library(data.table)
library(DT)
library(htmlwidgets)

f2p <- function(x) #get date-time data from recording file names
{
  if (is.data.frame((x)[1])) {pretemps <- vector(length = nrow(x))}
  op <- options(digits.secs = 3)
  pretemps <- paste(substr(x, nchar(x) - 18, nchar(x)-4), ".", substr(x, nchar(x) - 2, nchar(x)), sep = "")
  strptime(pretemps, "%Y%m%d_%H%M%OS",tz="UTC")-7200
}

args <- commandArgs(trailingOnly = TRUE)
#print(args)
EchelleErreur=c("","POSSIBLE","PROBABLE","SUR")
EchelleNumErreur=c(99,50,10,1)

#for test
#inputest=list.files("C:/Users/Yves Bas/Documents/GitHub/65MO_Galaxy-E/raw_scripts/Vigie-Chiro/output_IdValid_input_BilanEnrichi/",pattern="IdC2.csv",full.names=T)
#for (i in 1:length(inputest))
#{
#   args=c(inputest[i],"refPF.csv","SpeciesList.csv")
   
   
IdC2=fread(args[1])
refPF=fread(args[2])
GroupList=fread(args[3])

if(substr(IdC2$`nom du fichier`[1],2,2)!="a")
{
  print("Protocole non conforme, ce script doit etre lance pour un protocole Point Fixe")
}else{
  

#compute error risk by species (minimum error among files)
#to be replaced by glm outputs if I'll have time
RisqueErreurT=aggregate(IdC2$IdProb,by=list(IdC2$IdExtrap),FUN=function(x) ceiling((1-max(x-0.0001))*100))
barplot(RisqueErreurT$x,names.arg=RisqueErreurT$Group.1,las=2)
#compute error risk accoring to observer/validator (a little dirty because it relies on alphabetical order of confidence classes: POSSIBLE < PROBABLE < SUR)
RisqueErreurOV0=match(IdC2$ConfV,EchelleErreur)
RisqueErreurOV=aggregate(RisqueErreurOV0,by=list(IdC2$IdExtrap)
                         ,FUN=max) 
RisqueErreurOV2=EchelleNumErreur[RisqueErreurOV$x]
#compute minimum error risk between man and machine
RisqueErreur=pmin(RisqueErreurT$x,RisqueErreurOV2)

#compute number of files validated per species
FichValid=aggregate(IdC2$IdV,by=list(IdC2$IdExtrap,IdC2$'nom du fichier')
                                 ,FUN=function(x) sum(x!="")) 
NbValid2=aggregate(FichValid$x,by=list(FichValid$Group.1),FUN=function(x) sum(x>0))

DiffC50=vector() # to store the median of confidence difference between unvalidated records and validated ones
DiffT50=vector() # to store the median of time difference between unvalidated records and validated ones
for (j in 1:nlevels(as.factor(IdC2$IdExtrap)))
{
  IdSp=subset(IdC2
              ,IdC2$IdExtrap==levels(as.factor(IdC2$IdExtrap))[j])
  IdSp=IdSp[order(IdSp$IdProb),]
  IdSpV=subset(IdSp,IdSp$IdV!="")
  if(nrow(IdSpV)>0)
  {
  cuts <- c(-Inf, IdSpV$IdProb[-1]-diff(IdSpV$IdProb)/2, Inf)
  CorrC=findInterval(IdSp$IdProb, cuts)
  CorrC2=IdSpV$IdProb[CorrC]
  DiffC=abs(IdSp$IdProb-CorrC2)
  DiffC50=c(DiffC50,median(DiffC))
  
  IdSp=IdSp[order(IdSp$TimeNum),]
  IdSpV=subset(IdSp,IdSp$IdV!="")
  cuts <- c(-Inf, IdSpV$TimeNum[-1]-diff(IdSpV$TimeNum)/2, Inf)
  CorrT=findInterval(IdSp$TimeNum, cuts)
  CorrT2=IdSpV$TimeNum[CorrT]
  DiffT=abs(IdSp$TimeNum-CorrT2)
  DiffT50=c(DiffT50,median(DiffT))
  }else{
    DiffC50=c(DiffC50,Inf)
    DiffT50=c(DiffT50,Inf)
  }
}
#compute an index of validation effort per species
EffortV=1/DiffC50/DiffT50
EffortClass=(EffortV>0.0005)+(EffortV>0.005)+RisqueErreurOV$x
cbind(RisqueErreurOV,EffortV,DiffC50,DiffT50)
barplot(EffortClass-1,names.arg=NbValid2$Group.1,las=2)
ClassEffortV=c("-","FAIBLE","SUFFISANT","SUFFISANT","FORT","FORT")
EffortClassMot=ClassEffortV[EffortClass]


