'Generating P,T events ', value = 0, {
inFile <- input$QJ
QJ<- read.csv(inFile$datapath)
inFile <- input$PJ
P = read.csv(inFile$datapath)
inFile <- input$h1
h1 = read.csv(inFile$datapath)
inFile <- input$Ph
p1 = read.csv(inFile$datapath)
inFile <- input$sl
sl = read.csv(inFile$datapath)
inFile <- input$SWE
SWE = read.csv(inFile$datapath)
a=aR()
incProgress(amount = 0/5, detail = paste("loading data"))
b=initcond(Qobs=Qd,sl=sl,
POTF=a$POTF,POTW=a$POTW,POTSp=a$POTSp,POTS=a$POTS,SWE=SWE,Td=Td,durt=input$durt,PDFplots=FALSE,writeResults=FALSE)
d=rainPOT(datarainfall = P,durt=input$durt,qFtset=input$qT1,qWtset=input$qT2,qSptset=input$qT3,qStset=input$qT4,distfunc="GP",writeResults = FALSE,PDFplots = FALSE)
incProgress(amount = 1/5, detail = paste("extracting hyetographs"))
h=stormp(prpFt=d$pF,prpWt=d$PW,prpSpt=d$PSp,prpSt=d$PS,p1 = p1,durt=input$durt,writeResults=FALSE,PDFplots=FALSE)
incProgress(amount = 2/5, detail = paste("extracting T sequence"))
h1=temprsim(incondFt=b$ntp1F,incondWt=b$ntp1W,incondSpt=b$ntp1Sp,incondSt=b$ntp1S,durt=input$durt,tm=h1,writeResults=FALSE,PDFplots=FALSE)
incProgress(amount = 3/5, detail = paste("Generating T,P data"))
h=simulateP(Nsim=input$Nsim,ncl = 2,durt=input$durt,distfunc="GP",hyet=h,TempSeq=h1,Pexp=d$par,writeResults=FALSE,PDFplots=FALSE)
incProgress(amount = 5/5, detail = paste("completed"))
return(hbd=list(h=h,b=b,d=d))
})
})
observeEvent(input$do2, {
output$plot2 <- renderPlot({
withProgress(message = 'progress ', value = 0, {
inFile <- input$PJ
P = read.csv(inFile$datapath)
pathmain=input$stn
qtT1=input$qT1
par(mfrow=c(2,2))
incProgress(amount = 2/5)
rainPOT(datarainfall = P,durt=input$durt,qFtset=qtT1,qWtset=input$qT2,qSptset=input$qT3,qStset=input$qT4,distfunc="GP",writeResults = FALSE,PDFplots = FALSE)
})
})
})
observeEvent(input$do3,{
#output$text5 <- renderText({ "completed" })
output$text2 <- renderText({
hR1=hR()
d=hR1$d
N=input$Nsim
# table1=data.frame("SON"=format(unname(d$rl[3]),digit=3),"DJF"=format(unname(d$rl[6]),digit=3),
# "MAM"=format(unname(d$rl[9]),digit=3),"JJA="=format(unname(d$rl[12]),digit=3))
print(paste("Generated", N, "values"))
})
})
gincon<-eventReactive(input$do4,{
withProgress(message = ' progress ', value = 0, {
hR1=hR()
b=hR1$b
incProgress(amount = 2/5)
gincon=initconditions(incondFt=b$ntp1F,incondWt=b$ntp1W,incondSpt=b$ntp1Sp,incondSt=b$ntp1S, Nsim=input$Nsim,durt=input$durt,writeResults=FALSE,PDFplots=FALSE)
})
})
observeEvent(input$do4,{
output$plot3<- renderPlot({
gincon1= gincon()
if(input$radio2=="Ft"){
print(gincon1$plot1)
}
if(input$radio2=="Wt"){
print(gincon1$plot2)
}
if(input$radio2=="Spt"){
print(gincon1$plot3)
}
if(input$radio2=="St"){
print(gincon1$plot4)
}
# int1=read.table(paste(pathmain,"/evtExp/",seasn,"/inctmv/incond",seasn,"1.txt",sep=""))
# StochasticPQRUTSeNorge:::smoothhydropairs(int1)
# if(input$radio1==2){
# for(seasn in c("Ft","Wt","Spt", "St")){
# int1=read.table(paste(pathmain,"/evtExp/",seasn,"/inctmv/incond",seasn,"1.txt",sep=""))
# int1$sl=0
# write.table(int1,paste(pathmain,"/evtExp/",seasn,"/inctmv/incond",seasn,"1.txt",sep=""))
# }
# StochasticPQRUTSeNorge:::smoothhydropairs(int1)
# }
})
})
gSt<-eventReactive(input$do5,{
withProgress(message = 'Generating Q ', value = 0, {
gincon1= gincon()
hR1=hR()
h=hR1$h
incProgress(0, detail = paste("season 09-11"))
gFT= hydrolsim(seasn="Ft",ncl =1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[1]]),E=h[[5]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
incProgress(1/4, detail = paste(" season 12-02"))
