# HG changeset patch
# User ecology
# Date 1556295652 14400
# Node ID f3fc8d243b1a780dc34f6f71a67a46e70ba97b9b
# Parent 6681b6ba1d7eec08122a45dcc3aa0bb67e2bd03b
planemo upload for repository https://github.com/galaxyecology/tools-ecology/tools/vigiechiro commit 7ef0e58cbcbf41088e359f00b6c86504c773c271
diff -r 6681b6ba1d7e -r f3fc8d243b1a ClassifEspC2b_180222.learner
Binary file ClassifEspC2b_180222.learner has changed
diff -r 6681b6ba1d7e -r f3fc8d243b1a IdCorrect_2ndLayer.R
--- a/IdCorrect_2ndLayer.R Wed Mar 13 11:18:36 2019 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,181 +0,0 @@
-#!/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$ProbEsp_C2bs)]="empty"
-
-fout_name="output.tabular"
-
-write.table(DataCorrC2,file=fout_name,row.names=FALSE,sep="\t",quote=FALSE,na="NA")
diff -r 6681b6ba1d7e -r f3fc8d243b1a IdCorrect_2ndLayer_en.xml
--- a/IdCorrect_2ndLayer_en.xml Wed Mar 13 11:18:36 2019 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,68 +0,0 @@
-
- clean data from animal detection on acoustic recordings
-
- vigiechiro_macros.xml
-
-
- r-data.table
- r-randomforest
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff -r 6681b6ba1d7e -r f3fc8d243b1a IdTidyen.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/IdTidyen.xml Fri Apr 26 12:20:52 2019 -0400
@@ -0,0 +1,47 @@
+
+ clean data from animal detection on acoustic recordings
+
+ vigiechiro_macros.xml
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff -r 6681b6ba1d7e -r f3fc8d243b1a Id_Tidy.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/Id_Tidy.R Fri Apr 26 12:20:52 2019 -0400
@@ -0,0 +1,17 @@
+suppressMessages(library(data.table))
+
+args <- commandArgs(trailingOnly = TRUE)
+#print(args)
+filename=args[2]
+
+DataPar=fread(args[1]) #ids
+DataPar$participation=substr(filename,nchar(filename)-40,nchar(filename)-17)
+#DataPar$participation=substr(args[1],nchar(args[1])-40,nchar(args[1])-17)
+test1=duplicated(cbind(DataPar$'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)
+
+#write.table(DataPar,paste0(substr(args[1],nchar(args[1])-40,nchar(args[1])-17),"-DataCorrC2.csv"),row.names=F,sep="\t")
+write.table(DataPar,"Id_tidy.tabular",row.names=F,sep="\t")
diff -r 6681b6ba1d7e -r f3fc8d243b1a test-data/IdCor2Layer_Test1_obs.csv
--- a/test-data/IdCor2Layer_Test1_obs.csv Wed Mar 13 11:18:36 2019 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,1120 +0,0 @@
-"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";"";"";"";""
-"Car470026-2017-Pass1-Z1-CEN2-S2U17907_20170620_214303_165";"0.0";0.4;9.0;"piaf";0.492;"Phogri";"";"";"";""
-"Car470026-2017-Pass1-Z1-CEN2-S2U17907_20170620_220943_339";"0.0";2.1;10.0;"Tetvir";0.632;"noise";"";"";"";""
-"Car470026-2017-Pass1-Z1-CEN2-S2U17907_20170620_220946_143";"0.0";2.1;10.0;"Tetvir";0.686;"";"";"";"";""
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-"Car470026-2017-Pass1-Z1-CEN2-S2U17907_20170620_221137_981";"0.0";5.0;10.0;"Tetvir";0.682;"noise";"";"";"";""
-"Car470026-2017-Pass1-Z1-CEN2-S2U17907_20170620_221142_981";"0.0";5.0;10.0;"Tetvir";0.724;"noise";"";"";"";""
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diff -r 6681b6ba1d7e -r f3fc8d243b1a test-data/IdCor2Layer_Test1_out.tabular
--- a/test-data/IdCor2Layer_Test1_out.tabular Wed Mar 13 11:18:36 2019 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,1120 +0,0 @@
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diff -r 6681b6ba1d7e -r f3fc8d243b1a test-data/input_tidy_test1_obs.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/input_tidy_test1_obs.csv Fri Apr 26 12:20:52 2019 -0400
@@ -0,0 +1,1838 @@
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diff -r 6681b6ba1d7e -r f3fc8d243b1a test-data/output_tidy.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_tidy.tabular Fri Apr 26 12:20:52 2019 -0400
@@ -0,0 +1,1837 @@
