AppShiny/MoreMess/ui.R

In cesco-lab/Vigie-Chiro_scripts: Predict Distribution Of Chiropter

#new ui
#authors: Jean-Fran?ois Julien and Yves Bas

# ui.R pour TadaridaShinyVigie-Chiro
library(ggvis)
library(shiny)
library(data.table)

SpeciesList <- fread("SpeciesList.csv", encoding = "Latin-1")
SpeciesList$color=factor(SpeciesList$Esp)
#groupes=unique(SpeciesList$GroupFR)
especes=unique(SpeciesList$Esp)


shinyUI(
  pageWithSidebar(
    # Application title
    headerPanel(""),# ("Analyse Tadarida"),
    # Sidebar with controls to select parameters to plot, group, species etc.
    # Note the use of the br()
    # element to introduce extra vertical spacing
    sidebarPanel(width = 2,     
                 # Input: Select a file ----
                 fileInput("fileParticipation", "Importer votre fichier de participation",
                           multiple = FALSE,
                           accept = c("text/csv",
                                      "text/comma-separated-values,text/plain",
                                      ".csv")),
                 #textInput("wavdirChoice", "Entrer le chemin d'accès répertoire son"),
                 actionButton("do", "Valider"),
                 #uiOutput("paramschoix"),
                 uiOutput("idchoix"),
                 uiOutput("especechoix"),
                 sliderInput("conf", #s?lection sur le score de Tadarida
                             label = "Indice de confiance de l'espèce :",
                             min = 0, max = 1, value = c(0.5, 1))
                 ,
                 sliderInput("frequence_mediane", #s?lection sur la fr?quence m?diane
                             label = "Frequence mediane",
                             min = 0, max = 250, value = c(0, 120))
                 
                 
                 ,
                 #uiOutput("espececorrige")
                 selectInput("espececorrige", #choix de validations
                             "Espece correction:",
                             c(especes))
                 ,
                 selectInput("probacorrige", #choix de validations
                             "Confiance:",
                             c("POSSIBLE","PROBABLE","SUR"))
                 ,
                 actionButton("submit","Valider") #pour soumettre cette validation
                 ,
                 downloadButton('downloadData', 'Sauver les corrections') #sauver les corrections
    ),
    mainPanel(
      
      tabsetPanel(
        tabPanel("titre",
                 shiny::column(9,
                               ggvisOutput("plot")),
                 shiny::column(11, offset = 1,
                               uiOutput("heures")),
                 tableOutput("testStr")
                 # ,
                 #shiny::column(12,
                 #             sliderInput("frequence_mediane",
                 #                     min = 0, max = 130, value = c(0, 130)
                 
        ),
        
        tabPanel("Table", dataTableOutput(outputId="table")),
        tabPanel("Dernier fichier ouvert"
                 ,
                 tableOutput(outputId="table2")
                 ,
                 dataTableOutput(outputId="table3")
                 # ,
                 # wellPanel(
                 # textInput('groupecorrige', "nouveau groupe","")
                 # ,
                 # textInput('espececorrige', "nouvelle espèce","")
                 # ,
                 # actionButton("submit","Valider")
        )
        # shiny::column(3,
        # selectInput("groupecorrige",
        # "Groupe :",
        # c("Tous",
        # groupes)))
        # ,
        # shiny::column(3, offset = 4,
        # selectInput("espececorrige",
        # "Espèce :",
        # c("Toutes",
        # colnames(seqScores))))
        # ,
        # shiny::column(3, offset = 3,
        # actionButton("update", "Valider la correction"))
        #       ,
        #      tableOutput(outputId="table3")
      )
      
    )
  )
)