gWT= hydrolsim(seasn="Wt",ncl =1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[2]]),E=h[[6]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
incProgress(2/4, detail = paste("season 03-05"))
gSpT= hydrolsim(seasn="Spt",ncl = 1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[3]]),E=h[[7]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
incProgress(3/4, detail = paste(" season 06-08"))
gST= hydrolsim(seasn="St",ncl = 1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[4]]),E=h[[8]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
return(list( gFT= gFT,gWT=gWT, gSpT= gSpT,gST=gST))
})
})
observeEvent(input$do5,{
output$plot4<- renderPlot({
inFile <- input$Qh
Qh = read.csv(inFile$datapath)
gsim1=gSt()
hR1=hR()
d1=hR1$d[2:5]
h=hR1$h
gincon1= gincon()
m1=annualfreqplot(qtT=0.9,Nsim=input$Nsim,durt=input$durt,qobs=Qh,Pint=h[10:13],incond=gincon1,nsy=d1,Qsim=gsim1,writeResults=FALSE,PDFplots=FALSE)
# withProgress(message = 'Generating flood events ', value = 0, {
# # observeEvent(input$do5, {
# input$do5
# if (input$do5 == 0)
# return()
# this.station<<-gsub(pattern = "QJ.csv","",x = input$QJ)
# pathmain=input$stn
# kd=input$Kd
# param.station=isolate(c(input$K1,input$K2,input$T))
# print(param.station)
# Tmelt=input$Tmelt
# PrSn=input$PrSn
# incProgress(0, detail = paste("season 09-11"))
# seasn="Ft"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="Ft",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# incProgress(1/4, detail = paste(" season 12-02"))
# seasn="Wt"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="Wt",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# incProgress(2/4, detail = paste("season 03-05"))
# seasn="Spt"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="Spt",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# incProgress(3/4, detail = paste(" season 06-08"))
# seasn="St"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="St",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# annualfreqplot(pathmain,qtT=input$qT,Nsim=input$Nsim,durt=input$durt,mult=FALSE,PDFplots = FALSE)
# #annualfreqplot(pathmain,qtT=0.9,Nsim=1000,durt=48,mult=FALSE,PDFplots = FALSE)
# })
})
})
# observeEvent(input$do4, {
# output$plot5 <- renderPlot({
# pathmain=input$stn
# durt=as.numeric(as.character(read.table(file.path( pathmain,"duration.txt"))$V1[2]))
# print(durt)
# kd=input$Kd
# param.station=c(input$K1,input$K2,input$T)
# print(input$k)
# Qm<<- checkHydrograph(pathmain=input$stn,seasn=input$radio7,param.station,Nsim=input$Nsim,durt,k=(input$k)
# ,Area1=input$Area,kd,modelsnow="Snow.sim",slconst=1,snpSpt=0.3,ttsnow=-1,Tmax=0.5,Tmin=0.5)
#
# n2=Qm[[1]]
# evt1=data.frame(date=1:durt,P1=n2[,3],P2=n2[,2]+n2[,3],Q=n2[,1])
#
# plot(evt1[,4],type="l",ylab="Q",main=paste0(" soil moisture deficit=",round(Qm[[2]][3],1)))
# par(new = T)
# barplot(evt1[,2], yaxt = "n", space = NULL,
# ylim = rev(c(0, 4 * max(na.omit(evt1[,2])))),
# xaxt = "n",col=rgb(0, 0, 1, .3) )
# par(new = T)
# barplot(evt1[,3], yaxt = "n", space = NULL,
# ylim = rev(c(0, 4 * max(na.omit(evt1[,2])))),
# xaxt = "n",col=rgb(0, 0, 0, .1) )
# axis(side = 3, pos = 0, tck = 0,xaxt = "n")
# axis(side = 4, at = seq(0, floor(max(na.omit(evt1[,3])) +
# 1), length = (1 + ifelse(floor(max(na.omit(evt1[,3])) +
# 1) < 10, floor(max(na.omit(evt1[,3])) + 1),
# 4))), labels = as.integer(seq(0, floor(max(na.omit(evt1[,3])) +
# 1), length = (1 + ifelse(floor(max(na.omit(evt1[,3])) +
# 1) < 10, floor(max(na.omit(evt1[,3])) + 1), 4)))))
#
#
#
# })
#})
})
valeriyafilipova/StochasticPQRUT documentation built on May 26, 2019, 5:34 a.m.
