app.R

# setwd("~/Downloads")
{
  # app.R
  options(error = NULL)
  
  # ------------------------------
  # 1. Load Packages
  # ------------------------------
  library(shiny)
  library(shinydashboard)
  library(leaflet)
  library(raster)
  library(DT)
  library(readr)
  library(dplyr)    # For data manipulation
  library(ggplot2) # For histogram
  library(RColorBrewer)
  library(sp)      # For handling map clicks/extracting raster values
  
  # ------------------------------
  # 2. Data & Config
  # ------------------------------
  
  # Define time periods corresponding to each band in the GeoTIFF
  time_periods <- c("1990–1992", "1993–1995", "1996–1998", "1999–2001", "2002–2004",
                    "2005–2007", "2008–2010", "2011–2013", "2014–2016", "2017–2019")
  
  # Load GeoTIFF data (multi-band)
  wealth_stack <- stack("wealth_map.tif")
  
  # Clean up out-of-range values
  wealth_stack[wealth_stack <= 0 | wealth_stack > 1] <- NA
  
  all_vals <- values(wealth_stack)
  all_vals <- all_vals[!is.na(all_vals)]
  q_breaks_legend <- quantile(all_vals, probs = seq(0, 1, 0.2), na.rm = TRUE)
  q_breaks <- quantile(all_vals, probs = seq(0, 1, 0.1), na.rm = TRUE)
  
  # Load improvement data (change in IWI by state/province)
  improvement_data <- read_csv("poverty_improvement_by_state.csv")
  
  # Pre-calculate the mean IWI for each band (for the "Trends Over Time" chart).
  band_means <- sapply(seq_len(nlayers(wealth_stack)), function(i) {
    vals <- values(wealth_stack[[i]])
    vals <- vals[!is.na(vals)]
    mean(vals)
  })
  
  # ------------------------------
  # 3. UI
  # ------------------------------
  ui <- dashboardPage(
    # -- Header
    dashboardHeader(
      title = span(
        style = "font-weight: 600; font-size: 18px;",
        a(
          href = "http://aidevlab.org", 
          "aidevlab.org", 
          target = "_blank",
          style = "font-family: 'OCR A Std', monospace; color: white; text-decoration: underline;"
        )
      ),
      titleWidth = 250
    ),
    
    # -- Sidebar
    dashboardSidebar(
      width = 250,
      tags$style(HTML("
        @media (max-width: 768px) {
          .sidebar-toggle { 
            padding: 15px !important;
          }
          .sidebar-toggle .icon-bar {
            width: 25px !important;
            height: 3px !important;
          }
        }
      ")),
      sidebarMenu(
        id = "tabs",
        menuItem("Wealth Map", tabName = "mapTab", icon = icon("map"), 
                 selected = TRUE),
        menuItem("Improvement Data", tabName = "improvementTab", icon = icon("table")),
        menuItem("Trends Over Time", tabName = "trendTab", icon = icon("chart-line"))
      ),
      # Show inputs only for the map tab
      conditionalPanel(
        condition = "input.tabs == 'mapTab'",
        br(),
        # Larger, more touch-friendly time period slider
        div(
          style = "padding: 15px 15px 15px 15px !important;", # top right bottom left
          sliderInput(
            inputId   = "time_index", 
            label     = tags$span(style = "font-size: 16px;", "Select Time Period:"),
            min       = 1, 
            max       = length(time_periods), 
            value     = 1,
            step      = 1,
            animate   = animationOptions(interval = 3300, loop = TRUE),
            width     = "100%"
          )
        ),
        # Show the currently selected year range clearly
        div(
          style = "padding: 0 15px; margin-bottom: 20px;",
          strong(style = "font-size: 16px;", "Selected Period:"),
          textOutput("current_year_range", inline = TRUE)
        ),
        
