Update app.R

app.R

@@ -1,58 +1,297 @@
 library(shiny)
-library(bslib)
-library(dplyr)
-library(ggplot2)
-
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
-
-ui <- page_sidebar(
-  theme = bs_theme(bootswatch = "minty"),
-  title = "Penguins explorer",
-  sidebar = sidebar(
-    varSelectInput("xvar", "X variable", df_num, selected = "Bill Length (mm)"),
-    varSelectInput("yvar", "Y variable", df_num, selected = "Bill Depth (mm)"),
-    checkboxGroupInput("species", "Filter by species",
-      choices = unique(df$Species), selected = unique(df$Species)
+library(DT)
+library(shinyWidgets)
+library(data.table)
+library(stringr)
+library(markdown)
+
+data <- readRDS("donnees_nettes/dolq_min.RDS") |> setDT()
+
+readme_content <- readLines("README.md", warn = FALSE)
+
+source("Fonctions.R")
+
+ui <- fluidPage(
+  titlePanel("Dictionnaire des oeuvres littéraires du Québec, t. 1-6"),
+  tabsetPanel(
+    tabPanel("Recherche plein texte",
+    sidebarLayout(
+      sidebarPanel(
+        noUiSliderInput(inputId = "date_range", 
+                        label = "Sélectionner une période:",
+                        min = 1830,
+                        max = 1980,
+                        value = c(1830, 1980),
+                        format = wNumbFormat(decimals = 0),
+                        tooltips = TRUE),
+        br(),
+
+        pickerInput(
+          inputId = "column",
+          label = h5("Choisissez les colonnes où effectuer la recherche:"),
+          choices = c("Auteur_oeuvre", "Titre", "Auteur_notice", "Article",
+                      "Depouillement", "Details_bibliographiques"),
+          selected = "Article",
+          options = list(`actions-box` = TRUE),
+          multiple = TRUE
+        ),
+        pickerInput(
+          inputId = "additional_columns",
+          label = h5("Choisissez les colonnes à afficher:"),
+          choices = c("Id", "Auteur_oeuvre", "Titre", "Annee_parution",  "Auteur_notice", "Article", "Volume", "Depouillement", "Details_bibliographiques"),
+          selected = c("Auteur_oeuvre", "Titre", "Article"),
+          options = list(`actions-box` = TRUE),
+          multiple = TRUE
+        ),
+        textInput(
+          inputId = "motcle",
+          label = h5("Chaine de caractères à rechercher"),
+          value = "Montréal"
+        ),
+        prettySwitch(
+          inputId = "regex",
+          label = "Utiliser une expression régulière?",
+          fill = FALSE,
+          status = "primary"
+        ),
+        downloadButton("downloadData", "Exporter le résultat de la table (csv)"),
+        width = 4,
+         hr(),
+        
+        tags$head(tags$link(rel = "stylesheet", href = "https://maxcdn.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css")),
+        
+        
+        h5("Antisèche - expressions régulières"),
+        tags$a(href = "regex.pdf", target = "_blank",
+               tags$img(src = "regex.jpg", alt = "Thumbnail", width = "100%")),
+        
+        hr(),
+        h5("Accéder aux volumes (pdf)"),
+        # Add clickable images for each volume
+        tags$a(href = "https://crilcq.org/dictionnaire-des-oeuvres-litteraires-du-quebec-tome-1-des-origines-a-1900/", target = "_blank",
+               tags$img(src = "DOLQ_01.jpg", alt = "Volume 1", width = "50%")),
+        tags$a(href = "https://crilcq.org/dictionnaire-des-oeuvres-litteraires-du-quebec-tome-2-1900-a-1939/", target = "_blank",
+               tags$img(src = "DOLQ_02.jpg", alt = "Volume 2", width = "50%")),
+        tags$a(href = "https://crilcq.org/dictionnaire-des-oeuvres-litteraires-du-quebec-tome-3-1940-a-1959/", target = "_blank",
+               tags$img(src = "DOLQ_03.jpg", alt = "Volume 3", width = "50%")),
+        tags$a(href = "https://crilcq.org/dictionnaire-des-oeuvres-litteraires-du-quebec-tome-4-1960-1969/", target = "_blank",
+               tags$img(src = "DOLQ_04.jpg", alt = "Volume 4", width = "50%")),
+        tags$a(href = "https://crilcq.org/dictionnaire-des-oeuvres-litteraires-du-quebec-tome-5-1970-1975/", target = "_blank",
+               tags$img(src = "DOLQ_05.jpg", alt = "Volume 5", width = "50%")),
+        tags$a(href = "https://crilcq.org/dictionnaire-des-oeuvres-litteraires-du-quebec-tome-5-1970-1975/", target = "_blank",
+               tags$img(src = "DOLQ_06.jpg", alt = "Volume 6", width = "50%")),
+      ),
+      
+      mainPanel(h3("Distribution chronologique des notices"),
+                
+                radioButtons(inputId = "dist_type", 
+                             label = "Type de distribution:",
+                             choices = list("Distribution brute" = "raw", 
+                                            "Distribution relative" = "relative"),
+                             selected = "raw"),
+                
+                numericInput("num_breaks", label = "Nombre d'intervalles:", value = 65, min = 1),
+              
+                plotOutput("histogram"),
+                
+                downloadButton("download_graph", "Exporter le graphique"),
+                downloadButton("download_table", "Exporter les données du graphique"),
+                
+                h3("Table"),
+                textOutput("filtered_count"),
+                DT::dataTableOutput('table'))
+    )
     ),
-    hr(), # Add a horizontal rule
-    checkboxInput("by_species", "Show species", TRUE),
-    checkboxInput("show_margins", "Show marginal plots", TRUE),
-    checkboxInput("smooth", "Add smoother"),
-  ),
-  plotOutput("scatter")
+    
+    # Second tab: Documentation
+    
+    tabPanel("Documentation",
+             uiOutput("readme") 
+    )
+  )
 )
 
