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    ## simpleIC Shiny/R app server.R                                           
##                                                                      
## Author(s) :
## -----------
## J.J.
## Orginal version by Grégoire Vincke http://www.uclouvain.be/gregoire.vincke       
## For Statistical eLearning Tools http://sites.uclouvain.be/selt/      
##                                                                      
## Licences : 
## ---------
## CC-BY for the web page http://sites.uclouvain.be/selt/shiny/testhypic
## see http://creativecommons.org/licenses/by/2.0/be/ for more informations       
##
## GPLv2 for source code on https://github.com/uclouvain-selt/shiny  
## See LICENCE.tx or http://www.gnu.org/licenses/old-licenses/gpl-2.0.html for more informations

Sys.setlocale("LC_ALL", "de_DE.UTF-8")#to be sure that accents in text will be allowed in plots
library(shiny)
library(plotrix)
library(xtable)
library(ggplot2)

debug<-0

color.brown<-rgb(0.5,0.2,0)
color.blue<-rgb(0,0,0.9)
color.true<-rgb(0,0.7,0)
color.false<-rgb(1,0,0,0.9)
oui.color.false<-rgb(0.3,0.3,0.3)
oui.color.true<-rgb(.6,.6,.6)
text.color.false<-rgb(0.2,0.2,0.2)
text.color.true<-rgb(.5,.5,.5)
non.color.true<-rgb(0.8,0.8,0.8)
non.color.false<-rgb(0.93,0.93,0.93)


density.true<-10
density.false<-25

y.delta<-0.1 #factor to set delta between rows of datas in plots

hypoth.text.levels<-c(1,0.7,0.4,0.1)

x.lim.min<-0
x.lim.max<-60
x.amp<-x.lim.max-x.lim.min

# possible values for the mean, cf ui.R mx1, mx0, mx
mu.vec<-c(x.lim.min:x.lim.max)#c(25:75)

shinyServer(function(input, output,session){
  
  rv <- reactiveValues()# Create a reactiveValues object, to let us use settable reactive values
  
  rv$last.takesample.value<-0
  rv$samples.mat<-c() # matrix of all observations, each line one sample
  rv$new.sample<-c() # new matrix of observations, each line one sample
  rv$cv.ls<-list() # calculated values
  
  rv$lastAction <- 'none' # To start out, lastAction == NULL, meaning nothing clicked yet

  # Calculations only needed if one of these values are changed, so observe them
  rv$mx0.c<-0 # hypothesis mean
  rv$mx.c<-0 # population mean
  rv$sx.c<-0 # population deviation
  rv$IC.k.c<-0 # IC length
  rv$typIC.c<-'' # Type 'eCVk' empiric, 'vCVk' variance connue, 'sCVk' variance inconnue
  rv$test.c<-'' # Type '=' bilateral, '<=' unilateral, '=>' unilateral
  # Create all samples new if a change is made in sample size
  rv$n.c<-0 # sample size as in ui
  rv$tn.c<-0 # total numer of samples


  testicPl.choices.ls<- list("Choix" = "false",
                             "Indiquer couverture par les IC" = "cvPl", 
                                 "Indiquer la décision" = "testPl",
                                 "Afficher  % de rejet" = "rejFreqPl")
  
  observe({
      if(input$visM){
          js_string <- '$(".span8").width(500);'
          session$sendCustomMessage(type='jsCode', list(value = js_string))
      }
  })

  # reset option if IC off or Hypotheses off
  observe({
      if(!(input$icPl &&  input$hypPl!="false")){
          updateSelectInput(session, "testicPl","",testicPl.choices.ls, "false")
      }
  })

  # if IC Model with sigma known, show sigma
  observe({
      if(input$CVk == "vCVk"){
          updateCheckboxInput(session, "sigKn",value=TRUE)
      } else {
          updateCheckboxInput(session, "sigKn",value=FALSE)
      }
  })

  
  # if take sample
  observe({
      if (input$takesample != 0) {
          rv$lastAction <- 'takesample'
      }

      })

  # if reset all new
  observe({
      if(input$reset !=0){
          rv$lastAction <- 'reset'
          rv$last.takesample.value<-0

          rv$samples.mat<-c()
          rv$cv.ls<-list()
          rv$mx.c<-0 # population mean
          rv$sx.c<-0 # population deviation
          rv$IC.k.c<-0 # IC length
          rv$typIC.c<-'' # Type 'eCVk' empiric, 'vCVk' variance connue, 'sCVk' variance inconnue
          rv$n.c<-0 # sample size as in ui
          rv$tn.c<-0 # total numer of samples
          updateSliderInput(session, "mx1",value = sample(c(31:35),1))
          updateSliderInput(session, "sx",value = sample(seq(from = 2, to = 3.5, by = 0.5),1))
          updateCheckboxInput(session, "muKn",value=FALSE)
          updateCheckboxInput(session, "sigKn",value=FALSE)
      }
  })


  getSamples<-reactive({#créee n valeurs aléatoires N(0;1) quand input$takesample est implémenté (quand le bouton takesample est pressé)
      if(input$takesample > rv$last.takesample.value && rv$lastAction == "takesample"){
          return(isolate({#Now do the expensive stuff
              rv$new.sample<-matrix(rnorm(input$ns*input$n),ncol=input$n)
              return(TRUE)
          }))
      } else {
          return(FALSE)
      }
  })

  getPlotHeight <- function() {
      if(input$display=="default") {
	unit.height<-250 #cannot be auto because height is already "auto" in ui and double auto = conflict
      }
      if(input$display=="1024") {
	unit.height<-180
      }
      if(input$display=="800") {
	unit.height<-140 #160 for real full page
      }
    return(3*unit.height)
  }
  
  getPlotWidth <- function() {
      if(input$display=="default") {
	full.plot.width<-1310-310#"auto"
      }
      if(input$display=="1024") {
	full.plot.width<-900-310
      }
      if(input$display=="800") {
	full.plot.width<-700-310
      }
      if(input$visM && input$display!="default"){
	full.plot.width<-full.plot.width+310
      }
    return(full.plot.width)
  }
    
  getInputValues<-reactive({
      return(input)#collect all inputs
  })
  
  getComputedValues<-reactive({
      # returns TRUE if new calculations other wise FALSE
      # results hold in rv$cv.ls
      # gives TRUE back if new values calculated otherwise FALSE
      calc.new<-FALSE # we do not want  to calculate all values again
      # did we create new samples?
      sample.new<-getSamples() # if TRUE then append new observations from rv$new.sample
      v<-getInputValues() # get all values of input list
      # check if sample size was changed
      if (v$n != rv$n.c){# if changed create a new observation matrix of correct size
          rv$n.c<-v$n
          if(rv$tn.c>0){
              rv$samples.mat<-matrix(rnorm(rv$tn.c*rv$n.c),ncol=rv$n.c)
          }
          calc.new<-TRUE # we have to calculate all values again
      }
      if(sample.new){#if new observations created, append them
          sample.mat<-mat.or.vec(rv$tn.c + v$ns,v$n)
          if(rv$tn.c>0){
              sample.mat[1:rv$tn.c,]<-rv$samples.mat
          }
          sample.mat[(rv$tn.c+1):(rv$tn.c+v$ns),]<-rv$new.sample
          rv$samples.mat<-sample.mat  # new observations
          rv$tn.c<-length(rv$samples.mat[,1]) # new total number of samples
          calc.new<-TRUE # we have to calculate all values again
      }
         