+"nom du fichier" "temps_debut" "temps_fin" "frequence_mediane" "tadarida_taxon" "tadarida_probabilite" "tadarida_taxon_autre" "observateur_taxon" "observateur_probabilite" "validateur_taxon" "validateur_probabilite" "participation"
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+"Cir750016-2016-Pass1-Tron1-Chiro_0_00010_000" 0.3 0.5 98 "noise" 0.88 "" NA NA NA NA "input_t"
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+"Cir750016-2016-Pass1-Tron1-Chiro_0_00020_000" 0.1 0.2 106 "noise" 0.51 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron1-Chiro_0_00025_000" 0 0.3 93 "noise" 0.36 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron1-Chiro_0_00030_000" 0.2 0.5 103 "noise" 0.98 "" NA NA NA NA "input_t"
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+"Cir750016-2016-Pass1-Tron9-Chiro_1_00055_000" 3.6 5 9 "noise" 0.84 "" NA NA NA NA "input_t"
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+"Cir750016-2016-Pass1-Tron9-Chiro_1_00070_000" 0.6 4.5 9 "noise" 0.97 "" NA NA NA NA "input_t"
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+"Cir750016-2016-Pass1-Tron9-Chiro_1_00090_000" 2.9 4.1 10 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00095_000" 1 5 9 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00100_000" 1 3.8 9 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00105_000" 0.4 5 12 "noise" 0.89 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00110_000" 0.3 4.9 14 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00115_000" 0 1.6 15 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00120_000" 1.6 2.9 11 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00125_000" 1 4 9 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00130_000" 0.6 1.9 9 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00135_000" 0.2 2.3 10 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00140_000" 4.1 4.5 10 "noise" 0.74 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00140_000" 4.2 4.3 14 "Pipkuh" 0.03 "Tetvir, Phogri, mamm" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00145_000" 1.7 4.6 9 "noise" 0.92 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00150_000" 0.8 2.2 12 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00155_000" 0.3 4.6 10 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00160_000" 0.7 4.2 14 "noise" 0.94 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00165_000" 3 3.1 10 "noise" 0.92 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00170_000" 0.7 4.7 10 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00175_000" 1.8 4.5 9 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00180_000" 0.8 4.9 10 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00180_000" 2.3 2.4 13 "Pipkuh" 0.04 "Tadten, Tetvir" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00185_000" 0.3 4.9 10 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00190_000" 0 3.2 9 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00190_000" 2.6 2.7 13 "Tetvir" 0.02 "Pipkuh, Yerray, Yerbey, Vesmur, Urosp, Tyllil, Thycor, Tetpyg, Tetarg, Testes, Tadten, Sepsep, Rusnit, Roeroe, Rhihip, Rhifer, Rhieur, Ratnor, Plemac, Pleaus, Pleaur, Plasab, Plaint, Plafal, Plaalb, Plaaff, Pippyg, Pippip, Pipnat, piaf, Phogri, Phofem, Phanan, Phafal, Nycnoc, Nyclei, Nyclas, Myonat, Myomys, MyoGT, Myoema, Myodau, Myodas, Myocap, Myobec, Myoalc, Mussp, Minsch, Micagr, Metbra, mamm, Leppun, Lepbos, Lepalb, Lamsp., Isopyr, Inssp8, Inssp7, Inssp5, Insp12, Insp11, Insp10, Hypsav, gril, Eupsp, Eptser, Eptnil, Epheph, Decalb, Cyrscu, Cympud, criq, Confus, Tetarg, Barfis, Barbar, amph" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00195_000" 1.6 1.7 25 "noise" 0.54 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00195_000" 1.8 3.7 13 "Pipkuh" 0.03 "Tetvir, Tadten, Rusnit, Pippip" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00200_000" 