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#
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(shinyFiles)
library(StochasticPQRUT)
set.seed(567)
shinyServer( function(input, output) {
my_data=reactive({
inFile <- input$PJ
P <- read.csv(inFile$datapath)
# print(head(P))
}
)
aR<-eventReactive(input$do1,{
withProgress(message = 'progress ', value = 0, {
inFile <- input$QJ
QJ<- read.csv(inFile$datapath)
# print(head(QJ))
P=my_data()
incProgress(amount = 2/5)
criticalduration(Q=QJ,P = P,qtT=input$qT,intEvent = 7,PDFplots = FALSE,writeResults = FALSE)
})
})
observeEvent(input$do1, {
output$plot1 <- renderPlot({
inFile <- input$QJ
QJ<- read.csv(inFile$datapath)
print(head(QJ))
P=my_data()
print(head(P))
qtT=input$qT
criticalduration(Q=QJ,P = P,qtT=qtT,intEvent = 7,PDFplots = FALSE,writeResults = FALSE)
})
})
observeEvent(input$do1,{
output$text1 <- renderText({
# pathmain=input$stn
a=aR()
#print(a)
paste("critical duration=",a$d)
})
})
hR<-eventReactive(input$do3,{
withProgress(message = 'Generating P,T events ', value = 0, {
inFile <- input$QJ
QJ<- read.csv(inFile$datapath)
inFile <- input$PJ
P = read.csv(inFile$datapath)
inFile <- input$h1
h1 = read.csv(inFile$datapath)
inFile <- input$Ph
p1 = read.csv(inFile$datapath)
inFile <- input$sl
sl = read.csv(inFile$datapath)
inFile <- input$SWE
SWE = read.csv(inFile$datapath)
a=aR()
incProgress(amount = 0/5, detail = paste("loading data"))
b=initcond(Qobs=Qd,sl=sl,
POTF=a$POTF,POTW=a$POTW,POTSp=a$POTSp,POTS=a$POTS,SWE=SWE,Td=Td,durt=input$durt,PDFplots=FALSE,writeResults=FALSE)
d=rainPOT(datarainfall = P,durt=input$durt,qFtset=input$qT1,qWtset=input$qT2,qSptset=input$qT3,qStset=input$qT4,distfunc="GP",writeResults = FALSE,PDFplots = FALSE)
incProgress(amount = 1/5, detail = paste("extracting hyetographs"))
h=stormp(prpFt=d$pF,prpWt=d$PW,prpSpt=d$PSp,prpSt=d$PS,p1 = p1,durt=input$durt,writeResults=FALSE,PDFplots=FALSE)
incProgress(amount = 2/5, detail = paste("extracting T sequence"))
h1=temprsim(incondFt=b$ntp1F,incondWt=b$ntp1W,incondSpt=b$ntp1Sp,incondSt=b$ntp1S,durt=input$durt,tm=h1,writeResults=FALSE,PDFplots=FALSE)
incProgress(amount = 3/5, detail = paste("Generating T,P data"))
h=simulateP(Nsim=input$Nsim,ncl = 2,durt=input$durt,distfunc="GP",hyet=h,TempSeq=h1,Pexp=d$par,writeResults=FALSE,PDFplots=FALSE)
incProgress(amount = 5/5, detail = paste("completed"))
return(hbd=list(h=h,b=b,d=d))
})
})
observeEvent(input$do2, {
output$plot2 <- renderPlot({
withProgress(message = 'progress ', value = 0, {
inFile <- input$PJ
P = read.csv(inFile$datapath)
pathmain=input$stn
qtT1=input$qT1
par(mfrow=c(2,2))
incProgress(amount = 2/5)
rainPOT(datarainfall = P,durt=input$durt,qFtset=qtT1,qWtset=input$qT2,qSptset=input$qT3,qStset=input$qT4,distfunc="GP",writeResults = FALSE,PDFplots = FALSE)