      # check if caluations are needed due to parameter changes
      # could be still optimized since a change in rv$IC.k.c does not needs a whole new calcul 
      if (v$mx0 != rv$mx0.c){# hypothesis mean changed
          rv$mx0.c<-v$mx0 # update
          calc.new<-TRUE
      }

      if (v$mx != rv$mx.c){# population mean changed
          rv$mx.c<-v$mx # update
          calc.new<-TRUE
      }

      if (v$sx != rv$sx.c){# population sd changed
          rv$sx.c<-v$sx # update
          calc.new<-TRUE
      }

      if (v$k != rv$IC.k.c){# IC length changed
          rv$IC.k.c<-v$k # update
          calc.new<-TRUE
      }

      if (v$CVk != rv$typIC.c){# type IC  changed
          rv$typIC.c<-v$CVk # update
          calc.new<-TRUE
      }

      if (v$test != rv$test.c){# type test  changed
          rv$test.c<-v$test # update
          calc.new<-TRUE
      }

      # new calulations if new obsarvations or
      if(calc.new){
          cv<-list()#created empty computed values list
          ## Define reality parameters
          cv$vx<-v$sx^2#compute variance of Reality distribution
    
          ## Computation of x y coordinates for Normal curve of Reality
          z<-seq(-5,5,length=100)
          cv$xr<-(z*v$sx)+v$mx #x for Reality
          cv$yr<-dnorm(cv$xr,mean=v$mx,sd=v$sx)#y for Reality
	
        
          ## Computation of sample related values ##
          cv$samples.x.mat<-c() # matrix of observations, each line a sample
          cv$samples.x.m.vec<-c() # vector of mean values, each line a sample
          cv$samples.x.sd.vec<-c() # vector of sd values, each line a sample
          cv$ic.k.limit.mat<-c() # matrix of limits, columns lower and upper bound , lines by sample
          cv$ic.k.inc.allmu.mat<-c() # matrix of TRUE/FALSE if mu in IC columns all mu.vec=c(20:60) and lines by sample 
          cv$pc.ic.k.inc.allmu.vec<-c() # for all mu increment percentage covered by IC
          cv$n.ic.k.inc.allmu.vec<-c() # for all mu increment number covered by IC
        
          cv$n.samples<-rv$tn.c # number of samples
          cv$samples.x.n.toshow<-0
      
          if(cv$n.samples>0){
              cv$samples.x.mat<-mat.or.vec(cv$n.samples,v$n)
              cv$ic.k.limit.mat<-mat.or.vec(cv$n.samples,2)
              cv$vect.n.samples<-c(1:cv$n.samples)
              cv$samples.x.mat<-round((rv$samples.mat*v$sx)+v$mx,2)#Then sample values are compute with mx mean and standard deviation
              ## Computation of descriptives
              cv$samples.x.m.vec<-round(apply(cv$samples.x.mat,1,mean),2)#means of samples
              cv$samples.x.sd.vec<-round(apply(cv$samples.x.mat,1,sd),2)#sds of samples
              ## Computation of confidence intervals for the mean µ ##            
              if(v$CVk == 'vCVk'){#compute the CI limits with k value and known variance
                  cv$ic.k.limit.mat[,1]<-round(cv$samples.x.m.vec-v$k*v$sx*(v$n)^(-.5),2)
                  cv$ic.k.limit.mat[,2]<-round(cv$samples.x.m.vec+v$k*v$sx*(v$n)^(-.5),2)
              }
              if(v$CVk == 'sCVk'){#compute the CI limits with k value and unknown variance
                  cv$ic.k.limit.mat[,1]<-round(cv$samples.x.m.vec-v$k*cv$samples.x.sd.vec*(v$n)^(-.5),2)
                  cv$ic.k.limit.mat[,2]<-round(cv$samples.x.m.vec+v$k*cv$samples.x.sd.vec*(v$n)^(-.5),2)
              }
              if(v$CVk == 'eCVk'){#compute the CI limits with empiric k value 
                  cv$ic.k.limit.mat[,1]<-round(cv$samples.x.m.vec-v$k,2)
                  cv$ic.k.limit.mat[,2]<-round(cv$samples.x.m.vec+v$k,2)
              }

              ## test bilateral vs unilateral
              if(v$test == '='){
                  ## Check for all values in mu.vec if in IC
                  cv$ic.k.inc.allmu.mat<-sapply(mu.vec,function(x){return (cv$ic.k.limit.mat[,1] <=x & x<=cv$ic.k.limit.mat[,2])})
                  ## Check for mx0 if in IC changed for all values in mu.vec
                  cv$ic.k.mu0.inc.allmu.mat<-sapply((-mu.vec+v$mx+v$mx0),function(x){return (cv$ic.k.limit.mat[,1] <=x & x<=cv$ic.k.limit.mat[,2])})
              }
              if(v$test == '<='){
                  ## Check for all values in mu.vec if in IC
                  cv$ic.k.inc.allmu.mat<-sapply(mu.vec,function(x){return (cv$ic.k.limit.mat[,1] <=x)})
                  ## Check for mx0 if in IC changed for all values in mu.vec
                  cv$ic.k.mu0.inc.allmu.mat<-sapply((-mu.vec+v$mx+v$mx0),function(x){return (cv$ic.k.limit.mat[,1] <=x)})
              }
              if(v$test == '=>'){
                  ## Check for all values in mu.vec if in IC
                  cv$ic.k.inc.allmu.mat<-sapply(mu.vec,function(x){return (x<=cv$ic.k.limit.mat[,2])})
                  ## Check for mx0 if in IC changed for all values in mu.vec
                  cv$ic.k.mu0.inc.allmu.mat<-sapply((-mu.vec+v$mx+v$mx0),function(x){return (x<=cv$ic.k.limit.mat[,2])})
              }
              
