annotate BilanEnrichiRP.R @ 2:5ad79c210eb9 draft default tip

planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/vigiechiro commit 4707473e9991d095310f475a54e041c95accd873

#!/usr/bin/env Rscript

args <- commandArgs(trailingOnly = TRUE)

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

EchelleErreur=c("","POSSIBLE","PROBABLE","SUR")
EchelleNumErreur=c(99,50,10,1)

IdC2=fread(args[1],encoding="UTF-8")


if(substr(IdC2$`nom du fichier`[1],2,2)!="i")
{
#  print("Protocole non conforme, ce script doit etre lance uniquement pour un protocole Routier ou Pedestre")
  print("Wrong protocol, please only use this tool for a \'Pedestre\' or \'Routier\' protocol.")
}else{

  refRP=fread(args[2],encoding="UTF-8")
  GroupList=fread(args[3],encoding="UTF-8")
  
  IdC2$ConfV[is.na(IdC2$ConfV)]=""
  
    
  Routier=grepl("-",substr(IdC2$`nom du fichier`[1],4,7))
  #compute error risk by species (minimum error among files)
  #to be replaced by glm outputs if I'll have time
  RisqueErreurT=aggregate(IdC2$IdProb,by=list(IdC2$IdExtrap)
                          ,FUN=function(x) round((1-max(x))*100))
  barplot(RisqueErreurT$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$IdExtrap))[j])
    IdSp$IdProb[is.na(IdSp$IdProb)]=0
    IdSp=IdSp[order(IdSp$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]
  
  
  #compare activity / reference frame
  FileInfo=as.data.table(tstrsplit(IdC2$`nom du fichier`,"-"))
  IdC2$Tron=FileInfo$V4
  
  MicTempsInfo=as.data.table(tstrsplit(as.data.frame(FileInfo)[,(ncol(FileInfo))],"_"))
  MicDroit=(as.data.frame(MicTempsInfo)[,(ncol(MicTempsInfo)-2)]=="1")
  IdC2$MicDroit=MicDroit
  
  testTempsFin=aggregate(IdC2$temps_fin,by=list(MicDroit),FUN=max)
  testTempsFin$Direct=(testTempsFin$x>0.5)
  testTF2=sum((testTempsFin$x>0.5))
  if(testTF2>1){stop("Probleme stereo : les 2 canaux semblent etre en enregistrement direct")}
  IdC2M=merge(IdC2,testTempsFin,by.x="MicDroit",by.y="Group.1")
  
  ActMoy=aggregate(IdC2$`nom du fichier`
                   ,by=list(IdC2M$IdExtrap,IdC2M$Direct),FUN=length)
  ListSpref=match(levels(as.factor(ActMoy$Group.1)),refRP$Espece)
  Subref=refRP[ListSpref]
  if(Routier)
  {
    Subref=Subref[,c(1:17)]
  }else{
    Subref=Subref[,c(1,18:33)]
  }
  QualifActE=vector()
  QualifActD=vector()
  
  for (k in 1:nlevels(as.factor(ActMoy$Group.1)))
  {
    Actsub=subset(ActMoy,ActMoy$Group.1==levels(as.factor(ActMoy$Group.1))[k])
    if(is.na(Subref[k,2]))
    {
      QualifActE=c(QualifActE,NA)
      QualifActD=c(QualifActD,NA)
      }else{
        ActE=subset(Actsub,Actsub$Group.2==F)
        if(nrow(ActE)==0)
        {
          QualifActE=c(QualifActE,NA)
          
        }else{
          cuts=cbind(-Inf,as.numeric(Subref[k,6]),as.numeric(Subref[k,7])
                 ,as.numeric(Subref[k,8]),Inf)
          QualifActE=c(QualifActE,findInterval(ActE$x,cuts,left.open=T))
        }
        ActD=subset(Actsub,Actsub$Group.2==T)
        if(nrow(ActD)==0)
        {
          QualifActD=c(QualifActD,NA)
          
        }else{
          cuts=cbind(-Inf,as.numeric(Subref[k,14]),as.numeric(Subref[k,15])
                     ,as.numeric(Subref[k,16]),Inf)
          QualifActD=c(QualifActD,findInterval(ActD$x,cuts,left.open=T))
        }
        
        }
  }
  ClassAct=c("FAIBLE","MODEREE","FORTE","TRES FORTE")
  QualifActMotE=ClassAct[QualifActE]
  QualifActMotD=ClassAct[QualifActD]
  