        div(
          style = "padding: 0 15px;",
          selectInput(
            "color_palette", 
            tags$span(style = "font-size: 16px;", "Color Palette:"),
            choices = c("Viridis" = "viridis", 
                        "Plasma" = "plasma", 
                        "Magma"  = "magma",
                        "Inferno"= "inferno",
                        "Spectral (Brewer)" = "Spectral"),
            selected = "plasma",
            width = "100%"
          )
        ),
        div(
          style = "padding: 0 15px; margin-bottom: 20px;",
          sliderInput(
            "opacity", 
            tags$span(style = "font-size: 16px;", "Map Opacity:"), 
            min = 0.2, 
            max = 1, 
            value = 0.8, 
            step = 0.1,
            width = "100%"
          )
        )
      ),
      # Share button with improved mobile styling
      tags$div(
        style = "text-align: center; margin: 20px 0;",
        HTML('
          <button id="share-button" 
                  style="
                    display: inline-flex;
                    align-items: center;
                    justify-content: center;
                    gap: 10px; 
                    padding: 12px 20px;
                    font-size: 18px;
                    font-weight: bold;
                    color: #000;
                    background-color: #fff;
                    border: 1px solid #ddd;
                    border-radius: 8px;
                    cursor: pointer;
                    box-shadow: 0 2px 0 #000;
                    width: 80%;
                  ">
            <svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" 
                 stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
              <circle cx="18" cy="5" r="3"></circle>
              <circle cx="6" cy="12" r="3"></circle>
              <circle cx="18" cy="19" r="3"></circle>
              <line x1="8.59" y1="13.51" x2="15.42" y2="17.49"></line>
              <line x1="15.41" y1="6.51" x2="8.59" y2="10.49"></line>
            </svg>
            <strong>Share</strong>
          </button>
        '),
        # Insert the JS as well
        tags$script(
          HTML("
            (function() {
              const shareBtn = document.getElementById('share-button');
              // Reusable helper function to show a small \"Copied!\" message
              function showCopyNotification() {
                const notification = document.createElement('div');
                notification.innerText = 'Copied to clipboard';
                notification.style.position = 'fixed';
                notification.style.bottom = '20px';
                notification.style.left = '50%';
                notification.style.transform = 'translateX(-50%)';
                notification.style.backgroundColor = 'rgba(0, 0, 0, 0.8)';
                notification.style.color = '#fff';
                notification.style.padding = '10px 16px';
                notification.style.borderRadius = '6px';
                notification.style.zIndex = '9999';
                notification.style.fontSize = '16px';
                document.body.appendChild(notification);
                setTimeout(() => { notification.remove(); }, 2000);
              }
              shareBtn.addEventListener('click', function() {
                const currentURL = window.location.href;
                const pageTitle  = document.title || 'Check this out!';
                // If browser supports Web Share API (most mobile browsers)
                if (navigator.share) {
                  navigator.share({
                    title: pageTitle,
                    text: '',
                    url: currentURL
                  })
                  .catch((error) => {
                    console.log('Sharing failed', error);
                  });
                } else {
                  // Fallback: Copy URL
                  if (navigator.clipboard && navigator.clipboard.writeText) {
                    navigator.clipboard.writeText(currentURL).then(() => {
                      showCopyNotification();
                    }, (err) => {
                      console.error('Could not copy text: ', err);
                    });
                  } else {
                    // Double fallback for older browsers
                    const textArea = document.createElement('textarea');
                    textArea.value = currentURL;
                    document.body.appendChild(textArea);
                    textArea.select();
                    try {
                      document.execCommand('copy');
                      showCopyNotification();
                    } catch (err) {
                      alert('Please copy this link:\\n' + currentURL);
                    }
                    document.body.removeChild(textArea);
                  }
                }
              });
            })();
          ")
        )
      )
    ),
    
    # -- Body
    dashboardBody(
      tags$head(
        # Viewport meta tag for proper mobile scaling
        tags$meta(name = "viewport", content = "width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no"),
        tags$link(rel = "stylesheet", href = "https://fonts.cdnfonts.com/css/ocr-a-std"),
        # Additional mobile-friendly styles
        tags$style(HTML("
          body {
            font-family: 'OCR A Std', monospace !important;
          }
          
          .slider-animate-button {
            background-color: #ffffff !important;
            color: #000000 !important;
            border: 2px solid #000000 !important;
            border-radius: 6px !important;
            padding: 8px 15px !important;
            font-size: 18px !important;
            margin-top: 10px !important;  
            margin-left: 5px !important; 
            opacity: 1 !important;
            top: 5px !important;
            position: relative !important;           /* enable top/left offsets */
          }
          