})
})
})
observeEvent(input$do3,{
#output$text5 <- renderText({ "completed" })
output$text2 <- renderText({
hR1=hR()
d=hR1$d
N=input$Nsim
# table1=data.frame("SON"=format(unname(d$rl[3]),digit=3),"DJF"=format(unname(d$rl[6]),digit=3),
# "MAM"=format(unname(d$rl[9]),digit=3),"JJA="=format(unname(d$rl[12]),digit=3))
print(paste("Generated", N, "values"))
})
})
gincon<-eventReactive(input$do4,{
withProgress(message = ' progress ', value = 0, {
hR1=hR()
b=hR1$b
incProgress(amount = 2/5)
gincon=initconditions(incondFt=b$ntp1F,incondWt=b$ntp1W,incondSpt=b$ntp1Sp,incondSt=b$ntp1S, Nsim=input$Nsim,durt=input$durt,writeResults=FALSE,PDFplots=FALSE)
})
})
observeEvent(input$do4,{
output$plot3<- renderPlot({
gincon1= gincon()
if(input$radio2=="Ft"){
print(gincon1$plot1)
}
if(input$radio2=="Wt"){
print(gincon1$plot2)
}
if(input$radio2=="Spt"){
print(gincon1$plot3)
}
if(input$radio2=="St"){
print(gincon1$plot4)
}
# int1=read.table(paste(pathmain,"/evtExp/",seasn,"/inctmv/incond",seasn,"1.txt",sep=""))
# StochasticPQRUTSeNorge:::smoothhydropairs(int1)
# if(input$radio1==2){
# for(seasn in c("Ft","Wt","Spt", "St")){
# int1=read.table(paste(pathmain,"/evtExp/",seasn,"/inctmv/incond",seasn,"1.txt",sep=""))
# int1$sl=0
# write.table(int1,paste(pathmain,"/evtExp/",seasn,"/inctmv/incond",seasn,"1.txt",sep=""))
# }
# StochasticPQRUTSeNorge:::smoothhydropairs(int1)
# }
})
})
gSt<-eventReactive(input$do5,{
withProgress(message = 'Generating Q ', value = 0, {
gincon1= gincon()
hR1=hR()
h=hR1$h
incProgress(0, detail = paste("season 09-11"))
gFT= hydrolsim(seasn="Ft",ncl =1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[1]]),E=h[[5]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
incProgress(1/4, detail = paste(" season 12-02"))
gWT= hydrolsim(seasn="Wt",ncl =1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[2]]),E=h[[6]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
incProgress(2/4, detail = paste("season 03-05"))
gSpT= hydrolsim(seasn="Spt",ncl = 1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[3]]),E=h[[7]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
incProgress(3/4, detail = paste(" season 06-08"))
gST= hydrolsim(seasn="St",ncl = 1,param.station=c(input$K1,input$K2,input$T),Nsim=input$Nsim,int1=gincon1$SWEFt,Pt=as.matrix(h[[4]]),E=h[[8]],durt=input$durt,Area1=input$Area,kd=input$Kd,snpSpt=0.3,ttsnow=-1,Tmax=input$Tmelt,Tmin=input$Tmelt,writeResults=FALSE,PDFplots=FALSE)
return(list( gFT= gFT,gWT=gWT, gSpT= gSpT,gST=gST))
})
})
observeEvent(input$do5,{
output$plot4<- renderPlot({
inFile <- input$Qh
Qh = read.csv(inFile$datapath)
gsim1=gSt()
hR1=hR()
d1=hR1$d[2:5]
h=hR1$h
gincon1= gincon()
m1=annualfreqplot(qtT=0.9,Nsim=input$Nsim,durt=input$durt,qobs=Qh,Pint=h[10:13],incond=gincon1,nsy=d1,Qsim=gsim1,writeResults=FALSE,PDFplots=FALSE)