1.4 4.6 9 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00205_000" 1.3 4.4 11 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00210_000" 0.4 3.3 11 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00215_000" 0 4.3 10 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00220_000" 0.7 1.2 10 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00225_000" 0.3 5 21 "noise" 0.91 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00230_000" 0.5 4.9 9 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00235_000" 0.1 2.5 10 "noise" 0.17 "Phogri, Eupsp" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00240_000" 1.3 4.3 9 "noise" 0.26 "Phogri" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00245_000" 4.3 4.7 11 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00255_000" 0.3 3.4 18 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00260_000" 2.9 3 14 "noise" 0.95 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00265_000" 1.6 3.3 14 "noise" 0.92 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00265_000" 1.6 1.7 22 "Tetvir" 0.02 "Pippip, Nyclei, Yerray, Yerbey, Vesmur, Urosp, Tyllil, Thycor, Tetpyg, Tetarg, Testes, Tadten, Sepsep, Rusnit, Roeroe, Rhihip, Rhifer, Rhieur, Ratnor, Plemac, Pleaus, Pleaur, Plasab, Plaint, Plafal, Plaalb, Plaaff, Pippyg, Pipnat, Pipkuh, piaf, Phogri, Phofem, Phanan, Phafal, Nycnoc, Nyclas, Myonat, Myomys, MyoGT, Myoema, Myodau, Myodas, Myocap, Myobec, Myoalc, Mussp, Minsch, Micagr, Metbra, mamm, Leppun, Lepbos, Lepalb, Lamsp., Isopyr, Inssp8, Inssp7, Inssp5, Insp12, Insp11, Insp10, Hypsav, gril, Eupsp, Eptser, Eptnil, Epheph, Decalb, Cyrscu, Cympud, criq, Confus, Tetarg, Barfis, Barbar, amph" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00270_000" 0.6 4.3 11 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00275_000" 3.7 3.8 10 "noise" 0.96 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00280_000" 1.8 4.3 13 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00285_000" 0.5 4.8 16 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00290_000" 0.7 0.8 15 "noise" 0.93 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00295_000" 3.5 4.7 10 "noise" 0.91 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00300_000" 0.3 4.9 12 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00305_000" 0.2 5 16 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00310_000" 0 4.7 15 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00310_000" 1.9 2.2 44 "Pippip" 0.84 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00315_000" 0.9 5 11 "noise" 0.9 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00320_000" 1.8 5 18 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00325_000" 0.6 4.9 18 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00330_000" 0.1 4.5 16 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00335_000" 0.7 4.9 10 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00340_000" 1.7 5 22 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00345_000" 0.1 4.9 10 "noise" 0.98 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00345_000" 1.8 3.7 10 "Tetvir" 0.32 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00350_000" 0.1 4.7 10 "noise" 0.99 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00355_000" 1.4 4.6 10 "noise" 0.97 "" NA NA NA NA "input_t"
+"Cir750016-2016-Pass1-Tron9-Chiro_1_00360_000" 0.2 0.9 14 "noise" 0.9 "" NA NA NA NA "input_t"
diff -r 6681b6ba1d7e -r f3fc8d243b1a vigiechiro_macros.xml
--- a/vigiechiro_macros.xml Wed Mar 13 11:18:36 2019 -0400
+++ b/vigiechiro_macros.xml Fri Apr 26 12:20:52 2019 -0400
@@ -1,5 +1,5 @@
- 0.1.0
+ 0.1.1
@@ -28,13 +28,16 @@
10.5334/jors.154
-
+
- r-reshape2
- r-data.table
- r-dt
- r-htmlwidgets
- pandoc
-
+ r-data.table
+
+
+
+
+ r-reshape2
+ r-dt
+ r-htmlwidgets
+ pandoc