              ## Calculate for all values in mu.vec frequencies absolute and relative
              cv$n.ic.k.inc.allmu.vec<-apply(matrix(cv$ic.k.inc.allmu.mat,ncol=length(mu.vec)),2,sum)
              cv$pc.ic.k.inc.allmu.vec<-round(cv$n.ic.k.inc.allmu.vec/cv$n.samples,3)*100
              ## Calculate for all values in mu.vec frequencies absolute and relative
              cv$n.ic.k.mu0.inc.allmu.vec<-apply(matrix(cv$ic.k.mu0.inc.allmu.mat,ncol=length(mu.vec)),2,sum)
              cv$pc.ic.k.mu0.inc.allmu.vec<-round(cv$n.ic.k.mu0.inc.allmu.vec/cv$n.samples,3)*100              
              ## Define colors
              cv$ic.k.inc.mu.color.mat<-matrix(ifelse(cv$ic.k.inc.allmu.mat,oui.color.true,oui.color.false),ncol=length(mu.vec))
              cv$ic.k.inc.mu0.color.mat<-matrix(ifelse(cv$ic.k.inc.allmu.mat,color.false,color.true),ncol=length(mu.vec))
              cv$ic.k.inc.mu1.color.mat<-matrix(ifelse(cv$ic.k.inc.allmu.mat,color.true,color.false),ncol=length(mu.vec))
              ## Define subset to plot
              cv$samples.x.from<-1
              if(cv$n.samples>v$nss){
                  cv$samples.x.from<-cv$n.samples-v$nss+1
              }
              cv$samples.x.to<-cv$n.samples
              cv$samples.x.mat.toshow<-matrix(cv$samples.x.mat[cv$samples.x.from:cv$samples.x.to,],ncol=v$n)
              cv$samples.x.m.vec.toshow<-cv$samples.x.m.vec[cv$samples.x.from:cv$samples.x.to]
              cv$samples.x.sd.vec.toshow<-cv$samples.x.sd.vec[cv$samples.x.from:cv$samples.x.to]
              cv$samples.x.i.vec.toshow<-c(cv$samples.x.from:cv$samples.x.to)
              cv$ic.k.limit.mat.toshow<-matrix(cv$ic.k.limit.mat[cv$samples.x.from:cv$samples.x.to,],ncol=2)
              cv$ic.k.inc.allmu.mat.toshow<-matrix(matrix(cv$ic.k.inc.allmu.mat,ncol=length(mu.vec))[cv$samples.x.from:cv$samples.x.to,],ncol=length(mu.vec))
              cv$samples.y.mat.toshow<-c() # plot line by line the values, here corresponding y-values 
              cv$samples.x.n.toshow<-length(cv$samples.x.mat.toshow[,1])
              cv$ic.k.inc.mu.color.vec.toshow<-c() # color the IC for mu
              cv$ic.k.inc.mu0.color.vec.toshow<-c() # color the IC for mu0
              cv$ic.k.inc.mu1.color.vec.toshow<-c() # color the IC for mu1

              if(cv$samples.x.n.toshow>0){
                  cv$samples.y.mat.toshow<-matrix(rep(y.delta/(v$nss+1)*c(1:cv$samples.x.n.toshow),length(cv$samples.x.mat.toshow[1,])),nrow=length(cv$samples.x.mat.toshow[,1]))
                  ##     ## Define colors if IC covers µ or µ0 or µ1
                  cv$ic.k.inc.mu.color.vec.toshow<-cv$ic.k.inc.mu.color.mat[cv$samples.x.from:cv$samples.x.to,v$mx0-mu.vec[1]+1]
                  cv$ic.k.inc.mu0.color.vec.toshow<-cv$ic.k.inc.mu0.color.mat[cv$samples.x.from:cv$samples.x.to,v$mx0-mu.vec[1]+1]
                  cv$ic.k.inc.mu1.color.vec.toshow<-cv$ic.k.inc.mu1.color.mat[cv$samples.x.from:cv$samples.x.to,v$mx0-mu.vec[1]+1]
              }
          }
          rv$cv.ls<-cv # set new values
      }
      
    ## Last takesample value
          rv$last.takesample.value<-v$takesample
    return(calc.new)
  })
    
  output$plotEmp <- renderPlot({
      v<-getInputValues()
      calc.new<-getComputedValues() # TRUE if new values have been calculated
      cv<-rv$cv.ls # holds calculated values
      # if graphic values of parameter are changed without new calculus, so here calculate new values
      if(v$display=="default") {
          cex.samples<-2.2 	#size of text describing samples (2.2)
          cex.param<-3.5 		#size of text of parameter µ µ'', etc (3.5)
          cex.title<-2.2
          y.delta<-0.1 		#factor to set delta between rows of datas in plots
          ic.bar.half.height<-0.004
      }
      if(v$display=="1024") {
          cex.samples<-1.7	#size of text describing samples (2.2)
          cex.param<-2.5		#size of text of parameter µ µ'', etc (3.5)
          cex.title<-1.7
          y.delta<-0.1 		#factor to set delta between rows of datas in plots
          ic.bar.half.height<-0.004
      }
      if(v$display=="800") {
          cex.samples<-1.5		#size of text describing samples (2.2)
          cex.param<-2		#size of text of parameter µ µ'', etc (3.5)
          cex.title<-1.7
          y.delta<-0.1 		#factor to set delta between rows of datas in plots
          ic.bar.half.height<-0.004
      }
      ## Define subset to plot
      if(cv$n.samples>0){
          cv$samples.x.from<-1
          if(cv$n.samples>v$nss){
              cv$samples.x.from<-cv$n.samples-v$nss+1
          }
          cv$samples.x.to<-cv$n.samples
          cv$samples.x.mat.toshow<-matrix(cv$samples.x.mat[cv$samples.x.from:cv$samples.x.to,],ncol=v$n)
          cv$samples.x.m.vec.toshow<-cv$samples.x.m.vec[cv$samples.x.from:cv$samples.x.to]
          cv$samples.x.sd.vec.toshow<-cv$samples.x.sd.vec[cv$samples.x.from:cv$samples.x.to]
          cv$samples.x.i.vec.toshow<-c(cv$samples.x.from:cv$samples.x.to)
          cv$ic.k.limit.mat.toshow<-matrix(cv$ic.k.limit.mat[cv$samples.x.from:cv$samples.x.to,],ncol=2)
          cv$samples.y.mat.toshow<-c() # plot line by line the values, here corresponding y-values 
          cv$samples.x.n.toshow<-length(cv$samples.x.mat.toshow[,1])
          cv$ic.k.inc.mu.color.vec.toshow<-c() # color the IC for mu
          cv$ic.k.inc.mu0.color.vec.toshow<-c() # color the IC for mu0
          cv$ic.k.inc.mu1.color.vec.toshow<-c() # color the IC for mu1
          
          if(cv$samples.x.n.toshow>0){
              cv$samples.y.mat.toshow<-matrix(rep(y.delta/(v$nss+1)*c(1:cv$samples.x.n.toshow),length(cv$samples.x.mat.toshow[1,])),nrow=length(cv$samples.x.mat.toshow[,1]))
              ##     ## Define colors if IC covers µ or µ0 or µ1
              cv$ic.k.inc.mu.color.vec.toshow<-cv$ic.k.inc.mu.color.mat[cv$samples.x.from:cv$samples.x.to,v$mx0-mu.vec[1]+1]
              cv$ic.k.inc.mu0.color.vec.toshow<-cv$ic.k.inc.mu0.color.mat[cv$samples.x.from:cv$samples.x.to,v$mx0-mu.vec[1]+1]
              cv$ic.k.inc.mu1.color.vec.toshow<-cv$ic.k.inc.mu1.color.mat[cv$samples.x.from:cv$samples.x.to,v$mx0-mu.vec[1]+1] #?????
          }
      }

