diff --git a/RProject/Scripts/aggregation.R b/RProject/Scripts/aggregation.R
index b059396..41b1c20 100644
--- a/RProject/Scripts/aggregation.R
+++ b/RProject/Scripts/aggregation.R
@@ -531,6 +531,8 @@ compile_simulation2_rosali <- function(scenario) {
     flexible.detect <- prop.perfect
     moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0)  )
     moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:4)]%in%c(s[x,c("real_dif_1")]))/1)
+    percent.detect <- mean(percent.detect)
   }
   if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==2) {
     perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
@@ -540,6 +542,9 @@ compile_simulation2_rosali <- function(scenario) {
     moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
                                                               s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0)  )
     moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:4)]%in%c(s[x,c("real_dif_1","real_dif_2")]))/2)
+    percent.detect <- mean(percent.detect)
+    
   }
   if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==2) {
     perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
@@ -549,6 +554,8 @@ compile_simulation2_rosali <- function(scenario) {
     moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
                                                               s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0)  )
     moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:7)]%in%c(s[x,c("real_dif_1","real_dif_2")]))/2)
+    percent.detect <- mean(percent.detect)
   }
   if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==2) {
     perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) 
@@ -558,6 +565,8 @@ compile_simulation2_rosali <- function(scenario) {
     moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
                                                               s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
     moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:7)]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]))/3)
+    percent.detect <- mean(percent.detect)
   }
   z <- data.frame(m.beta=mean(s$beta),
                   se.empirical.beta=sd(s$beta),
@@ -571,7 +580,8 @@ compile_simulation2_rosali <- function(scenario) {
                   dif.detected=dif.d,
                   prop.perfect=prop.perfect,
                   flexible.detect=flexible.detect,
-                  moreflexible.detect=moreflexible.detect
+                  moreflexible.detect=moreflexible.detect,
+                  percent.detect=ifelse(name%%2==0,NA,percent.detect)
   )
   d <- cbind(b,a,z)
   d$prop.
diff --git a/RProject/Scripts/functions/resali.R b/RProject/Scripts/functions/resali.R
index 00f77cc..36ba0f3 100644
--- a/RProject/Scripts/functions/resali.R
+++ b/RProject/Scripts/functions/resali.R
@@ -18,6 +18,8 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
   while (length(unique(quantile(dat$score,seq(0,1,1/nqt))))!=nqt+1) {
     nqt <- nqt-1
   }
+  # ITEM POLYTOMIQUE
+  if (max(resp)>1) {
   dat$score_q5 <- cut(dat$score,unique(quantile(dat$score,seq(0,1,1/nqt))),labels=1:nqt,include.lowest=T)
   res.anova <- rep(NA,nbitems)
   pval <- rep(NA,nbitems)
@@ -89,67 +91,15 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
     }
     return(NULL)
   }
-}
-
-
-
-
-
-resali_BF2 <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
-  if (verbose) {
-    cat('-----------------------------------------------------------\n')
-    cat('COMPUTING INITIAL PCM\n')
-    cat('-----------------------------------------------------------\n')
-  }
-  nbitems <- length(items)
-  nbitems_o <- nbitems
-  items_n <- paste0('item',items)
-  resp <- df[,items_n]
-  grp <- df[,group]
-  pcm_initial <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
-  dat <- df
-  dat$score <- rowSums(dat[,items_n])
