Shiny App Reports

#Libraries
library(shiny)
library(jsonlite)
library(ggplot2)
library(shinydashboard)

# Histogram plot
create_histogram_plot <- function(hist_data, colors, title) {
  hist_df <- do.call(rbind, lapply(hist_data, function(h) {
    data.frame(Category = as.character(h$Category$`@value`),
               Count = as.numeric(h$Count$`@value`))
  }))
  
  ggplot(hist_df, aes(x = Category, y = Count, fill = Category)) +
    geom_bar(stat = "identity") +
    scale_fill_manual(values = colors) +
    labs(title = title, x = "Category", y = "Count") +
    theme_minimal()
}

# Line chart
create_line_chart <- function(line_data, title) {
  x_values <- as.numeric(line_data$X$`@value`)
  y_values <- as.numeric(line_data$Y$`@value`)
  
  ggplot(data.frame(X = x_values, Y = y_values), aes(x = X, y = Y)) +
    geom_line(color = "blue", size = 1) +
    labs(title = title, x = "X", y = "Y") +
    theme_minimal()
}

# Create boxplot
create_boxplot <- function(hist_data, title) {
  hist_df <- do.call(rbind, lapply(hist_data, function(h) {
    data.frame(Category = as.character(h$Category$`@value`),
               Count = as.numeric(h$Count$`@value`))
  }))
  
  ggplot(hist_df, aes(x = Category, y = Count)) +
    geom_boxplot() +
    labs(title = title, x = "Category", y = "Count") +
    theme_minimal()
}

# Statistical details
extract_statistical_details <- function(json_data) {
  if (!is.null(json_data$Histogram)) {
    hist_data <- json_data$Histogram
    values <- unlist(lapply(hist_data, function(h) as.numeric(h$Count$`@value`)))
    stats <- data.frame(
      Mean = mean(values, na.rm = TRUE),
      Median = median(values, na.rm = TRUE),
      SD = sd(values, na.rm = TRUE)
    )
    return(stats)
  }
  return(data.frame(Mean = NA, Median = NA, SD = NA))
}

# UI
ui <- dashboardPage(
  dashboardHeader(title = "DIZ Reports"),
  dashboardSidebar(
    sidebarMenu(
      menuItem("Upload Files", tabName = "uploads", icon = icon("file-upload")),
      menuItem("Visualize Data", tabName = "visualize", icon = icon("chart-bar")),
      menuItem("Statistical Details", tabName = "stats", icon = icon("info-circle")),
      menuItem("Download Output", tabName = "download", icon = icon("download"))
    )
  ),
  dashboardBody(
    tabItems(
      tabItem(tabName = "uploads",
              fileInput("file1", label = "University Hospital Dresden Report:"),
              fileInput("file2", label = "University Hospital Greifswald Report:"),
              fileInput("file3", label = "University Hospital Leipzig Report:"),
              selectInput("chart_type", label = "Chart Type:", choices = c("Histogram", "Line Chart", "Boxplot"))
      ),
      tabItem(tabName = "visualize",
              uiOutput("plots_output")
      ),
      tabItem(tabName = "stats",
              tableOutput("stats_output")
      ),
      tabItem(tabName = "download",
              downloadButton("download_plots", "Download Plots"),
              downloadButton("download_stats", "Download Statistical Data")
      )
    )
  )
)