#get date-night
pourDateNuit=IdC2$TimeNum-12*3600 #bricolage-decalage de 12 heures pour ramener a la date du debut de nuit
DateNuit=as.Date.POSIXct(pourDateNuit) # date of the beginning of the night
DateJour=as.Date.POSIXct(IdC2$TimeNum) # date (UTC+0)
IdC2$DateNuit=DateNuit
IdC2$DateJour=DateJour
NbNuit=as.numeric(max(IdC2$DateNuit)-min(IdC2$DateNuit))+1

#compare activity / reference frame
ActMoy=aggregate(IdC2$`nom du fichier`
                 ,by=list(IdC2$IdExtrap),FUN=function(x) length(x)/NbNuit)
ListSpref=match(ActMoy$Group.1,refPF$Espece)
Subref=refPF[ListSpref]
QualifAct=vector()
for (k in 1:nrow(ActMoy))
{
  if(is.na(Subref$Q25[k]))
  {
    QualifAct=c(QualifAct,NA)
  }else{
    cuts=cbind(-Inf,as.numeric(Subref$Q25[k]),as.numeric(Subref$Q75[k])
               ,as.numeric(Subref$Q98[k]),Inf)
  
    QualifAct=c(QualifAct,findInterval(ActMoy$x[k],cuts,left.open=T))
  }
}
ClassAct=c("FAIBLE","MODEREE","FORTE","TRES FORTE")
QualifActMot=ClassAct[QualifAct]

#compute activity by nights (to be completed)
#ActNuit=aggregate(IdC2$`nom du fichier`,by=list(IdC2$DateNuit,IdC2$IdExtrap),FUN=length)

#organize the csv summary
SummPart0=cbind(Esp=levels(as.factor(IdC2$IdExtrap))
                ,RisqueErreur,NbValid=NbValid2$x,EffortValid=EffortClassMot
                ,Contacts_Nuit=round(ActMoy$x),Niveau_Activite=QualifActMot)


InfoSp=c("GroupFR","NomFR","Scientific name","Esp")
GroupShort=GroupList[,InfoSp,with=FALSE]
#GroupShort=GroupList[,..InfoSp]
SummPart=merge(GroupShort,SummPart0,by="Esp")
IndexGroupe=c("Autre","Sauterelle","Chauve-souris")
SummPart$IndexSumm=match(SummPart$GroupFR,IndexGroupe)
SummPart=SummPart[with(SummPart
                       ,order(IndexSumm,as.numeric(Contacts_Nuit),decreasing=T)),]
colnames(SummPart)=c("Code","Groupe","Nom francais","Nom scientifique"
                     ,"Risque d'erreur (%)","Nb Validations"
                     ,"Effort de validation","Nb de Contacts par Nuit"
                     ,"Niveau d'Activite","TriGroupe")

#to do: extend colors to other columns to improve readability
SummHTML=datatable(SummPart, rownames = FALSE) %>%
  formatStyle(columns = c("Code","Groupe","Nom francais","Nom scientifique","Risque d'erreur (%)"),valueColumns="Risque d'erreur (%)", 
              background = styleInterval(c(1, 10, 50), c("white", "khaki", "orange", "orangered"))) %>%
  formatStyle(columns = "Effort de validation", 
              background = styleEqual(c("-","FAIBLE","SUFFISANT","FORT"), c("white", "cyan", "royalblue", "darkblue"))) %>%
  formatStyle(columns = c("Nb de Contacts par Nuit","Niveau d'Activite"),valueColumns="Niveau d'Activite",
              background = styleEqual(c("FAIBLE","MODEREE","FORTE","TRES FORTE"), c("palegoldenrod", "greenyellow", "limegreen", "darkgreen")))

saveWidget(SummHTML,"output-summary.html")
write.table(SummPart,"output-summary.tabular",sep="\t",row.names=F)

#compute number of files validated per night/hour
IdC2$Heure=sapply(IdC2$`nom du fichier`,FUN=function(x) substr(x,nchar(x)-9,nchar(x)-8))

ActNuit=aggregate(IdC2$`nom du fichier`,by=list(IdC2$IdExtrap,IdC2$Session),FUN=length)
ListSpref=match(ActNuit$Group.1,refPF$Espece)
Subref=refPF[ListSpref]


QualifActN=vector()
for (k in 1:nrow(ActNuit))
{
  if(is.na(Subref$Q25[k]))
  {
    QualifActN=c(QualifActN,NA)
  }else{
    cuts=cbind(-Inf,as.numeric(Subref$Q25[k]),as.numeric(Subref$Q75[k])
               ,as.numeric(Subref$Q98[k]),Inf)
    