-  nqt <- ifelse(length(unique(quantile(dat$score,seq(0,1,0.2))))==6,5,length(unique(quantile(dat$score,seq(0,1,0.2))))-1)
-  dat$score_q5 <- cut(dat$score,unique(quantile(dat$score,seq(0,1,1/nqt))),labels=1:nqt,include.lowest=T)
-  res.anova <- rep(NA,nbitems)
-  pval <- rep(NA,nbitems)
-  fval <- rep(NA,nbitems)
-  for (i in items) {
-    dat[,paste0('res_',i)] <- rowMeans(predict(pcm_initial)$stand.resid[,,i])
-    res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
-    pval[i] <- res.anova[[i]][1,"Pr(>F)"]
-    fval[i] <- res.anova[[i]][1,'F value']
-  }
-  if (verbose) {
-    cat('DONE\n')
-    cat('-----------------------------------------------------------\n')
-  }
-  res.items <- c()
-  res.uniform <- c()
-  k <- 1
-  while(any(pval<0.05/(nbitems_o-k+1))) {
-    k <- k+1
-    if (verbose) {
-      cat(paste('COMPUTING STEP',k,'\n'))
-      cat('-----------------------------------------------------------\n')
-    }
-    res.item <- gsub("[a-z]", "",colnames(resp)[which.max(fval)])
-    res.items <- c(res.items,res.item)
-    res.uni <- res.anova[[which.max(fval)]][3,"Pr(>F)"]>0.05
-    res.uniform <- c(res.uniform,res.uni)
-    items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
-    dat[,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
-    dat[,paste0("item",res.item,'noTT')] <- dat[dat$TT==0,paste0('item',res.item)]
-    resp <- dat[,items_n]
-    grp <- dat[,group]
-    pcm_while <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
-    nbitems <- length(items_n)
+  # ITEM DICHOTOMIQUE
+  } else {
+    
     res.anova <- rep(NA,nbitems)
     pval <- rep(NA,nbitems)
     fval <- rep(NA,nbitems)
-    for (i in 1:nbitems) {
-      dat[,paste0('res_',i)] <- rowMeans(predict(pcm_while)$stand.resid[,,i])
-      res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
+    for (i in items) {
+      dat[,paste0('res_',i)] <- IRT.residuals(pcm_initial)$stand_residuals[,i]
+      res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT,data=dat))
       pval[i] <- res.anova[[i]][1,"Pr(>F)"]
       fval[i] <- res.anova[[i]][1,'F value']
     }
@@ -157,72 +107,9 @@ resali_BF2 <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
       cat('DONE\n')
       cat('-----------------------------------------------------------\n')
     }
-  }
-  if (verbose) {
-    cat("DETECTED DIF ITEMS\n")
-    cat('-----------------------------------------------------------\n')
-  }
-  if (length(res.items>0)) {
-    results <- data.frame(dif.items=res.items,
-                          uniform=1*res.uniform)
-    return(results)
-  }
-  else {
-    if (verbose) {
-      cat("No DIF was detected\n")
-    }
-    return(NULL)
-  }
-}
-
-
-
-
-
-
-
-
-resali_LRT <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
-  if (verbose) {
-    cat('-----------------------------------------------------------\n')
-    cat('COMPUTING INITIAL PCM\n')
-    cat('-----------------------------------------------------------\n')
-  }
-  nbitems <- length(items)
-  nbitems_o <- nbitems
-  items_n <- paste0('item',items)
-  resp <- df[,items_n]
-  grp <- df[,group]
-  items_n_alt <- paste0(items_n,c("_TT","_noTT"))
-  for (i in items_n) {
-    df[df$TT==0,paste0(i,"_noTT")] <- df[df$TT==0,i]
-    df[df$TT==1,paste0(i,"_TT")] <- df[df$TT==1,i]
-  }
-  resp_alt <- df[,items_n_alt]
-  pcm_initial <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
-  pcm_alt <- TAM::tam.mml(resp=resp_alt,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
-  dat <- df
-  dat$score <- rowSums(dat[,items_n])
-  nqt <- ifelse(length(unique(quantile(dat$score,seq(0,1,0.2))))==6,5,length(unique(quantile(dat$score,seq(0,1,0.2))))-1)
-  dat$score_q5 <- cut(dat$score,unique(quantile(dat$score,seq(0,1,1/nqt))),labels=1:nqt,include.lowest=T)
-  res.anova <- rep(NA,nbitems)
-  pval <- rep(NA,nbitems)
-  fval <- rep(NA,nbitems)