          .slider-animate-container {
            margin-top: 10px !important; /* Adjust this value as needed */
            margin-bottom: 20px !important;
          }

          /* Mobile-friendly boxes and layouts */
          @media (max-width: 768px) {
            .box {
              margin-bottom: 20px !important;
              border-radius: 8px !important;
            }
            
            .box-header {
              padding: 15px !important;
            }
            
            .box-title {
              font-size: 18px !important;
            }
            
            .box-body {
              padding: 15px !important;
            }
            
            .nav-tabs-custom .nav-tabs li a {
              padding: 15px !important;
              font-size: 16px !important;
            }
            
            /* Increase button sizes for touch */
            .btn {
              padding: 12px 18px !important;
              font-size: 16px !important;
            }
            
            /* Larger inputs and form controls */
            .form-control {
              height: 45px !important;
              font-size: 16px !important;
            }
            
            /* Improve DataTable mobile view */
            .dataTables_wrapper .dataTables_length,
            .dataTables_wrapper .dataTables_filter,
            .dataTables_wrapper .dataTables_info,
            .dataTables_wrapper .dataTables_paginate {
              text-align: center !important;
              float: none !important;
              margin-bottom: 10px !important;
            }
            
            /* Make sure text doesn't overflow on small screens */
            p, h1, h2, h3, h4, h5, h6 {
              word-wrap: break-word !important;
            }
          }
          
          /* Ensure value boxes stack nicely */
          .small-box {
            border-radius: 8px !important;
            margin-bottom: 20px !important;
          }
          
          .small-box .icon {
            font-size: 70px !important;
          }
          
          @media (max-width: 768px) {
            .small-box h3 {
              font-size: 24px !important;
            }
            
            .small-box p {
              font-size: 16px !important;
            }
            
            .small-box .icon {
              display: none !important;
            }
          }
          
          /* Make leaflet controls more touch friendly */
          .leaflet-touch .leaflet-control-layers,
          .leaflet-touch .leaflet-bar {
            border: 2px solid rgba(0,0,0,0.2) !important;
          }
          
          .leaflet-touch .leaflet-control-zoom-in,
          .leaflet-touch .leaflet-control-zoom-out {
            font-size: 18px !important;
            width: 34px !important;
            height: 34px !important;
            line-height: 34px !important;
          }
          
          /* Ensure plots are responsive */
          .shiny-plot-output {
            width: 100% !important;
            max-width: 100% !important;
          }
        "))
      ),
      tabItems(
        # ---------- MAP TAB ----------
        tabItem(
          tabName = "mapTab",
          fluidRow(
            column(
              width = 12,
              # Value Boxes - will stack on mobile
              div(
                class = "row",
                div(class = "col-sm-4 col-xs-12", valueBoxOutput("highest_iwi_vb", width = NULL)),
                div(class = "col-sm-4 col-xs-12", valueBoxOutput("lowest_iwi_vb", width = NULL)),
                div(class = "col-sm-4 col-xs-12", valueBoxOutput("avg_iwi_vb", width = NULL))
              )
            )
          ),
          fluidRow(
            # Map - full width on mobile
            column(
              width = 12,
              div(
                class = "row",
                div(
                  class = "col-md-8 col-sm-12",
                  box(
                    title = span("Wealth Map of Africa",
                                 style = "font-family: 'OCR A Std', monospace; font-size: 18px;"),
                    width = NULL, solidHeader = TRUE, status = "primary",
                    leafletOutput("map", height = "450px"),
                    p(style = "padding-top: 10px; font-size: 14px;", 
                      "Tap anywhere on the map to view the time-series of IWI for that location.")
                  )
                ),
                # Histogram - will position below map on mobile
                div(
                  class = "col-md-4 col-sm-12",
                  box(
                    title = span("IWI Distribution", 
                                 style = "font-family: 'OCR A Std', monospace; font-size: 16px;"),
                    width = NULL, solidHeader = TRUE, status = "info",
                    plotOutput("iwi_histogram", height = "200px"),
                    p(style = "font-size: 14px;", 
                      "Distribution of International Wealth Index values for the selected time period."),
                    strong(style = "font-size: 14px;", "Note:"),
                    span(style = "font-size: 14px;", 
                         " Areas without human settlements are excluded."),
                    div(
                      style = "margin-top: 10px;",
                      p(HTML("<a href='https://doi.org/10.24963/ijcai.2023/684' target='_blank' style='font-size: 14px;'>[Paper PDF]</a>"))
                    )
                  )
                )
              )
            )
          ),
          # Time series at clicked location
          fluidRow(
            column(
              width = 12,
              box(
                title = span("Time Series at Tapped Location",
                             style = "font-family: 'OCR A Std', monospace; font-size: 16px;"),
                width = NULL, solidHeader = TRUE, status = "warning",
                plotOutput("clicked_ts_plot", height = "250px"),
                p(style = "font-size: 14px;", 
                  "Tap on the map to see the IWI time-series (1990–2019) for that location.")
              )
            )
          )
        ),
        