      # color the population mean green if H0 is true otherwise red
      if(v$test == "="){#bilateral
          if(v$mx0 == v$mx){
              color.mx<-color.true
          } else {
              color.mx<-color.false
          }
      }
      if(v$test == "<="){#unilateral
          if(v$mx <= v$mx0){
              color.mx<-color.true
          } else {
              color.mx<-color.false
          }
      }
      if(v$test == "=>"){#unilateral
          if(v$mx0 <= v$mx){
              color.mx<-color.true
          } else {
              color.mx<-color.false
          }
      }
      m<-matrix(c(1,2,3,4,5,6),3,2,byrow=TRUE)
      layout(m,width=c(3,1))
      ##-------------------------------------------    
      ## Plot always Reality ##
      ##-------------------------------------------    
      cv$maxdmx=0.05
      par(mai=c(0.3,0.6,0.5,0))
      label<-""
      if(v$showreality){
          label<-"Density"
      }
      plot(c(0),c(-5),lty=1,lwd=1,col="black",yaxt="n",bty="n",las=1,xaxs="i",yaxs="i",cex.lab=1,cex.axis=1.5,xlim=c(x.lim.min,x.lim.max),ylim=c(0,cv$maxdmx*2.1),xlab="",ylab=label,xaxp=c(x.lim.min,x.lim.max,20),main=bquote(paste("Echantillons prélevés :")),cex.main=cex.title)
      if(debug){
          box(which="outer",lty = 'dotted', col = 'red')
          box(which="figure",lty = 'dotted', col = 'blue')
          box(which="plot",lty = 'dotted', col = 'blue')
      }
      if(cv$samples.x.n.toshow>0){
          for(i in 1:cv$samples.x.n.toshow){
              points(cv$samples.x.mat.toshow[i,],cv$samples.y.mat.toshow[i,],cex=cex.samples*0.8)
              text(cv$samples.x.m.vec.toshow[i],cv$samples.y.mat.toshow[i,1],labels=bquote(bar(x)[.(cv$samples.x.i.vec.toshow[i])]),cex=cex.samples*1.2,col=color.blue)
          }
      }
      
      if(v$showreality){
          axis(2,las=2,yaxp=c(0,signif(cv$maxdmx,1),5),cex.axis=1.2)
          points(cv$xr,cv$yr,type="l")
          text(1,signif(cv$maxdmx,1)*0.75,labels=bquote(paste(N *"~"* ( mu *","* sigma^2 ) ," ", N *"~"* (.(v$mx)*","*.(cv$vx)) ,sep='')),cex=1.4, pos=4)
      }

      if(v$hypPl == "realite"){
          ## Plot true mean only if known
          lines(x<-c(v$mx,v$mx),y <- c(0,cv$maxdmx*1.8),lty=1,lwd=2,col=color.mx)
          text(v$mx,cv$maxdmx*1.95,labels=bquote(mu),cex=cex.param,col=color.mx)
      }
      
      ## empty plot for layout
      par(mai=c(0.3,0,0.5,0))
      plot(c(0,1),c(0,0),col="white",xaxt="n",yaxt="n",xlab="",ylab="",ylim=c(0,cv$maxdmx*2.1),bty="n",las=1)
      if(debug){
          box(which="figure",lty = 'dotted', col = 'blue')
          box(which="plot",lty = 'dotted', col = 'blue')
      }
      if(v$empPl){
          mtext(bquote(paste("Descriptives : ", N == .(cv$n.samples), sep="")),side=1,line=1,at=0.05,adj=0)
          if(cv$samples.x.n.toshow>0){
              for(i in 1:cv$samples.x.n.toshow){
                  text(0,cv$samples.y.mat.toshow[i,1],labels=bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])] == .(sprintf("%.2f",cv$samples.x.m.vec.toshow[i])),sep="")),cex=cex.samples,col=color.blue,pos=4)
                  text(0.5,cv$samples.y.mat.toshow[i,1],labels=bquote(paste(s[.(cv$samples.x.i.vec.toshow[i])] == .(sprintf("%.2f",cv$samples.x.sd.vec.toshow[i])),sep="")),cex=cex.samples,pos=4)
              }
          }
      }
      
      if(v$icPl || (v$hypPl != "false")){
          ##-------------------------------------------    
          ## Plot IC  or Hyportheis    ##
          ##-------------------------------------------              
          cv$maxdmx=0.05
          par(mai=c(0.3,0.6,0.5,0))
          if(v$icPl && !(v$hypPl != "false")){
              plot(c(0),c(-5),lty=1,lwd=1,col="black",yaxt="n",bty="n",las=1,xaxs="i",yaxs="i",cex.lab=1,cex.axis=1.5,xlim=c(x.lim.min,x.lim.max),ylim=c(0,cv$maxdmx*2.1),ylab="",xlab="",xaxp=c(x.lim.min,x.lim.max,20),main=bquote(paste("Intervalles de confiance:")),cex.main=cex.title)
         }
          