-  for (i in items) {
-    dat[,paste0('res_',i)] <- rowMeans(predict(pcm_initial)$stand.resid[,,i])
-    res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
-    pval[i] <- res.anova[[i]][1,"Pr(>F)"]
-    fval[i] <- res.anova[[i]][1,'F value']
-  }
-  if (verbose) {
-    cat('DONE\n')
-    cat('-----------------------------------------------------------\n')
-  }
-  res.items <- c()
-  res.uniform <- c()
-  k <- 1
-  if (anova(pcm_initial,pcm_alt)$p[1]<0.05) {
-    while(any(pval<0.05/nbitems_o)) {
+    res.items <- c()
+    k <- 1
+    while(any(pval<0.05/(nbitems_o))) {
       k <- k+1
       if (verbose) {
         cat(paste('COMPUTING STEP',k,'\n'))
@@ -230,8 +117,6 @@ resali_LRT <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
       }
       res.item <- gsub("[a-z]", "",colnames(resp)[which.max(fval)])
       res.items <- c(res.items,res.item)
-      res.uni <- res.anova[[which.max(fval)]][3,"Pr(>F)"]>0.05
-      res.uniform <- c(res.uniform,res.uni)
       items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
       dat[,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
       dat[,paste0("item",res.item,'noTT')] <- dat[dat$TT==0,paste0('item',res.item)]
@@ -243,11 +128,19 @@ resali_LRT <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
       pval <- rep(NA,nbitems)
       fval <- rep(NA,nbitems)
       for (i in 1:nbitems) {
-        dat[,paste0('res_',i)] <- rowMeans(predict(pcm_while)$stand.resid[,,i])
-        res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
+        dat[,paste0('res_',i)] <- IRT.residuals(pcm_while)$stand_residuals[,i]
+        res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT,data=dat))
         pval[i] <- res.anova[[i]][1,"Pr(>F)"]
         fval[i] <- res.anova[[i]][1,'F value']
       }
+      zz <- 0
+      for (name_i in items_n) {
+        zz <- zz+1
+        if (grepl("TT",name_i)) {
+          pval[zz] <- 1
+          fval[zz] <- 0
+        }
+      }
       if (verbose) {
         cat('DONE\n')
         cat('-----------------------------------------------------------\n')
@@ -259,7 +152,7 @@ resali_LRT <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
     }
     if (length(res.items>0)) {
       results <- data.frame(dif.items=res.items,
-                            uniform=1*res.uniform)
+                            uniform=rep(1,length(res.items)))
       return(results)
     }
     else {
@@ -268,11 +161,6 @@ resali_LRT <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
       }
       return(NULL)
     }
+    
   }
-  else {
-    if (verbose) {
-      cat("No DIF was detected\n")
-    }
-    return(NULL)
-  }
-}
\ No newline at end of file
+}
diff --git a/RProject/Scripts/resali_generate_newdata.R b/RProject/Scripts/resali_generate_newdata.R
index f70009e..19c2d29 100644
--- a/RProject/Scripts/resali_generate_newdata.R
+++ b/RProject/Scripts/resali_generate_newdata.R
@@ -1,141 +1,3 @@
-## Liste des scenarios
-
-results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
-
-results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
-
-results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
-
-results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
-
-results <- sort(results)
-
-results2 <- sort(results2)
-
-results <- c(results,results2)
-
-## Importer l'analyse resali pour chaque scenario
-
-for (r in results) {
-  cat('--------------------------------------------------------------------------\n')
-  cat(paste0(r,"\n"))
-  cat('--------------------------------------------------------------------------\n')
-  #### Importer les datas
-  scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-  if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-    N <- 50
-  }
-  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-    N <- 100
-  }
-  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-    N <- 200