-server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
-  })
-
-  output$scatter <- renderPlot(
-    {
-      p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) +
-        theme_light() +
-        list(
-          theme(legend.position = "bottom"),
-          if (input$by_species) aes(color = Species),
-          geom_point(),
-          if (input$smooth) geom_smooth()
-        )
-
-      if (input$show_margins) {
-        margin_type <- if (input$by_species) "density" else "histogram"
-        p <- p |> ggExtra::ggMarginal(
-          type = margin_type, margins = "both",
-          size = 8, groupColour = input$by_species, groupFill = input$by_species
-        )
-      }
+server <- function(input, output) {
 
-      p
+  reactive_data <- reactive({
+    filter_data(data, input, input$additional_columns)
+  })
+  
+  reactive_data1 <- reactive({
+    filter_data(data, input)
+  })
+  
+  filtered_count <- reactive({
+    nrow(reactive_data())
+  })
+  
+  hist_data <- reactive({
+    if ("Annee_unique" %in% names(reactive_data1()) && nrow(reactive_data1()) > 0) {
+      # Ensure the data is numeric
+      data_numeric <- as.numeric(reactive_data1()[, Annee_unique])
+      
+      # Remove NA values
+      data_numeric <- na.omit(data_numeric)
+      
+      if (length(data_numeric) > 0) {
+        min_year <- min(data_numeric)
+        max_year <- max(data_numeric)
+        breaks_hist <- seq(min_year, max_year, length.out = input$num_breaks + 1)
+        
+        # Raw counts
+        raw_counts <- hist(data_numeric, plot=FALSE, breaks=breaks_hist)$counts
+        
+        # Relative counts
+        total_counts <- hist(data[data$Annee_unique %in% reactive_data1()[, Annee_unique], Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+        
+        relative_counts <- ifelse(total_counts == 0, 0, raw_counts / total_counts)
+        
+        breaks <- round(seq(min_year, max_year, length.out = length(raw_counts)))
+        
+        # Return data based on user's selection
+        if (input$dist_type == "raw") {
+          return(data.frame(Breaks = breaks, Counts = raw_counts))
+        } else {
+          return(data.frame(Breaks = breaks, RelativeCounts = relative_counts))
+        }
+      }
+    }
+    # Ensure a dataframe is always returned
+    return(data.frame(Breaks = numeric(0), Counts = numeric(0)))
+  })
+  
+  
+  output$filtered_count <- renderText({
+    paste("Nombre de notices filtrées:", filtered_count())
+  })
+  
+  output$table <- DT::renderDataTable({
+    datatable(reactive_data(), options = list(searching = FALSE), 
+              callback = JS(paste0("
+                table.on('draw.dt', function() {
+                  var keyword = '", input$motcle, "';
+                  $('td').each(function() {
+                    var content = $(this).html();
+                    var highlighted = content.replace(new RegExp(keyword, 'gi'), function(match) {
+                      return '<span style=\"background-color: yellow;\">' + match + '</span>';
+                    });
+                    $(this).html(highlighted);
+                  });
+                });
+              ")))
+  })
+  
+  output$downloadData <- downloadHandler(
+    filename = function() {
+      paste("filtered_data-", Sys.Date(), ".csv", sep="")
     },
-    res = 100
+    content = function(file) {
+      fwrite(reactive_data(), file)
+    }
   )
+  
+  output$histogram <- renderPlot({
+    # Check if 'Annee_unique' column exists and has data
+    if ("Annee_unique" %in% names(reactive_data1()) && nrow(reactive_data1()) > 0) {
+      min_year <- min(na.omit(reactive_data1()[, Annee_unique]))
+      max_year <- max(na.omit(reactive_data1()[, Annee_unique]))
+      breaks_hist <- seq(min_year, max_year, length.out = input$num_breaks + 1)
+      
+      if (input$dist_type == "raw") {
+        hist(reactive_data1()[, Annee_unique],