         if(v$hypPl != "false"){
             if(v$test == "="){# bilateral
                 plot(c(0),c(-5),lty=1,lwd=1,col="black",yaxt="n",bty="n",las=1,xaxs="i",yaxs="i",cex.lab=1,cex.axis=1.5,xlim=c(x.lim.min,x.lim.max),ylim=c(0,cv$maxdmx*2.1),ylab="",xlab="",xaxp=c(x.lim.min,x.lim.max,20),main=bquote(paste("Hypothèses ",H[0]," : ",mu," = ",.(v$mx0)," vs ",H[1]," : ",.(v$mx0)," ≠ ",mu,sep="")),cex.main=cex.title)
                 lines(x<-c(x.lim.min,x.lim.max),y<-c(.0025,+.0025),lty=1,lwd=3,col="gray")
                 points(v$mx0,.0025, pch=22,cex=2, col="black",bg="black")
             }
             if(v$test == "<="){#unilateral
                 plot(c(0),c(-5),lty=1,lwd=1,col="black",yaxt="n",bty="n",las=1,xaxs="i",yaxs="i",cex.lab=1,cex.axis=1.5,xlim=c(x.lim.min,x.lim.max),ylim=c(0,cv$maxdmx*2.1),ylab="",xlab="",xaxp=c(x.lim.min,x.lim.max,20),main=bquote(paste("Hypothèses ",H[0]," : ",mu," ≤ ",.(v$mx0)," vs ",H[1]," : ",.(v$mx0)," < ",mu,sep="")),cex.main=cex.title)
                 lines(x<-c(v$mx0,x.lim.max),y<-c(.0025,+.0025),lty=1,lwd=3,col="gray")
                 lines(x<-c(x.lim.min,v$mx0),y<-c(.0025,+.0025),lty=1,lwd=7,col="black")
                 points(v$mx0,.0025, pch=22,cex=2, col="black",bg="black")
             }
             if(v$test == "=>"){#unilateral
                 plot(c(0),c(-5),lty=1,lwd=1,col="black",yaxt="n",bty="n",las=1,xaxs="i",yaxs="i",cex.lab=1,cex.axis=1.5,xlim=c(x.lim.min,x.lim.max),ylim=c(0,cv$maxdmx*2.1),ylab="",xlab="",xaxp=c(x.lim.min,x.lim.max,20),main=bquote(paste("Hypothèses ",H[0]," : ",.(v$mx0)," ≤ ",mu," vs ",H[1]," : ",mu," < ",.(v$mx0),sep="")),cex.main=cex.title)
                 lines(x<-c(x.lim.min,v$mx0),y<-c(.0025,+.0025),lty=1,lwd=3,col="gray")
                 lines(x<-c(v$mx0,x.lim.max),y<-c(.0025,+.0025),lty=1,lwd=7,col="black")
                 points(v$mx0,.0025, pch=22,cex=2, col="black",bg="black")
             }
             if(v$hypPl == "true"){
                  lines(x<-c(v$mx0,v$mx0),y <- c(0,cv$maxdmx*1.8),lty=1,lwd=2,col=oui.color.true)
                  text(v$mx0,cv$maxdmx*1.95,labels=bquote(mu[.0]),cex=cex.param*0.75,col=oui.color.true)
              }
             if(v$hypPl == "realite" && v$mx0 == v$mx){
                 lines(x<-c(v$mx,v$mx),y <- c(0,cv$maxdmx*1.8),lty=1,lwd=2,col=color.mx)
                 text(v$mx,cv$maxdmx*1.95,labels=bquote(paste(mu[0],'=',mu)),cex=cex.param*0.75,col=color.true)
             }
             if(v$hypPl == "realite" && v$mx0 != v$mx){
                 lines(x<-c(v$mx0,v$mx0),y <- c(0,cv$maxdmx*1.8),lty=1,lwd=3,col=oui.color.true)
                 lines(x<-c(v$mx,v$mx),y <- c(0,cv$maxdmx*1.8),lty=1,lwd=3,col=color.mx)               
                 text(v$mx0,cv$maxdmx*1.95,labels=bquote(mu[0]),cex=cex.param,col=oui.color.true)
                 text(v$mx,cv$maxdmx*1.95,labels=bquote(mu),cex=cex.param,col=color.mx) 
             }     
         }
          if(debug){
              box(which="figure",lty = 'dotted', col = 'blue')
              box(which="plot",lty = 'dotted', col = 'blue')
          }
      }
      
      if(v$icPl){
          ##-------------------------------------------    
          ## Plot IC   ##
          ##-------------------------------------------              
          help.color.vec<-ifelse(cv$ic.k.inc.mu0.color.vec.toshow,"black","black")
          if(v$testicPl != "false"){
              if(v$hypPl == "true"){
                  help.color.vec<-cv$ic.k.inc.mu.color.vec.toshow
              }
              if(v$test == "="){#bilateral
                  if(v$hypPl == "realite" && v$mx0 == v$mx){
                      help.color.vec<-cv$ic.k.inc.mu1.color.vec.toshow
                  }
                  if(v$hypPl == "realite" && v$mx0 != v$mx){  
                      help.color.vec<-cv$ic.k.inc.mu0.color.vec.toshow
                  }
              }
              if(v$test == "<="){#unilateral
                  if(v$hypPl == "realite" && v$mx <= v$mx0){
                      help.color.vec<-cv$ic.k.inc.mu1.color.vec.toshow
                  }
                  if(v$hypPl == "realite" && v$mx0 < v$mx){  
                      help.color.vec<-cv$ic.k.inc.mu0.color.vec.toshow
                  }
              }
              if(v$test == "=>"){#unilateral
                  if(v$hypPl == "realite" && v$mx0 <= v$mx){
                      help.color.vec<-cv$ic.k.inc.mu1.color.vec.toshow
                  }
                  if(v$hypPl == "realite" && v$mx < v$mx0){  
                      help.color.vec<-cv$ic.k.inc.mu0.color.vec.toshow
                  }
              }
              
          }
          if(cv$samples.x.n.toshow>0){
              for(i in 1:cv$samples.x.n.toshow){
                  polygon(c(cv$ic.k.limit.mat.toshow[i,1],cv$ic.k.limit.mat.toshow[i,1],cv$ic.k.limit.mat.toshow[i,2],cv$ic.k.limit.mat.toshow[i,2]),c(cv$samples.y.mat.toshow[i,1]-0.0025,cv$samples.y.mat.toshow[i,1]+0.0025,cv$samples.y.mat.toshow[i,1]+0.0025,cv$samples.y.mat.toshow[i,1]-0.0025),col=help.color.vec[i])
                  text(cv$samples.x.m.vec.toshow[i],cv$samples.y.mat.toshow[i,1],labels=bquote(bar(x)[.(cv$samples.x.i.vec.toshow[i])]),cex=cex.samples*1.2,col="blue")
                  lines(x<-c(cv$ic.k.limit.mat.toshow[i,1],cv$samples.x.m.vec.toshow[i]-1),y <- c(cv$samples.y.mat.toshow[i,1],cv$samples.y.mat.toshow[i,1]),lwd=1,lty=2,col="black")
                  lines(x<-c(cv$samples.x.m.vec.toshow[i]+1,cv$ic.k.limit.mat.toshow[i,2]),y <- c(cv$samples.y.mat.toshow[i,1],cv$samples.y.mat.toshow[i,1]),lwd=1,lty=2,col="black")
              }
          }
      }

