# HG changeset patch
# User ecology
# Date 1552490316 14400
# Node ID 6681b6ba1d7eec08122a45dcc3aa0bb67e2bd03b
planemo upload for repository https://github.com/galaxyecology/tools-ecology/tools/vigiechiro commit d2de8e10c11bfa3b04729e59bba58e08d23b56aa
diff -r 000000000000 -r 6681b6ba1d7e ClassifEspC2b_180222.learner
Binary file ClassifEspC2b_180222.learner has changed
diff -r 000000000000 -r 6681b6ba1d7e IdCorrect_2ndLayer.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/IdCorrect_2ndLayer.R Wed Mar 13 11:18:36 2019 -0400
@@ -0,0 +1,181 @@
+#!/usr/bin/env Rscript
+
+suppressMessages(library(data.table))
+suppressMessages(library(randomForest))
+args <- commandArgs(trailingOnly = TRUE)
+
+set.seed(1) #To test reproductibility
+
+filename=args[3]
+if (exists("ClassifEspC2b")==F){load(args[2])}
+
+DataPar=fread(args[1],na.strings="") #id to be corrected
+DataPar$participation=substr(filename,nchar(filename)-40,nchar(filename)-17)
+test1=duplicated(cbind(DataPar$'nom du fichier',DataPar$tadarida_taxon))
+test2=(DataPar$tadarida_taxon=="empty")
+DataPar=subset(DataPar,(!test1)|(test2))
+DataPar$tadarida_probabilite[DataPar$tadarida_probabilite==""]="0"
+DataPar$tadarida_probabilite=as.numeric(DataPar$tadarida_probabilite)
+
+
+#table counting number of contacts per species
+nbcT=as.matrix(table(DataPar$participation,DataPar$tadarida_taxon))
+
+DataPar$tadarida_probabilite=as.numeric(DataPar$tadarida_probabilite)
+
+#generating input variables for second layer classification
+
+Q25=vector()
+Q50=vector()
+Q75=vector()
+Q90=vector()
+Q95=vector()
+Q98=vector()
+Q100=vector()
+compt=0
+PropSp=nbcT[0,]
+VoteO=DataPar[0,]
+for (j in 1:nlevels(as.factor(DataPar$tadarida_taxon)))
+ {
+ Datasub2=subset(DataPar,DataPar$tadarida_taxon==levels(as.factor(DataPar$tadarida_taxon))[j])
+
+ Q25=c(Q25,rep(quantile(Datasub2$tadarida_probabilite,0.25),nrow(Datasub2)))
+ Q50=c(Q50,rep(quantile(Datasub2$tadarida_probabilite,0.50),nrow(Datasub2)))
+ Q75=c(Q75,rep(quantile(Datasub2$tadarida_probabilite,0.75),nrow(Datasub2)))
+ Q90=c(Q90,rep(quantile(Datasub2$tadarida_probabilite,0.90),nrow(Datasub2)))
+ Q95=c(Q95,rep(quantile(Datasub2$tadarida_probabilite,0.95),nrow(Datasub2)))
+ Q98=c(Q98,rep(quantile(Datasub2$tadarida_probabilite,0.98),nrow(Datasub2)))
+ Q100=c(Q100,rep(max(Datasub2$tadarida_probabilite),nrow(Datasub2)))
+ Ncont1=nrow(Datasub2)
+ VoteO=rbind(VoteO,Datasub2)
+ PropSp0=nbcT/Ncont1
+ PropSp=rbind(PropSp,PropSp0[rep(seq_len(nrow(PropSp0)),nrow(Datasub2)),])
+ compt=compt+nrow(Datasub2)
+ #print(paste(compt,levels(as.factor(DataPar$tadarida_taxon))[j]))
+ }
+
+VoteC2=cbind(VoteO,PropSp,Q25,Q50,Q75,Q90,Q95,Q98,Q100)
+
+
+#editing column titles to identify var of type "proportion d'abondances"
+for (i in 15:(ncol(VoteC2)-7))
+{
+ colnames(VoteC2)[i]=paste0(names(VoteC2)[i],"_prop")
+}
+
+#Add missing species
+EspForm=subset(row.names(ClassifEspC2b$importance)
+ ,substr(row.names(ClassifEspC2b$importance)
+ ,nchar(row.names(ClassifEspC2b$importance))-4
+ ,nchar(row.names(ClassifEspC2b$importance)))
+ =="_prop")
+test=match(EspForm,colnames(VoteC2))
+EspM=subset(EspForm,is.na(test))
+Zeros=matrix(nrow=nrow(VoteC2),ncol=length(EspM))
+Zeros[is.na(Zeros)]=0
+colnames(Zeros)=EspM
+VoteC2=cbind(VoteC2,Zeros)
+
+ListDV=levels(as.factor(DataPar$'nom du fichier'))
+#calcule les probabilités max par espèce et par fichier
+#(utile pour corriger les erreurs dues à la coexistence de taxons dans le même fichier
+#ex: cris sociaux de Pipistrelles identifiées comme autre chose (Noctule, oreillard...))