    QualifActN=c(QualifActN,findInterval(ActNuit$x[k],cuts,left.open=T))
  }
}
ActNuit$QualifActN=QualifActN

ActNuitT=dcast(data=ActNuit,formula=Group.1~Group.2
              ,value.var="x")
ActNuitT[is.na(ActNuitT)]=0
RefNuitT=dcast(data=ActNuit,formula=Group.1~Group.2
               ,value.var="QualifActN")
ARNuit=merge(ActNuitT,RefNuitT,by="Group.1")

SummPartshort=cbind(SummPart[,c(1:5)],TriGroupe=SummPart[,TriGroupe])
SummPartN=merge(SummPartshort,ARNuit,by.x="Code",by.y="Group.1")
SummPartN=SummPartN[order(TriGroupe,decreasing=T),]

test=grepl(".x",colnames(SummPartN))
colnames(SummPartN)=mapply(FUN=function(x,y) if(y){substr(x,1,2)}else{x}
                           ,colnames(SummPartN),test)
ListNuit=subset(colnames(SummPartN),test)
ListRef=subset(colnames(SummPartN),grepl(".y",colnames(SummPartN)))
testHide=match(ListRef,colnames(SummPartN))-1
#to do: extend colors to other columns to improve readability
SummHTMLN=datatable(SummPartN, rownames = FALSE,options = list(
  columnDefs = list(list(targets = testHide,visible = FALSE)))) %>%
  formatStyle(columns = c("Code","Groupe","Nom francais","Nom scientifique","Risque d'erreur (%)"),valueColumns="Risque d'erreur (%)", 
              background = styleInterval(c(1, 10, 50), c("white", "khaki", "orange", "orangered"))) %>%
  formatStyle(columns = ListNuit,valueColumns=ListRef, 
              background = styleEqual(c(1,2,3,4), c("palegoldenrod", "greenyellow", "limegreen", "darkgreen")))

saveWidget(SummHTMLN,"output-nightly.html")
write.table(SummPartN,"output-nightly.tabular",sep="\t",row.names=F)


#summary by hour
ActMoyH=dcast(data=IdC2,formula=IdExtrap~Heure
              ,fun.aggregate=length)
ActMoyHA=aggregate(IdC2$`nom du fichier`
                   ,by=list(IdC2$IdExtrap,IdC2$Heure)
                   ,FUN=length)

test=(as.numeric(colnames(ActMoyH))>12)
ColDebut=subset(colnames(ActMoyH),test)
ColFin=subset(colnames(ActMoyH),test==F)
ListH=c(ColDebut,ColFin)
neworder=c("IdExtrap",ColDebut,ColFin)
ActMoyH=ActMoyH[,..neworder]

SummPartH=merge(SummPartshort,ActMoyH,by.x="Code",by.y="IdExtrap")
SummPartH=SummPartH[order(TriGroupe,decreasing=T),]


brks <- quantile(ActMoyHA$x, probs = seq(.05, .95, .05), na.rm = TRUE)-1
clrs <- round(seq(255, 40, length.out = length(brks) + 1), 0) %>%
{paste0("rgb(255,", ., ",", ., ")")}


SummHTMLH=datatable(SummPartH, rownames = FALSE) %>%
  formatStyle(columns = c("Code","Groupe","Nom francais","Nom scientifique","Risque d'erreur (%)"),valueColumns="Risque d'erreur (%)", 
              background = styleInterval(c(1, 10, 50), c("white", "khaki", "orange", "orangered"))) %>%
  formatStyle(columns=ListH, backgroundColor = styleInterval(brks, clrs))

saveWidget(SummHTMLH,"output-hourly.html")
write.table(SummPartH,"output-hourly.tabular",sep="\t",row.names=F)


#saveWidget(SummHTML,paste0(substr(args[1],1,nchar(args[1])-9),"-summary.html"))
#write.table(SummPart,paste0(substr(args[1],1,nchar(args[1])-9),"-summary.csv"),sep="\t",row.names=F)
#saveWidget(SummHTMLN,paste0(substr(args[1],1,nchar(args[1])-9),"-nightly.html"))
#write.table(SummPartN,paste0(substr(args[1],1,nchar(args[1])-9),"-nightly.csv"),sep="\t",row.names=F)
#saveWidget(SummHTMLH,paste0(substr(args[1],1,nchar(args[1])-9),"-hourly.html"))
#write.table(SummPartH,paste0(substr(args[1],1,nchar(args[1])-9),"-hourly.csv"),sep="\t",row.names=F)


}