        # ---------- IMPROVEMENT DATA TAB ----------
        tabItem(
          tabName = "improvementTab",
          fluidRow(
            column(
              width = 12,
              box(
                width = NULL, 
                title = span("Poverty Improvement by State",
                             style = "font-family: 'OCR A Std', monospace; font-size: 18px;"),
                status = "primary", solidHeader = TRUE,
                p(style = "font-size: 14px;", "This table shows the estimated improvement in mean IWI between 1990–1992 and 2017–2019 for each province in Africa."),
                div(
                  style = "margin: 15px 0;",
                  downloadButton("download_data", "Download CSV", 
                                 style = "width: 100%; padding: 12px; font-size: 16px;")
                ),
                # Mobile-optimized table
                div(
                  style = "overflow-x: auto;", 
                  DTOutput("improvement_table")
                )
              )
            )
          )
        ),
        
        # ---------- TRENDS OVER TIME TAB ----------
        tabItem(
          tabName = "trendTab",
          fluidRow(
            column(
              width = 12,
              box(
                width = NULL, 
                title = span("Average Wealth Index Over Time",
                             style = "font-family: 'OCR A Std', monospace; font-size: 18px;"),
                status = "success", solidHeader = TRUE,
                p(style = "font-size: 14px;", 
                  "Mean IWI across Africa over the ten time periods, showing how wealth has changed over time."),
                plotOutput("trend_plot", height = "350px")
              )
            )
          )
        )
      )
    )
  )
  
  
  # ------------------------------
  # 4. Server
  # ------------------------------
  server <- function(input, output, session) {
    
    # ReactiveVal to store the time-series of the last clicked point (across all periods).
    clicked_point_vals <- reactiveVal(NULL)
    
    # ----------------------------------
    # Reactive expression for selected raster layer
    # ----------------------------------
    selected_raster <- reactive({
      req(input$time_index)
      wealth_stack[[input$time_index]]
    })
    
    # ----------------------------------
    # Custom color palette function
    # (reactive to user-selected palette)
    # ----------------------------------
    color_pal <- reactive({
      # Switch the user selection to a palette name
      palette_choice <- switch(
        input$color_palette,
        "viridis"  = "viridis",
        "plasma"   = "plasma",
        "magma"    = "magma",
        "inferno"  = "inferno",
        "Spectral" = "Spectral"
      )
      
      # Create a single palette across *all* data (all_vals) using quantiles:
      colorBin(
        palette   = palette_choice,
        domain    = all_vals,
        bins      = q_breaks,
        na.color  = "transparent"
      )
    })
    
    color_pal_legend <- reactive({
      # Switch the user selection to a palette name
      palette_choice <- switch(
        input$color_palette,
        "viridis"  = "viridis",
        "plasma"   = "plasma",
        "magma"    = "magma",
        "inferno"  = "inferno",
        "Spectral" = "Spectral"
      )
      
      # Create a single palette across *all* data (all_vals) using quantiles:
      colorBin(
        palette   = palette_choice,
        domain    = all_vals,
        bins      = q_breaks_legend,
        na.color  = "transparent"
      )
    })
    
    
    # ----------------------------------
    # Display the currently selected time period (year range)
    # ----------------------------------
    output$current_year_range <- renderText({
      time_periods[input$time_index]
    })
    