      if(v$icPl || (v$hypPl != "false")){
          ##-------------------------------------------    
          ## Plot IC  or Hyportheis    ##
          ##-------------------------------------------              
          ## empty plot for layout
          par(mai=c(0.3,0,0.5,0))
          if((v$testicPl == "testPl" ||  v$testicPl == "rejFreqPl") && v$empPl){
                  plot(c(0,1),c(0,0),col="white",xaxt="n",yaxt="n",xlab="",ylab="",ylim=c(0,cv$maxdmx*2.1),bty="n",las=1,main=bquote(paste("Rejet de ",H[0]," ? ",sep="")),cex.main=cex.title)
          } else {
              plot(c(0,1),c(0,0),col="white",xaxt="n",yaxt="n",xlab="",ylab="",ylim=c(0,cv$maxdmx*2.1),bty="n",las=1)
          }
          if(debug){
              box(which="figure",lty = 'dotted', col = 'blue')
              box(which="plot",lty = 'dotted', col = 'blue')
          }
      }
      if(v$empPl && v$icPl){
          if(!v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
              mtext(bquote(paste("Intervalles : ", N == .(cv$n.samples), sep="")),side=1,line=1,at=0.05,adj=0)
          } else {
              mtext(bquote(paste("Décisions : ", N == .(cv$n.samples), sep="")),side=1,line=1,at=0.05,adj=0)
          }
          if(cv$samples.x.n.toshow>0){
              for(i in 1:cv$samples.x.n.toshow){ 
                  help.color.vec<-ifelse(cv$ic.k.inc.mu0.color.vec.toshow,"black","black")
                  if(v$testicPl != "false"){
                      if(v$hypPl == "true"){
                          help.color.vec<-cv$ic.k.inc.mu.color.vec.toshow
                      }
                      if(v$test == "="){#bilateral
                          if(v$hypPl == "realite" && v$mx == v$mx0){
                              help.color.vec<-cv$ic.k.inc.mu1.color.vec.toshow
                          }
                          if(v$hypPl == "realite" && v$mx != v$mx0){
                              help.color.vec<-cv$ic.k.inc.mu0.color.vec.toshow
                          }
                      }
                      if(v$test == "<="){#unilateral
                          if(v$hypPl == "realite" && v$mx <= v$mx0){
                              help.color.vec<-cv$ic.k.inc.mu1.color.vec.toshow
                          }
                          if(v$hypPl == "realite" && v$mx0 < v$mx){
                              help.color.vec<-cv$ic.k.inc.mu0.color.vec.toshow
                          }
                      }
                      if(v$test == "=>"){#unilateral
                          if(v$hypPl == "realite" && v$mx0 <= v$mx){
                              help.color.vec<-cv$ic.k.inc.mu1.color.vec.toshow
                          }
                          if(v$hypPl == "realite" && v$mx < v$mx0){
                              help.color.vec<-cv$ic.k.inc.mu0.color.vec.toshow
                          }
                      }
                      
                  }
                  if(v$thresholds == "formula"){
                      if(v$CVk == 'eCVk'){
                          if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                             if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                                 if(v$test == "="){#bilateral
                                     text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0] %in% group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c,bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                 }
                                 if(v$test == "<="){#unilateral
                                     text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c<=mu[0] %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                 }
                                 if(v$test == "=>"){#unilateral
                                     text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]<=bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                 }

                             } else {
                                 if(v$test == "="){#bilateral
                                     text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0] %notin% group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c,bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                 }
                                 if(v$test == "=>"){#unilateral
                                     text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c<mu[0] %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                 }
                                 if(v$test == "<="){#unilateral
                                     text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]<bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                 }
 
                             }
                         } else {
                             text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c,bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                         }
                      }
                      if(v$CVk == 'vCVk'){
                          if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                              if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0] %in% group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]%+-%c*'*'*sigma/sqrt(n)),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c*'*'*sigma/sqrt(n)<=mu[0] %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]<=bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c*'*'*sigma/sqrt(n) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                  
                              } else {
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]%notin% group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]%+-%c*'*'*sigma/sqrt(n)),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c*'*'*sigma/sqrt(n)<mu[0] %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]<bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c*'*'*sigma/sqrt(n) %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                                                    
                              }
                          } else {
                              text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c*'*'*sigma/sqrt(n),bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c*'*'*sigma/sqrt(n)),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                          }
                      }
                      if(v$CVk == 'sCVk'){
                          if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                              if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0] %in% group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]%+-%c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n)),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n)<=mu[0] %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]<=bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                  
                              } else {
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0] %notin% group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]%+-%c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n)),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n)<mu[0] %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(mu[0]<bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n) %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                                                    
                              }
                          } else {
                              text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(bar(x)[.(cv$samples.x.i.vec.toshow[i])]-c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n),bar(x)[.(cv$samples.x.i.vec.toshow[i])]+c*'*'*s[.(cv$samples.x.i.vec.toshow[i])]/sqrt(n)),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                          }
                      }
                  }
                  if(v$thresholds == "calcul"){
                      if(v$CVk == 'eCVk'){
                          if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                              if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %in% group("[",list(.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))-.(v$k)<=.(v$mx0) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<=.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))+.(v$k) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                  
                              } else {
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %notin% group("[",list(.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))+.(v$k)<.(v$mx0) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))-.(v$k) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                  
                              }
                          } else {
                              text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))-.(v$k),.(sprintf("%.2f",cv$samples.x.m.vec.toshow[i]))+.(v$k)),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                          }
                      }
                      if(v$CVk == 'vCVk'){
                          if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                              if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %in% group("[",list(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5))),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))-.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5))<=.(v$mx0) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<=.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))+.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5)) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                 
                              } else {
                                  if(v$test == "="){#bilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %notin% group("[",list(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5))),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))+.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5))<.(v$mx0) %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))-.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5)) %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                                  }                                                                   
                              }
                          } else {
                              text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)*'*'*.(v$sx)/.(sprintf("%.1f",v$n^.5))),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                          }
                      }
                      if(v$CVk == 'sCVk'){
                          if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                              if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                                  if(v$test == "="){#bilateral
                                      text(-0.02,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %in% group("[",list(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5))),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples*.9,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(-0.02,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))-.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5))<=.(v$mx0) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples*.9,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(-0.02,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<=.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))+.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5)) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples*.9,pos=4)
                                  }
                              } else {
                                  if(v$test == "="){#bilateral
                                      text(-0.02,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %notin% group("[",list(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5))),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples*.9,pos=4)
                                  }
                                  if(v$test == "=>"){#unilateral
                                      text(-0.02,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))+.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5))<.(v$mx0) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples*.9,pos=4)
                                  }
                                  if(v$test == "<="){#unilateral
                                      text(-0.02,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))-.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5)) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples*.9,pos=4)
                                  }
                              }
                          } else {
                              text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(.(sprintf("%.1f",cv$samples.x.m.vec.toshow[i]))%+-%.(v$k)*'*'*.(sprintf("%.1f",cv$samples.x.sd.vec.toshow[i]))/.(sprintf("%.1f",v$n^.5))),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                          }
                      }
                  }
                  if(v$thresholds == "result"){
                      if(v$testicPl == "testPl" || v$testicPl == "rejFreqPl"){
                          if(cv$ic.k.inc.allmu.mat.toshow[i,v$mx0-mu.vec[1]+1]){
                              if(v$test == "="){#bilateral
                                  text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %in% group("[",list(.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,1])),.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,2]))),"]") %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                              }
                              if(v$test == "<="){#unilateral
                                  text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,1]))<=.(v$mx0) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                              }
                              if(v$test == "=>"){#unilateral
                                  text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<=.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,2])) %=>% 'Non',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                              }                             
                          } else {
                              if(v$test == "="){#bilateral
                                  text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0) %notin% group("[",list(.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,1])),.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,2]))),"]") %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                              }
                              if(v$test == "=>"){#unilateral
                                  text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,2]))<.(v$mx0) %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                              }
                              if(v$test == "<="){#unilateral
                                  text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(.(v$mx0)<.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,1])) %=>% 'Oui',sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                              }                                                           
                          }
                      } else {                                      
                          text(0,cv$samples.y.mat.toshow[i,1],bquote(paste(group("[",list(.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,1])),.(sprintf("%.2f",cv$ic.k.limit.mat.toshow[i,2]))),"]"),sep="")),las=2,col=help.color.vec[i],cex=cex.samples,pos=4)
                      }
                  }
              }
          }
      }
     