+#comptue max proba per species and files
+#(useful to correct errors that came from multiple taxons in the same file
+#eg ; Pipistrelles socials shouting identified as something else (Noctule, oreillard..))
+
+MaxI=tapply(DataPar$tadarida_probabilite
+ ,INDEX=list(c(DataPar$'nom du fichier'),c(DataPar$tadarida_taxon))
+ ,FUN=max)
+MaxI2=as.data.frame(cbind(row.names(MaxI),MaxI))
+for (i in 2:ncol(MaxI2))
+{
+ MaxI2[,i]=as.numeric(as.character(MaxI2[,i]))
+}
+MaxI2[is.na(MaxI2)]=0
+
+#édition des titres de colonne pour identifier les variables de type "indices max"
+#editing col titles to identify "indices max" variables
+for (i in 2:(ncol(MaxI2)))
+{
+ colnames(MaxI2)[i]=paste0(names(MaxI2)[i],"_maxI")
+}
+
+
+#add missing species
+EspForm=subset(row.names(ClassifEspC2b$importance)
+ ,substr(row.names(ClassifEspC2b$importance)
+ ,nchar(row.names(ClassifEspC2b$importance))-4
+ ,nchar(row.names(ClassifEspC2b$importance)))
+ =="_maxI")
+test=match(EspForm,colnames(MaxI2))
+EspM=subset(EspForm,is.na(test))
+Zeros=matrix(nrow=nrow(MaxI2),ncol=length(EspM))
+Zeros[is.na(Zeros)]=0
+colnames(Zeros)=EspM
+MaxI2=cbind(MaxI2,Zeros)
+
+
+
+
+#indice de confiance à l'echelle de l'observation (groupe de cris identifié comme provenant d'une seule espèce par la première couche)
+#Confidence indice on obs scale (shoutings groups identified as comming from a single species from the first layer)
+if(exists("IdS3")){rm(IdS3)}
+for (i in 1:nlevels(as.factor(DataPar$tadarida_taxon)))
+{
+ Idsub=subset(DataPar,DataPar$tadarida_taxon==levels(as.factor(DataPar$tadarida_taxon))[i])
+ IdS2=cbind('nom du fichier'=Idsub$'nom du fichier',tadarida_taxon=Idsub$tadarida_taxon,prob=Idsub$tadarida_probabilite)
+ colnames(IdS2)[3]=paste(levels(as.factor(DataPar$tadarida_taxon))[i])
+ if(exists("IdS3")){IdS3=merge(IdS3,IdS2,all=T)}else{IdS3=IdS2}
+}
+
+for (i in 3:ncol(IdS3))
+{
+ IdS3[,i]=as.numeric(as.character(IdS3[,i]))
+}
+
+#édition des titres de colonne pour identifier les variables de type "indices de l'observation"
+#editing col titles to identify "indices de l'observation" variables
+for (i in 3:(ncol(IdS3)))
+{
+ colnames(IdS3)[i]=paste0(names(IdS3)[i],"_ValI")
+}
+
+IdS3[is.na(IdS3)]=0
+
+#add missing species
+EspForm=subset(row.names(ClassifEspC2b$importance)
+ ,substr(row.names(ClassifEspC2b$importance)
+ ,nchar(row.names(ClassifEspC2b$importance))-4
+ ,nchar(row.names(ClassifEspC2b$importance)))
+ =="_ValI")
+test=match(EspForm,colnames(IdS3))
+EspM=subset(EspForm,is.na(test))
+Zeros=matrix(nrow=nrow(IdS3),ncol=length(EspM))
+Zeros[is.na(Zeros)]=0
+colnames(Zeros)=EspM
+IdS3=cbind(IdS3,Zeros)
+
+#on merge les prop d'espèces, les quantiles et les indices par fichiers et par observations
+#merge species probabilities, quantiles and indice per files and per obs
+VoteC3=merge(VoteC2,MaxI2,by.x="nom du fichier",by.y="V1")
+VoteC4=merge(VoteC3,IdS3,by=c("nom du fichier","tadarida_taxon"))
+VoteC4$temps_fin=as.numeric(as.character(VoteC4$temps_fin))
+VoteC4$temps_debut=as.numeric(as.character(VoteC4$temps_debut))
+VoteC4$frequence=as.numeric(as.character(VoteC4$frequence_mediane))
+VoteC4$durseq=VoteC4$temps_fin-VoteC4$temps_debut
