setwd("J:/Documents/Arbete/Fortlöpande miljöanalys/Fenologi/Skoglig fenologi vid SLU")
library(dplyr)

xpre<-91:250
ypre<-rep(0,160)
minxpre<-min(xpre)
maxxpre<-max(xpre)
xtspre<-seq(0,2000,by=5)
PEP.table<-data.frame(koder=0,doy=0,year=0,station=0,species=0)[FALSE, ]
Interpol.table<-data.frame(DOY=0,ShootDev=0,ShootProc=0,Year=0,Station=0,Species=0)[FALSE, ]
Interpol.tsum<-data.frame(Station=0,Species=0,Year=0,Tempsum=0,ShootDevProc=0)[FALSE, ]

tree0<- read.csv("Tree_data.csv", header=TRUE, sep=",", dec=".")
tempsum<- read.csv("Tempsum.csv", header=TRUE, sep=",", dec = ".")

treedata<-arrange(tree0,Species,Station,Year,doy)

specieslist<-unique(treedata$Species)

for (l in 1:length(specieslist)) {
  testspecies<-subset(treedata,treedata$Species==specieslist[l])
  stationlist<-unique(testspecies$Station)
  
  #  plot.new()
  par(mfrow = c(2,1))
  
  for (k in 1:length(stationlist)) {
    teststation<-subset(testspecies,testspecies$Station==stationlist[k])
    yearlist<-unique(teststation$Year)
    
    plot(xpre,ypre, xlab="", ylab = paste("Station ", stationlist[k], ", species " ,specieslist[l]),ylim=c(0,100),col="white")
    
    for (j in 1:length(yearlist)) {
      testyear<-subset(teststation,teststation$Year==yearlist[j])
      tempsumyear<-subset(tempsum,tempsum$Station==stationlist[k] & tempsum$Year==yearlist[j] & tempsum$doy>=minxpre & tempsum$doy<=maxxpre)
      
      shootdev0<-as.data.frame(approx(testyear$doy,testyear$ShootDev,xout=xpre,yleft = -1, yright = -2), col.names = c("doy","ShootDev"))
      shootdev<-subset(shootdev0,shootdev0$ShootDev>-1)
      minshoot<-min(shootdev$ShootDev)
      maxshoot<-max(shootdev$ShootDev)

      for (i in 1:length(xpre)) {
        if (shootdev0$ShootDev[i]==-1) shootdev0$ShootDev[i]=minshoot else shootdev0$ShootDev[i]
        if (shootdev0$ShootDev[i]==-2) shootdev0$ShootDev[i]=maxshoot else shootdev0$ShootDev[i]
      }
      
      shootdev0$ShootProc<-(shootdev0$ShootDev-minshoot)/(maxshoot-minshoot)*100

      if (nrow(tempsumyear)>0) {
         colnames(shootdev0)[1]<-"doy"
         colnames(tempsumyear)[3]<-"doy"
         shootdev1<-merge(shootdev0, tempsumyear, by = "doy")

         shootdev2<-as.data.frame(approx(shootdev1$Tempsum,shootdev1$ShootProc,xout=xtspre, yleft = 0, yright = 100, ties = mean), col.names = c("Tempsum","ShootDevProc"))
         shootdev2$Year <-yearlist[j]
         shootdev2$Station<-stationlist[k]
         shootdev2$Species<-specieslist[l]
         shootdev2<-shootdev2 %>% relocate(Station,Species,Year)
         Interpol.tsum<-rbind(Interpol.tsum,shootdev2)
         
      }
         
      shootdev0$Year <-yearlist[j]
      shootdev0$Station<-stationlist[k]
      shootdev0$Species<-specieslist[l]
      
      koder<-c(31,32,33,34,35,36,37,38,39)
      doy<-c(0,0,0,0,0,0,0,0,0)
     
      for (m in 1:(length(koder)-1)) {
        
        for (i in 1:length(xpre)) {
          if (shootdev0$ShootProc[i]>=10*m & doy[m]==0) doy[m]=shootdev0$doy[i] else doy[m]
        }
      }

      for (i in 1:length(xpre)) {
        if (shootdev0$ShootProc[i]==100 & doy[9]==0) doy[9]=shootdev0$doy[i] else doy[9]
      }
      
      #points(doy[1],shootdev$ShootProc[doy[1]-90], col = 6, pch = 1, cex = 0.7)

      lines(shootdev0$doy,shootdev0$ShootProc, col = 6)
      
      Interpol.table<-rbind(Interpol.table,shootdev0)
      
      koddoy<-as.data.frame(koder)
      koddoy<-merge(koddoy,as.data.frame(doy),0)
      koddoy$Row.names=NULL
      
      koddoy$Year <-yearlist[j]
      koddoy$Station<-stationlist[k]
      koddoy$Species<-specieslist[l]
      
      PEP.table<-rbind(PEP.table,koddoy)

    }
  }
}

Intpoltab<-Interpol.table %>% relocate(Species,Station,Year)
PEPtab<-PEP.table %>% relocate(Station,Species,koder,Year)
colnames(PEPtab)[3]<-"phase_id"

Intpoltab<-arrange(Intpoltab,Species,Station,Year,doy)
PEPtab<-arrange(PEPtab,Species,Station,Year,phase_id)

write.csv(Intpoltab, "InterpolTreeData.csv", row.names = FALSE)
write.csv(PEPtab, "PEP-TreeData.csv", row.names = FALSE)
write.csv(Interpol.tsum, "InterpolTsumTreeData.csv", row.names = FALSE)