      if(v$icPl && (v$hypPl != "false") && v$testicPl == "rejFreqPl"){
          par(mai=c(0.3,0.6,0.5,0))
          ## Plot only if realité known
          xlab.text<-""
          if(cv$n.samples>0){
              if(v$hypPl == "realite"){
                  includes<-t(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec,cv$pc.ic.k.mu0.inc.allmu.vec),ncol=2))
                  xlab.text<-bquote(paste("Moyenne ",mu," de la population d'origine",sep =" "))
                  my.color.vec<-c(non.color.false,non.color.true)
              } else {
                  includes<-t(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec,cv$pc.ic.k.mu0.inc.allmu.vec),ncol=2))
                  xlab.text<-bquote(paste("Moyenne ",mu[0]," de la Hypothèse ",H[0],sep =" "))
                  my.color.vec<-c("white","white")
              }
          } else {
              includes<-t(matrix(c(rep(0,length(mu.vec)),100-rep(0,length(mu.vec))),ncol=2))
              my.color.vec<-c("white","white")
          }

          if(v$hypPl == "realite"){
              barplot.kH1<-barplot(includes,names.arg=mu.vec,xlab="",ylim=c(0,100),col=my.color.vec,cex.names=1.25,cex.axis=1.5,beside=FALSE,xaxs="i",space=0,yaxt="n",las=2)
              axis(2,las=2,yaxp=c(0,100,2),cex.axis=1.5)#to have las=2 for horizontal labels on y axis
              mtext("%",side=2,line=3,at=50)
              title(main=bquote(paste("% de rejet de ",H[0]," lorsque ",mu," = ",.(v$mx)," est la moyenne de la population d'origine",sep=" ")),cex.main=cex.title)
          } else {
               barplot.kH1<-barplot(includes,names.arg=rep("",length(mu.vec)),xlab="",ylim=c(0,100),col=my.color.vec,cex.names=1.25,cex.axis=1.5,beside=FALSE,xaxs="i",space=0,yaxt="n",las=2,border = NA)
               title(main=bquote(paste("% de rejet de ",H[0],sep=" ")),cex.main=cex.title)
          }
          
          if(debug){
              box(which="figure",lty = 'dotted', col = 'blue')
              box(which="plot",lty = 'dotted', col = 'blue')
          }

                                        #  barplot.kH1 is the vector of positions of th bars which we use next
          if(v$hypPl == "true" && cv$n.samples>0){
           barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(oui.color.false,oui.color.true), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
          }
          if(v$test == "="){#bilateral
              if(v$hypPl == "realite" && v$mx0 == v$mx && cv$n.samples>0){
                  barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(color.false,color.true), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
              }
              if(v$hypPl == "realite" && v$mx0 != v$mx && cv$n.samples>0){
                  barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(color.true,color.false), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
              }
          }
          if(v$test == "<="){#unilateral
              if(v$hypPl == "realite" && v$mx <= v$mx0 && cv$n.samples>0){
                  barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(color.false,color.true), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
              }
              if(v$hypPl == "realite" && v$mx0 < v$mx && cv$n.samples>0){
                  barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(color.true,color.false), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
              }
          }
          if(v$test == "=>"){#bilateral
              if(v$hypPl == "realite" && v$mx0 <= v$mx && cv$n.samples>0){
                  barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(color.false,color.true), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
              }
              if(v$hypPl == "realite" && v$mx < v$mx0 && cv$n.samples>0){
                  barplot.spp<-barplot(matrix(c(100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=1),col=c(color.true,color.false), add=TRUE,beside=FALSE,space=(barplot.kH1[(v$mx-mu.vec[1]+1)]-0.5),axes=FALSE)
              }
          }
          