-  }
-  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-    N <- 300
-  }
-  if (scen<5) {
-    datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',N,'/scenario_',r,'.csv'))
-  }
-  if (scen>=5) {
-    datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',N,'/scenario_',r,'.csv'))
-  }
-  #### Importer l'analyse
-  analyse <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection/',r,".csv"))
-  #### Pour chaque replication
-  for (k in 1:1000) {
-    if (k%%100==0) {
-      cat(paste0("N = ",k," / 1000\n"))
-    }
-    datt[datt$replication==k,"dif.detect.1"] <- analyse[analyse$X==k,"dif.detect.1"]
-    datt[datt$replication==k,"dif.detect.2"] <- analyse[analyse$X==k,"dif.detect.2"]
-    datt[datt$replication==k,"dif.detect.3"] <- analyse[analyse$X==k,"dif.detect.3"]
-    datt[datt$replication==k,"dif.detect.4"] <- analyse[analyse$X==k,"dif.detect.4"]
-    datt[datt$replication==k,"dif.detect.unif.1"] <- analyse[analyse$X==k,"dif.detect.unif.1"]
-    datt[datt$replication==k,"dif.detect.unif.2"] <- analyse[analyse$X==k,"dif.detect.unif.2"]
-    datt[datt$replication==k,"dif.detect.unif.3"] <- analyse[analyse$X==k,"dif.detect.unif.3"]
-    datt[datt$replication==k,"dif.detect.unif.4"] <- analyse[analyse$X==k,"dif.detect.unif.4"]
-    if (scen==3 | scen==4 | scen>=13) {
-      datt[datt$replication==k,"dif.detect.5"] <- analyse[analyse$X==k,"dif.detect.5"]
-      datt[datt$replication==k,"dif.detect.6"] <- analyse[analyse$X==k,"dif.detect.6"]
-      datt[datt$replication==k,"dif.detect.7"] <- analyse[analyse$X==k,"dif.detect.7"]
-      datt[datt$replication==k,"dif.detect.unif.5"] <- analyse[analyse$X==k,"dif.detect.unif.5"]
-      datt[datt$replication==k,"dif.detect.unif.6"] <- analyse[analyse$X==k,"dif.detect.unif.6"]
-      datt[datt$replication==k,"dif.detect.unif.7"] <- analyse[analyse$X==k,"dif.detect.unif.7"]
-    }
-  }
-  datt[is.na(datt$dif.detect.1),"dif.detect.1"] <- ""
-  datt[is.na(datt$dif.detect.2),"dif.detect.2"] <- ""
-  datt[is.na(datt$dif.detect.3),"dif.detect.3"] <- ""
-  datt[is.na(datt$dif.detect.4),"dif.detect.4"] <- ""
-  datt[is.na(datt$dif.detect.unif.1),"dif.detect.unif.1"] <- ""
-  datt[is.na(datt$dif.detect.unif.2),"dif.detect.unif.2"] <- ""
-  datt[is.na(datt$dif.detect.unif.3),"dif.detect.unif.3"] <- ""
-  datt[is.na(datt$dif.detect.unif.4),"dif.detect.unif.4"] <- ""
-  if (scen==3 | scen==4 | scen>=13) {
-    datt[is.na(datt$dif.detect.5),"dif.detect.5"] <- ""
-    datt[is.na(datt$dif.detect.6),"dif.detect.6"] <- ""
-    datt[is.na(datt$dif.detect.7),"dif.detect.7"] <- ""
-    datt[is.na(datt$dif.detect.unif.5),"dif.detect.unif.5"] <- ""
-    datt[is.na(datt$dif.detect.unif.6),"dif.detect.unif.6"] <- ""
-    datt[is.na(datt$dif.detect.unif.7),"dif.detect.unif.7"] <- ""
-  }
-  write.csv(datt,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}
-
-
-
-
-
-
-
-
-
-for (r in results) {
-  cat('--------------------------------------------------------------------------\n')
-  cat(paste0(r,"\n"))
-  cat('--------------------------------------------------------------------------\n')
-  #### Importer les datas
-  scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-  if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-    N <- 50
-  }
-  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-    N <- 100
-  }
-  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-    N <- 200
-  }
-  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-    N <- 300
-  }
-  #### Importer l'analyse
-  analyse <- read.csv(paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-  analyse[is.na(analyse)] <- ""
-  names(analyse)[names(analyse)=="dif.detect.1"] <- "dif_detect_1"
-  names(analyse)[names(analyse)=="dif.detect.2"] <- "dif_detect_2"
-  names(analyse)[names(analyse)=="dif.detect.3"] <- "dif_detect_3"
-  names(analyse)[names(analyse)=="dif.detect.4"] <- "dif_detect_4"