+
+ProbEsp_C2b=predict(ClassifEspC2b,VoteC4,type="prob",norm.votes=TRUE)
+ProbEsp_C2bs=predict(ClassifEspC2b,VoteC4,type="response",norm.votes=TRUE)
+
+colnum=match("participation",colnames(VoteC4))
+DataCorrC2=cbind(VoteC4[,1:colnum],ProbEsp_C2b,ProbEsp_C2bs)
+DataCorrC2=DataCorrC2[order(DataCorrC2$tadarida_probabilite,decreasing=T),]
+DataCorrC2=DataCorrC2[order(DataCorrC2$'nom du fichier'),]
+
+DataCorrC2$ProbEsp_C2bs=as.character(DataCorrC2$ProbEsp_C2bs)
+DataCorrC2$ProbEsp_C2bs[is.na(DataCorrC2$ProbEsp_C2bs)]="empty"
+
+fout_name="output.tabular"
+
+write.table(DataCorrC2,file=fout_name,row.names=FALSE,sep="\t",quote=FALSE,na="NA")
diff -r 000000000000 -r 6681b6ba1d7e IdCorrect_2ndLayer_en.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/IdCorrect_2ndLayer_en.xml Wed Mar 13 11:18:36 2019 -0400
@@ -0,0 +1,68 @@
+
+ clean data from animal detection on acoustic recordings
+
+ vigiechiro_macros.xml
+
+
+ r-data.table
+ r-randomforest
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff -r 000000000000 -r 6681b6ba1d7e test-data/IdCor2Layer_Test1_obs.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/IdCor2Layer_Test1_obs.csv Wed Mar 13 11:18:36 2019 -0400
@@ -0,0 +1,1120 @@
+"nom du fichier";"temps_debut";"temps_fin";"frequence_mediane";"tadarida_taxon";"tadarida_probabilite";"tadarida_taxon_autre";"observateur_taxon";"observateur_probabilite";"validateur_taxon";"validateur_probabilite"
+"Car470026-2017-Pass1-Z1-CEN2-S2U17907_20170620_212736_466";"0.0";3.4;8.0;"noise";0.54;"piaf, Tetvir, Tadten, Phogri";"";"";"";""
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diff -r 000000000000 -r 6681b6ba1d7e test-data/IdCor2Layer_Test1_out.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/IdCor2Layer_Test1_out.tabular Wed Mar 13 11:18:36 2019 -0400
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diff -r 000000000000 -r 6681b6ba1d7e vigiechiro_macros.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/vigiechiro_macros.xml Wed Mar 13 11:18:36 2019 -0400
@@ -0,0 +1,40 @@
+
+ 0.1.0
+
+
+
+ @article{kerbiriou2015vigie,
+ title={Vigie-Chiro: 9 ans de suivi des tendances des esp{\`e}ces communes},
+ author={Kerbiriou, C and Julien, JF and Bas, Y and Marmet, J and Le Viol, I and Lorrilliere, R and Azam, C and Gasc, A and Lois, G},
+ journal={Symbioses, nouvelle s{\'e}rie},
+ number={34},
+ year={2015}
+ }
+
+
+ @inproceedings{bas2013automatic,
+ title={Automatic echolocation calls identification in Europe vs. Neotropics: more species does not mean more difficult},
+ author={Bas, Yves and Escallon, Antoine and Ferre, Matthieu and Haquart, Alexandre and Rufray, Vincent and Disca, Thierry and Julien, Jean-Fran{\c{c}}ois}
+ }
+
+
+ @inproceedings{kerbiriou2010long,
+ title={Long term trends monitoring of bats, from biodiversity indicator production to species specialization assessment},
+ author={Kerbiriou, C and Bas, Y and Dufr{\^e}ne, L and Robert, A and Julien, JF},
+ booktitle={24th Annual Meeting of the Society for Conservation Biology, Edmonton, Canada},
+ year={2010}
+ }
+
+ 10.5334/jors.154
+
+
+
+
+ r-reshape2
+ r-data.table
+ r-dt
+ r-htmlwidgets
+ pandoc
+
+
+