# withProgress(message = 'Generating flood events ', value = 0, {
# # observeEvent(input$do5, {
# input$do5
# if (input$do5 == 0)
# return()
# this.station<<-gsub(pattern = "QJ.csv","",x = input$QJ)
# pathmain=input$stn
# kd=input$Kd
# param.station=isolate(c(input$K1,input$K2,input$T))
# print(param.station)
# Tmelt=input$Tmelt
# PrSn=input$PrSn
# incProgress(0, detail = paste("season 09-11"))
# seasn="Ft"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="Ft",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# incProgress(1/4, detail = paste(" season 12-02"))
# seasn="Wt"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="Wt",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# incProgress(2/4, detail = paste("season 03-05"))
# seasn="Spt"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="Spt",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# incProgress(3/4, detail = paste(" season 06-08"))
# seasn="St"
# isolate(hydrolsim(pathmain=pathmain,mult=FALSE,sn="St",param.station=param.station,Nsim=input$Nsim,durt=input$durt
# ,Area1=input$Area,kd=kd,modelsnow="Snow.sim",slconst=1,snpSpt = PrSn,ttsnow = -1,Tmax=Tmelt,Tmin=Tmelt))
# annualfreqplot(pathmain,qtT=input$qT,Nsim=input$Nsim,durt=input$durt,mult=FALSE,PDFplots = FALSE)
# #annualfreqplot(pathmain,qtT=0.9,Nsim=1000,durt=48,mult=FALSE,PDFplots = FALSE)
# })
})
})
# observeEvent(input$do4, {
# output$plot5 <- renderPlot({
# pathmain=input$stn
# durt=as.numeric(as.character(read.table(file.path( pathmain,"duration.txt"))$V1[2]))
# print(durt)
# kd=input$Kd
# param.station=c(input$K1,input$K2,input$T)
# print(input$k)
# Qm<<- checkHydrograph(pathmain=input$stn,seasn=input$radio7,param.station,Nsim=input$Nsim,durt,k=(input$k)
# ,Area1=input$Area,kd,modelsnow="Snow.sim",slconst=1,snpSpt=0.3,ttsnow=-1,Tmax=0.5,Tmin=0.5)
#
# n2=Qm[[1]]
# evt1=data.frame(date=1:durt,P1=n2[,3],P2=n2[,2]+n2[,3],Q=n2[,1])
#
# plot(evt1[,4],type="l",ylab="Q",main=paste0(" soil moisture deficit=",round(Qm[[2]][3],1)))
# par(new = T)
# barplot(evt1[,2], yaxt = "n", space = NULL,
# ylim = rev(c(0, 4 * max(na.omit(evt1[,2])))),
# xaxt = "n",col=rgb(0, 0, 1, .3) )
# par(new = T)
# barplot(evt1[,3], yaxt = "n", space = NULL,
# ylim = rev(c(0, 4 * max(na.omit(evt1[,2])))),
# xaxt = "n",col=rgb(0, 0, 0, .1) )
# axis(side = 3, pos = 0, tck = 0,xaxt = "n")
# axis(side = 4, at = seq(0, floor(max(na.omit(evt1[,3])) +
# 1), length = (1 + ifelse(floor(max(na.omit(evt1[,3])) +
# 1) < 10, floor(max(na.omit(evt1[,3])) + 1),
# 4))), labels = as.integer(seq(0, floor(max(na.omit(evt1[,3])) +
# 1), length = (1 + ifelse(floor(max(na.omit(evt1[,3])) +
# 1) < 10, floor(max(na.omit(evt1[,3])) + 1), 4)))))
#
#
#
# })
#})
})
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