-  names(analyse)[names(analyse)=="dif.detect.unif.1"] <- "dif_detect_unif_1"
-  names(analyse)[names(analyse)=="dif.detect.unif.2"] <- "dif_detect_unif_2"
-  names(analyse)[names(analyse)=="dif.detect.unif.3"] <- "dif_detect_unif_3"
-  names(analyse)[names(analyse)=="dif.detect.unif.4"] <- "dif_detect_unif_4"
-
-  
-  if (scen==3 | scen==4 | scen>=13) {
-    names(analyse)[names(analyse)=="dif.detect.5"] <- "dif_detect_5"
-    names(analyse)[names(analyse)=="dif.detect.6"] <- "dif_detect_6"
-    names(analyse)[names(analyse)=="dif.detect.7"] <- "dif_detect_7"
-    names(analyse)[names(analyse)=="dif.detect.unif.5"] <- "dif_detect_unif_5"
-    names(analyse)[names(analyse)=="dif.detect.unif.6"] <- "dif_detect_unif_6"
-    names(analyse)[names(analyse)=="dif.detect.unif.7"] <- "dif_detect_unif_7"
-
-  }
-  analyse <- analyse[,!names(analyse) %in% c("X","X.1","X.2")]
-  write.csv(analyse,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}
-
-
 ##############################################################################
 #----------------------------------------------------------------------------#
 ################################### RESALI ###################################
@@ -251,9 +113,6 @@ generate_resali <- function(scenario=NULL,grp=NULL) {
 
 
 
-
-
-
 results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
 
 results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
@@ -275,6 +134,146 @@ for (r in results) {
   cat(paste0("-------------------------------------------","\n"))
 }
 
+##############################################################################
+#----------------------------------------------------------------------------#
+################################### NEWDATA ##################################
+#----------------------------------------------------------------------------#
+##############################################################################
+
+## Liste des scenarios
+
+results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
+
+results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
+
+results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
+
+results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
+
+results <- sort(results)
+
+results2 <- sort(results2)
+
+results <- c(results,results2)
+
+## Importer l'analyse resali pour chaque scenario
+
+for (r in results) {
+  cat('--------------------------------------------------------------------------\n')
+  cat(paste0(r,"\n"))
+  cat('--------------------------------------------------------------------------\n')
+  #### Importer les datas
+  scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
+  if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
+    N <- 50
+  }
+  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
+    N <- 100
+  }
+  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
+    N <- 200
+  }
+  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
+    N <- 300
+  }
+  if (scen<5) {
+    datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',N,'/scenario_',r,'.csv'))
+  }
+  if (scen>=5) {
+    datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',N,'/scenario_',r,'.csv'))
+  }
+  #### Importer l'analyse
+  analyse <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection/',r,".csv"))
+  #### Pour chaque replication
+  for (k in 1:1000) {
+    if (k%%100==0) {
+      cat(paste0("N = ",k," / 1000\n"))
+    }
+    datt[datt$replication==k,"dif.detect.1"] <- analyse[analyse$X==k,"dif.detect.1"]
+    datt[datt$replication==k,"dif.detect.2"] <- analyse[analyse$X==k,"dif.detect.2"]
+    datt[datt$replication==k,"dif.detect.3"] <- analyse[analyse$X==k,"dif.detect.3"]
+    datt[datt$replication==k,"dif.detect.4"] <- analyse[analyse$X==k,"dif.detect.4"]
+    datt[datt$replication==k,"dif.detect.unif.1"] <- analyse[analyse$X==k,"dif.detect.unif.1"]