# Server
server <- function(input, output) {
  # Generate plots
  all_plots <- reactive({
    plots <- list()
    for (i in 1:3) {
      file <- input[[paste0("file", i)]]
      if (!is.null(file) && file$name != "") {
        json_data <- tryCatch(fromJSON(file = file$datapath), error = function(e) NULL)
        if (!is.null(json_data)) {
          if (input$chart_type == "Histogram") {
            hist_data <- json_data$Histogram
            if (!is.null(hist_data)) {
              plot <- create_histogram_plot(hist_data, rainbow(10), paste("University Hospital", c("Dresden", "Greifswald", "Leipzig")[i]))
              plots <- c(plots, list(plot))
            } else {
              plots <- c(plots, list(ggplot() + ggtitle("No Histogram data found")))
            }
          } else if (input$chart_type == "Line Chart") {
            line_data <- json_data$LineChart
            if (!is.null(line_data)) {
              plot <- create_line_chart(line_data, paste("University Hospital", c("Dresden", "Greifswald", "Leipzig")[i]))
              plots <- c(plots, list(plot))
            } else {
              plots <- c(plots, list(ggplot() + ggtitle("No Line Chart data found")))
            }
          } else if (input$chart_type == "Boxplot") {
            hist_data <- json_data$Histogram
            if (!is.null(hist_data)) {
              plot <- create_boxplot(hist_data, paste("University Hospital", c("Dresden", "Greifswald", "Leipzig")[i]))
              plots <- c(plots, list(plot))
            } else {
              plots <- c(plots, list(ggplot() + ggtitle("No Boxplot data found")))
            }
          }
        } else {
          plots <- c(plots, list(ggplot() + ggtitle("Invalid JSON data")))
        }
      }
    }
    plots
  })
  
  # Generate statistical details
  all_stats <- reactive({
    stats_list <- list()
    for (i in 1:3) {
      file <- input[[paste0("file", i)]]
      if (!is.null(file) && file$name != "") {
        json_data <- tryCatch(fromJSON(file = file$datapath), error = function(e) NULL)
        if (!is.null(json_data)) {
          stats <- extract_statistical_details(json_data)
          stats_list[[i]] <- cbind(Hospital = c("Dresden", "Greifswald", "Leipzig")[i], stats)
        } else {
          stats_list[[i]] <- data.frame(Hospital = c("Dresden", "Greifswald", "Leipzig")[i], Mean = NA, Median = NA, SD = NA)
        }
      }
    }
    do.call(rbind, stats_list)
  })
  
  # Render the plots
  output$plots_output <- renderUI({
    plots <- all_plots()
    if (length(plots) > 0) {
      plot_ui_list <- lapply(1:length(plots), function(i) {
        plot_output_id <- paste0("plot_", i)
        checkbox_id <- paste0("checkbox_", i)
        column(
          width = 4,
          plotOutput(plot_output_id),
          checkboxInput(checkbox_id, label = paste("Show/Hide", c("Dresden", "Greifswald", "Leipzig")[i]), value = TRUE)
        )
      })
      fluidRow(plot_ui_list)
    } else {
      tagList(
        plot(1, type = "n", ann = FALSE),  # create an empty plot area
        text(1, 1, "No data to display", cex = 1.5)  # display a message in the empty plot area
      )
    }
  })
  
  # Render plots based on checkboxes
  observe({
    plots <- all_plots()
    for (i in 1:length(plots)) {
      local({
        plot_output_id <- paste0("plot_", i)
        checkbox_id <- paste0("checkbox_", i)
        output[[plot_output_id]] <- renderPlot({
          if (input[[checkbox_id]]) {
            plots[[i]]
          } else {
            NULL
          }
        })
      })
    }
  })
  
  # Render statistical details
  output$stats_output <- renderTable({
    all_stats()
  })
  
  # Download for plots
  output$download_plots <- downloadHandler(
    filename = function() { paste("plots-", Sys.Date(), ".pdf", sep = "") },
    content = function(file) {
      plots <- all_plots()
      pdf(file)
      for (plot in plots) {
        print(plot)
      }
      dev.off()
    }
  )
  
  # Download for statistical data
  output$download_stats <- downloadHandler(
    filename = function() { paste("stats-", Sys.Date(), ".csv", sep = "") },
    content = function(file) {
      stats <- all_stats()
      write.csv(stats, file, row.names = FALSE)
    }
  )
}

# Run the app
shinyApp(ui = ui, server = server)