+             main = "Distribution brute des notices",
+             xlab = "Année",
+             ylab = "Nombre",
+             border = "blue",
+             col = "lightblue",
+             breaks = breaks_hist)
+      } else {
+        # Compute relative distribution
+        filtered_counts <- hist(reactive_data1()[, Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+        total_counts <- hist(data[data$Annee_unique %in% reactive_data1()[, Annee_unique], Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+        relative_counts <- ifelse(total_counts == 0, 0, filtered_counts / total_counts)
+        
+        # Ensure names.arg matches the length of relative_counts
+        names_for_bars <- round(seq(min_year, max_year, length.out = length(relative_counts)))
+        
+        barplot(relative_counts, 
+                main = "Distribution relative des notices",
+                xlab = "Année",
+                ylab = "Fréquence relative",
+                border = "blue",
+                col = "lightblue",
+                space = 0,
+                names.arg = names_for_bars)
+      }
+    } else {
+      plot.new()
+      title(main = "No data available for the selected criteria")
+    }
+  })
+  
+  output$download_graph <- downloadHandler(
+    filename = function() {
+      paste("histogram_graph", Sys.Date(), ".png", sep = "_")
+    },
+    content = function(file) {
+      png(file)
+        # Check if 'Annee_unique' column exists and has data
+        if ("Annee_unique" %in% names(reactive_data1()) && nrow(reactive_data1()) > 0) {
+          min_year <- min(na.omit(reactive_data1()[, Annee_unique]))
+          max_year <- max(na.omit(reactive_data1()[, Annee_unique]))
+          breaks_hist <- seq(min_year, max_year, length.out = input$num_breaks + 1)
+          
+          if (input$dist_type == "raw") {
+            hist(reactive_data1()[, Annee_unique],
+                 main = "Distribution brute des notices",
+                 xlab = "Année",
+                 ylab = "Nombre",
+                 border = "blue",
+                 col = "lightblue",
+                 breaks = breaks_hist)
+          } else {
+            # Compute relative distribution
+            filtered_counts <- hist(reactive_data1()[, Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+            total_counts <- hist(data[data$Annee_unique %in% reactive_data1()[, Annee_unique], Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+            relative_counts <- ifelse(total_counts == 0, 0, filtered_counts / total_counts)
+            
+            # Ensure names.arg matches the length of relative_counts
+            names_for_bars <- round(seq(min_year, max_year, length.out = length(relative_counts)))
+            
+            barplot(relative_counts, 
+                    main = "Distribution relative des notices",
+                    xlab = "Année",
+                    ylab = "Fréquence relative",
+                    border = "blue",
+                    col = "lightblue",
+                    space = 0,
+                    names.arg = names_for_bars)
+          }
+        } else {
+          plot.new()
+          title(main = "No data available for the selected criteria")
+        }
+      dev.off()
+    }
+  )
+  
+  output$download_table <- downloadHandler(
+    filename = function() {
+      paste("histogram_data", Sys.Date(), ".csv", sep = "_")
+    },
+    content = function(file) {
+      write.csv(hist_data(), file, row.names = FALSE)
+    }
+  )
+  output$readme <- renderUI({
+    # Read the content of the README.md file
+    readme_content <- readLines("README.md", warn = FALSE)
+    
+    # Convert the markdown content to HTML for rendering in the Shiny app
+    HTML(markdown::markdownToHTML(text = readme_content, fragment.only = TRUE))
+  })
+  
 }
 
-shinyApp(ui, server)
+
+shinyApp(ui = ui, server = server)