+    datt[datt$replication==k,"dif.detect.unif.2"] <- analyse[analyse$X==k,"dif.detect.unif.2"]
+    datt[datt$replication==k,"dif.detect.unif.3"] <- analyse[analyse$X==k,"dif.detect.unif.3"]
+    datt[datt$replication==k,"dif.detect.unif.4"] <- analyse[analyse$X==k,"dif.detect.unif.4"]
+    if (scen==3 | scen==4 | scen>=13) {
+      datt[datt$replication==k,"dif.detect.5"] <- analyse[analyse$X==k,"dif.detect.5"]
+      datt[datt$replication==k,"dif.detect.6"] <- analyse[analyse$X==k,"dif.detect.6"]
+      datt[datt$replication==k,"dif.detect.7"] <- analyse[analyse$X==k,"dif.detect.7"]
+      datt[datt$replication==k,"dif.detect.unif.5"] <- analyse[analyse$X==k,"dif.detect.unif.5"]
+      datt[datt$replication==k,"dif.detect.unif.6"] <- analyse[analyse$X==k,"dif.detect.unif.6"]
+      datt[datt$replication==k,"dif.detect.unif.7"] <- analyse[analyse$X==k,"dif.detect.unif.7"]
+    }
+  }
+  datt[is.na(datt$dif.detect.1),"dif.detect.1"] <- ""
+  datt[is.na(datt$dif.detect.2),"dif.detect.2"] <- ""
+  datt[is.na(datt$dif.detect.3),"dif.detect.3"] <- ""
+  datt[is.na(datt$dif.detect.4),"dif.detect.4"] <- ""
+  datt[is.na(datt$dif.detect.unif.1),"dif.detect.unif.1"] <- ""
+  datt[is.na(datt$dif.detect.unif.2),"dif.detect.unif.2"] <- ""
+  datt[is.na(datt$dif.detect.unif.3),"dif.detect.unif.3"] <- ""
+  datt[is.na(datt$dif.detect.unif.4),"dif.detect.unif.4"] <- ""
+  if (scen==3 | scen==4 | scen>=13) {
+    datt[is.na(datt$dif.detect.5),"dif.detect.5"] <- ""
+    datt[is.na(datt$dif.detect.6),"dif.detect.6"] <- ""
+    datt[is.na(datt$dif.detect.7),"dif.detect.7"] <- ""
+    datt[is.na(datt$dif.detect.unif.5),"dif.detect.unif.5"] <- ""
+    datt[is.na(datt$dif.detect.unif.6),"dif.detect.unif.6"] <- ""
+    datt[is.na(datt$dif.detect.unif.7),"dif.detect.unif.7"] <- ""
+  }
+  write.csv(datt,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
+}
+
+
+
+
+
+
+
+
+
+for (r in results) {
+  cat('--------------------------------------------------------------------------\n')
+  cat(paste0(r,"\n"))
+  cat('--------------------------------------------------------------------------\n')
+  #### Importer les datas
+  scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
+  if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
+    N <- 50
+  }
+  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
+    N <- 100
+  }
+  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
+    N <- 200
+  }
+  if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
+    N <- 300
+  }
+  #### Importer l'analyse
+  analyse <- read.csv(paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
+  analyse[is.na(analyse)] <- ""
+  names(analyse)[names(analyse)=="dif.detect.1"] <- "dif_detect_1"
+  names(analyse)[names(analyse)=="dif.detect.2"] <- "dif_detect_2"
+  names(analyse)[names(analyse)=="dif.detect.3"] <- "dif_detect_3"
+  names(analyse)[names(analyse)=="dif.detect.4"] <- "dif_detect_4"
+  names(analyse)[names(analyse)=="dif.detect.unif.1"] <- "dif_detect_unif_1"
+  names(analyse)[names(analyse)=="dif.detect.unif.2"] <- "dif_detect_unif_2"
+  names(analyse)[names(analyse)=="dif.detect.unif.3"] <- "dif_detect_unif_3"
+  names(analyse)[names(analyse)=="dif.detect.unif.4"] <- "dif_detect_unif_4"
 
+  
+  if (scen==3 | scen==4 | scen>=13) {
+    names(analyse)[names(analyse)=="dif.detect.5"] <- "dif_detect_5"
+    names(analyse)[names(analyse)=="dif.detect.6"] <- "dif_detect_6"
+    names(analyse)[names(analyse)=="dif.detect.7"] <- "dif_detect_7"
+    names(analyse)[names(analyse)=="dif.detect.unif.5"] <- "dif_detect_unif_5"
+    names(analyse)[names(analyse)=="dif.detect.unif.6"] <- "dif_detect_unif_6"
+    names(analyse)[names(analyse)=="dif.detect.unif.7"] <- "dif_detect_unif_7"
 
+  }
+  analyse <- analyse[,!names(analyse) %in% c("X","X.1","X.2")]
+  write.csv(analyse,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
+}