      }
      
      if((v$hypPl != "false") && v$testicPl == "rejFreqPl" && v$empPl){
          ## empty plot descriptives
          par(mai=c(0.3,0,0.5,0))
          plot(c(0,1),c(0,0),col="white",xaxt="n",yaxt="n",xlab="",ylab="",ylim=c(0,cv$maxdmx*2.1),bty="n",las=1)
	  if(debug){
              box(which="figure",lty = 'dotted', col = 'blue')
              box(which="plot",lty = 'dotted', col = 'blue')
          }
          if(v$hypPl == "true"){
              y.max<-cv$maxdmx*2.              
              text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0]," ?",sep=" ")),cex=cex.samples)
              text(0.425,y.max*0.6,bquote(paste("n",sep=" ")),cex=cex.samples)
              text(0.675,y.max*0.6,bquote(paste("%",sep=" ")),cex=cex.samples)
              text(0.175,y.max*0.4,"Non",col=text.color.true,cex=cex.samples*0.85)
              text(0.175,y.max*0.2,"Oui",col=text.color.false,cex=cex.samples*0.85)
              if(cv$n.samples>0){
                  ICvsmu0.mat<-matrix(c(cv$n.ic.k.inc.allmu.vec[(v$mx0-mu.vec[1]+1)],cv$n.samples-cv$n.ic.k.inc.allmu.vec[(v$mx0-mu.vec[1]+1)],cv$pc.ic.k.inc.allmu.vec[(v$mx0-mu.vec[1]+1)],100-cv$pc.ic.k.inc.allmu.vec[(v$mx0-mu.vec[1]+1)]),ncol=2)
                  ICvsmu0.mat<-round(ICvsmu0.mat,0)
                  text(0.425,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,1]),sep=" ")),col=text.color.true,cex=cex.samples)
                  text(0.675,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,2]),sep=" ")),col=text.color.true,cex=cex.samples)
                  text(0.425,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,1]),sep=" ")),col=text.color.false,cex=cex.samples)
                  text(0.675,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,2]),sep=" ")),col=text.color.false,cex=cex.samples)
		}
              }
          if(v$test == "<="){#unilateral
              if(v$hypPl == "realite" && v$mx <= v$mx0){
                  y.max<-cv$maxdmx*2.1
                  text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0],", si ",mu,"=",.(v$mx)," ?",sep=" ")),cex=cex.samples)
                  text(0.425,y.max*0.6,bquote(paste("n",sep=" ")),cex=cex.samples)
                  text(0.675,y.max*0.6,bquote(paste("%",sep=" ")),cex=cex.samples)
                  text(0.175,y.max*0.4,"Non",col=color.true,cex=cex.samples*0.85)
                  text(0.175,y.max*0.2,"Oui",col=color.false,cex=cex.samples*0.85)
                  if(cv$n.samples>0) {
                      ICvsmu0.mat<-matrix(c(cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$n.samples-cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=2)
                      ICvsmu0.mat<-round(ICvsmu0.mat,0)
                      text(0.425,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,1]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.675,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,2]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.425,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,1]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.675,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,2]),sep=" ")),col=color.false,cex=cex.samples)
                  }
              }
              if(v$hypPl == "realite" && v$mx0 < v$mx){
                  y.max<-cv$maxdmx*2.1
                  text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0],", si ",mu,"=",.(v$mx)," ?",sep=" ")),cex=cex.samples)
                  text(0.425,y.max*0.6,bquote(paste("n",sep=" ")),cex=cex.samples)
                  text(0.675,y.max*0.6,bquote(paste("%",sep=" ")),cex=cex.samples)
                  text(0.175,y.max*0.4,"Non",col=color.false,cex=cex.samples*0.85)
                  text(0.175,y.max*0.2,"Oui",col=color.true,cex=cex.samples*0.85)
                  if(cv$n.samples>0) {
                      ICvsmu0.mat<-matrix(c(cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$n.samples-cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=2)
                      ICvsmu0.mat<-round(ICvsmu0.mat,0)
                      text(0.425,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,1]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.675,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,2]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.425,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,1]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.675,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,2]),sep=" ")),col=color.true,cex=cex.samples)
                  }
              }
          }
          if(v$test == "=>"){#unilateral
              if(v$hypPl == "realite" && v$mx0 <= v$mx){
                  y.max<-cv$maxdmx*2.1
                  text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0],", si ",mu,"=",.(v$mx)," ?",sep=" ")),cex=cex.samples)
                  text(0.425,y.max*0.6,bquote(paste("n",sep=" ")),cex=cex.samples)
                  text(0.675,y.max*0.6,bquote(paste("%",sep=" ")),cex=cex.samples)
                  text(0.175,y.max*0.4,"Non",col=color.true,cex=cex.samples*0.85)
                  text(0.175,y.max*0.2,"Oui",col=color.false,cex=cex.samples*0.85)
                  if(cv$n.samples>0) {
                      ICvsmu0.mat<-matrix(c(cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$n.samples-cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=2)
                      ICvsmu0.mat<-round(ICvsmu0.mat,0)
                      text(0.425,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,1]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.675,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,2]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.425,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,1]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.675,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,2]),sep=" ")),col=color.false,cex=cex.samples)
                  }
              }
              if(v$hypPl == "realite" && v$mx < v$mx0){
                  y.max<-cv$maxdmx*2.1
                  text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0],", si ",mu,"=",.(v$mx)," ?",sep=" ")),cex=cex.samples)
                  text(0.425,y.max*0.6,bquote(paste("n",sep=" ")),cex=cex.samples)
                  text(0.675,y.max*0.6,bquote(paste("%",sep=" ")),cex=cex.samples)
                  text(0.175,y.max*0.4,"Non",col=color.false,cex=cex.samples*0.85)
                  text(0.175,y.max*0.2,"Oui",col=color.true,cex=cex.samples*0.85)
                  if(cv$n.samples>0) {
                      ICvsmu0.mat<-matrix(c(cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$n.samples-cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=2)
                      ICvsmu0.mat<-round(ICvsmu0.mat,0)
                      text(0.425,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,1]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.675,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,2]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.425,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,1]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.675,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,2]),sep=" ")),col=color.true,cex=cex.samples)
                  }
              }
          }
          if(v$test == "="){#bilateral
              if(v$hypPl == "realite" && v$mx0 == v$mx){
                  y.max<-cv$maxdmx*2.1
                  text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0],", si ",mu,"=",.(v$mx)," ?",sep=" ")),cex=cex.samples)
                  text(0.425,y.max*0.6,bquote(paste("n",sep=" ")),cex=cex.samples)
                  text(0.675,y.max*0.6,bquote(paste("%",sep=" ")),cex=cex.samples)
                  text(0.175,y.max*0.4,"Non",col=color.true,cex=cex.samples*0.85)
                  text(0.175,y.max*0.2,"Oui",col=color.false,cex=cex.samples*0.85)
                  if(cv$n.samples>0) {
                      ICvsmu0.mat<-matrix(c(cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$n.samples-cv$n.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)],100-cv$pc.ic.k.mu0.inc.allmu.vec[(v$mx-mu.vec[1]+1)]),ncol=2)
                      ICvsmu0.mat<-round(ICvsmu0.mat,0)
                      text(0.425,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,1]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.675,y.max*0.4,bquote(paste(.(ICvsmu0.mat[1,2]),sep=" ")),col=color.true,cex=cex.samples)
                      text(0.425,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,1]),sep=" ")),col=color.false,cex=cex.samples)
                      text(0.675,y.max*0.2,bquote(paste(.(ICvsmu0.mat[2,2]),sep=" ")),col=color.false,cex=cex.samples)
                  }
              }
              if(v$hypPl == "realite" && v$mx0 != v$mx){
                  y.max<-cv$maxdmx*2.1
                  text(0.425,y.max*0.8,bquote(paste("Rejettent ",H[0],", si ",mu,"=",.(v$mx)," ?",sep=" ")),cex=cex.samples)
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