  #compute activity by nights (to be completed)
  #ActNuit=aggregate(IdC2M$`nom du fichier`,by=list(IdC2M$DateNuit,IdC2M$IdExtrap),FUN=length)
  ActED=dcast(data=ActMoy,formula=Group.1~Group.2,value=x)
  ActED[is.na(ActED)]=0
  #organize the csv summary
  SummPart0=cbind(Esp=levels(as.factor(IdC2M$IdExtrap))
                  ,RisqueErreur,NbValid=NbValid2$x,EffortValid=EffortClassMot)
  
  test=match("FALSE",colnames(ActED))
  if(is.na(test)==F)
  {
    SummPart0=cbind(SummPart0,Contacts_Expansion=ActED$'FALSE'
                    ,Niveau_Activite_Expansion=QualifActMotE)
  }else{
    SummPart0=cbind(SummPart0,Contacts_Expansion=""
                    ,Niveau_Activite_Expansion="")
  }
  test=match("TRUE",colnames(ActED))
  if(is.na(test)==F)
  {
    
    SummPart0=cbind(SummPart0,Contacts_Direct=ActED$'TRUE'
                  ,Niveau_Activite_Direct=QualifActMotD)
  }else{
    SummPart0=cbind(SummPart0,Contacts_Direct=""
                    ,Niveau_Activite_Direct="")
  }
  
  InfoSp=c("GroupFR","NomFR","Scientific name","Esp")
  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_Direct),as.numeric(Contacts_Expansion),decreasing=T)),]
  colnames(SummPart)=c("Code","Groupe","Nom francais","Nom scientifique"
                     ,"Risque d'erreur (%)","Nb Validations"
                     ,"Effort de validation","Nb de Contacts en expansion"
                     ,"Niveau d'Activite en expansion"
                     ,"Nb de Contacts en direct"
                     ,"Niveau d'Activite en direct","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 en expansion","Niveau d'Activite en expansion"),valueColumns="Niveau d'Activite en expansion", 
              background = styleEqual(c("FAIBLE","MODEREE","FORTE","TRES FORTE"), c("palegoldenrod", "greenyellow", "limegreen", "darkgreen"))) %>%
  formatStyle(columns = c("Nb de Contacts en direct","Niveau d'Activite en direct"),valueColumns="Niveau d'Activite en direct", 
              background = styleEqual(c("FAIBLE","MODEREE","FORTE","TRES FORTE"), c("palegoldenrod", "greenyellow", "limegreen", "darkgreen")))


  saveWidget(SummHTML,"output-summaryRP.html")
  write.table(SummPart,"output-summaryRP.tabular",row.names=F,sep="\t")
  #write.csv2(SummPart,"output-summaryRP.tabular",row.names=F) #for testing
  
  #summary for each point/transect
  
  #compute number of files validated per species
  IdC2M$Canal=sapply(IdC2M$Direct,FUN=function(x) if(x){"Direct"}else{"Expansion"})
  
  ActMoyTA=aggregate(IdC2M$`nom du fichier`,by=list(IdC2M$IdExtrap,IdC2M$Canal,IdC2M$Session),FUN=length)
  ActMoyT=dcast(data=IdC2M,formula=IdExtrap+Canal~Session
                ,fun.aggregate=length)
  SummPartshort=cbind(SummPart[,c(1:5)],TriGroupe=SummPart[,TriGroupe])
  SummPartTron=merge(SummPartshort,ActMoyT,by.x="Code",by.y="IdExtrap")
  SummPartTron=SummPartTron[order(TriGroupe,decreasing=T),]
  
  ListSession=levels(as.factor(IdC2M$Session))
  brks <- quantile(ActMoyTA$x, probs = seq(.05, .95, .05), na.rm = TRUE)-1
  clrs <- round(seq(255, 40, length.out = length(brks) + 1), 0) %>%
  {paste0("rgb(255,", ., ",", ., ")")}
  
  
  #to do: extend colors to other columns to improve readability
  SummHTMLT=datatable(SummPartTron, 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=ListSession, backgroundColor = styleInterval(brks, clrs))

  saveWidget(SummHTMLT,"output-detailRP.html")
  write.table(SummPartTron,"output-detailRP.tabular",row.names=F,sep="\t")
#  write.csv2(SummPartTron,"output-detailRP.tabular",row.names=F)#for testing
}