Mercurial > repos > ecology > vigiechiro_bilanenrichipf
view BilanEnrichiPF.R @ 2:911f80dce38d draft default tip
planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/vigiechiro commit 4707473e9991d095310f475a54e041c95accd873
author | ecology |
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date | Wed, 05 Jun 2019 13:48:45 -0400 |
parents | 775809e2f6c8 |
children |
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#!/usr/bin/env Rscript args <- commandArgs(trailingOnly = TRUE) #print(args) EchelleErreur=c("","POSSIBLE","PROBABLE","SUR") EchelleNumErreur=c(99,50,10,1) suppressMessages(library(data.table)) suppressMessages(library(DT)) suppressMessages(library(htmlwidgets)) f2p <- function(x) #get date-time data from recording file names { if (is(x)[1] == "data.frame") {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 } IdC2=fread(args[1],encoding="UTF-8") if(substr(IdC2$`nom du fichier`[1],2,2)!="a") { # print("Protocole non conforme, ce script doit etre lance uniquement pour un protocole Point Fixe") print("Wrong protocol, please only use this tool for a \'Point Fixe\' protocol.") }else{ refPF=fread(args[2],encoding="UTF-8") GroupList=fread(args[3],encoding="UTF-8") IdC2$ConfV[is.na(IdC2$ConfV)]="" #compute error risk by species (minimum error among files) #to be replaced by glm outputs if I'll have time RisqueErreurT=aggregate(IdC2$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$IdExtrap))[j]) IdSp=IdSp[order(IdSp$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-16*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] #organize the csv summary SummPart0=cbind(Esp=levels(as.factor(IdC2$IdExtrap)) ,RisqueErreur,NbValid=NbValid2$x,EffortValid=EffortClassMot ,Contacts_Nuit=round(ActMoy$x),Niveau_Activite=QualifActMot) InfoSp=c("GroupFR","NomFR","Scientific name","Esp") GroupShort=GroupList[,..InfoSp] SummPart=merge(GroupShort,SummPart0,by="Esp") IndexGroupe=c("Autre","Sauterelle","Chauve-souris") SummPart$IndexSumm=match(SummPart$GroupFR,IndexGroupe) SummPart=SummPart[with(SummPart ,order(IndexSumm,as.numeric(Contacts_Nuit),decreasing=T)),] colnames(SummPart)=c("Code","Groupe","Nom francais","Nom scientifique" ,"Risque d'erreur (%)","Nb Validations" ,"Effort de validation","Nb de Contacts par Nuit" ,"Niveau d'Activite","TriGroupe") #to do: extend colors to other columns to improve readability SummHTML=datatable(SummPart, rownames = FALSE) %>% formatStyle(columns = c("Code","Groupe","Nom francais","Nom scientifique","Risque d'erreur (%)"),valueColumns="Risque d'erreur (%)", background = styleInterval(c(1, 10, 50), c("white", "khaki", "orange", "orangered"))) %>% formatStyle(columns = "Effort de validation", background = styleEqual(c("-","FAIBLE","SUFFISANT","FORT"), c("white", "cyan", "royalblue", "darkblue"))) %>% formatStyle(columns = c("Nb de Contacts par Nuit","Niveau d'Activite"),valueColumns="Niveau d'Activite", background = styleEqual(c("FAIBLE","MODEREE","FORTE","TRES FORTE"), c("palegoldenrod", "greenyellow", "limegreen", "darkgreen"))) saveWidget(SummHTML,"output-summary.html") # write.csv2(SummPart,"output-summary.tabular",row.names=F) write.table(SummPart,"output-summary.tabular",row.names=F,sep="\t") #compute number of files validated per night/hour IdC2$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.csv2(SummPartN,"output-nightly.tabular",row.names=F) write.table(SummPartN,"output-nightly.tabular",row.names=F,sep="\t") #summary by hour ActMoyH=dcast(data=IdC2,formula=IdExtrap~Heure ,fun.aggregate=length) ActMoyHA=aggregate(IdC2$`nom du fichier` ,by=list(IdC2$IdExtrap,IdC2$Heure) ,FUN=length) test=(as.numeric(colnames(ActMoyH))>16) ColDebut=subset(colnames(ActMoyH),test) ColFin=subset(colnames(ActMoyH),test==F) ListH=c(ColDebut,ColFin) neworder=c("IdExtrap",ColDebut,ColFin) ActMoyH=ActMoyH[,..neworder] SummPartH=merge(SummPartshort,ActMoyH,by.x="Code",by.y="IdExtrap") SummPartH=SummPartH[order(TriGroupe,decreasing=T),] brks <- quantile(ActMoyHA$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.csv2(SummPartH,"output-hourly.tabular",row.names=F) write.table(SummPartH,"output-hourly.tabular",row.names=F,sep="\t") }