    # ----------------------------------
    # 1. MAP OUTPUT
    # ----------------------------------
    output$map <- renderLeaflet({
      # We'll create 5 legend steps: 1, 0.75, 0.5, 0.25, 0
      legend_values <- seq(1, 0, length.out = 5)
      
      leaflet() %>%
        addProviderTiles(providers$OpenStreetMap) %>%
        setView(lng = 20, lat = 0, zoom = 3) %>%  # Center on Africa
        addLegend(
          position = "bottomright",
          pal      = color_pal_legend(),
          values   = all_vals,  # the entire distribution for the legend
          title    = "IWI",
          opacity  = 1
        )
    })
    
    # Redraw the raster when inputs change
    observeEvent(list(input$time_index, input$color_palette, input$opacity), {
      leafletProxy("map") %>%
        clearImages() %>%
        addRasterImage(
          selected_raster(),
          colors  = color_pal(),
          opacity = input$opacity,
          project = TRUE
        )
    })
    
    # ----------------------------------
    # Handle clicks on the map to show full time-series at that location
    # ----------------------------------
    observeEvent(input$map_click, {
      click <- input$map_click
      if (!is.null(click)) {
        lat <- click$lat
        lng <- click$lng
        
        # Convert clicked point to SpatialPoints
        coords <- data.frame(lng = lng, lat = lat)
        sp_pt  <- SpatialPoints(coords, proj4string = CRS("+proj=longlat +datum=WGS84 +no_defs"))
        
        # Extract values across ALL bands at the clicked location
        extracted_vals <- raster::extract(wealth_stack, sp_pt)
        # extracted_vals is a 1x10 matrix if the point is valid
        if (!is.null(extracted_vals)) {
          # Convert to numeric vector
          clicked_point_vals(as.numeric(extracted_vals))
        } else {
          # If the point is outside the raster or invalid
          clicked_point_vals(NULL)
        }
      }
    })
    
    # Plot the time-series for the clicked location
    output$clicked_ts_plot <- renderPlot({
      vals <- clicked_point_vals()
      if (is.null(vals)) {
        # No location clicked yet or invalid click
        plot.new()
        title("Click on the map to see the IWI time-series here.")
        return()
      }
      
      # If user clicked in a region with all NAs, do not plot
      if (all(is.na(vals))) {
        plot.new()
        title("No data at this location. Try another spot.")
        return()
      }
      
      df <- data.frame(Period = factor(time_periods, levels = time_periods),
                       IWI    = vals)
      
      ggplot(df, aes(x = Period, y = IWI, group = 1)) +
        geom_line(color = "darkorange", size = 1) +
        geom_point(color = "darkorange", size = 2) +
        labs(title = "Time Series of IWI at Clicked Location",
             x = "Time Period",
             y = "IWI (0 to 1)") +
        ylim(0, 1) +
        theme_minimal(base_size = 14) +
        theme(axis.text.x = element_text(angle = 45, hjust = 1))
    })
    
    # ----------------------------------
    # 2. HISTOGRAM OUTPUT (for selected time period)
    # ----------------------------------
    output$iwi_histogram <- renderPlot({
      # Extract raster values for histogram
      r_vals <- values(selected_raster())
      r_vals <- r_vals[!is.na(r_vals)]
      
      ggplot(data.frame(iwi = r_vals), aes(x = iwi)) +
        geom_histogram(binwidth = 0.02, fill = "#2c7bb6", color = "white", alpha = 0.7) +
        labs(x = "IWI (0 to 1)", y = "Frequency") +
        theme_minimal(base_size = 14)
    })
    
    # ----------------------------------
    # 3. VALUE BOXES FOR KEY STATS
    # ----------------------------------
    # Compute stats for current raster
    raster_stats <- reactive({
      r_vals <- values(selected_raster())
      r_vals <- r_vals[!is.na(r_vals)]
      list(
        highest = max(r_vals, na.rm = TRUE),
        lowest  = min(r_vals, na.rm = TRUE),
        average = mean(r_vals, na.rm = TRUE)
      )
    })
    
    # Highest IWI
    output$highest_iwi_vb <- renderValueBox({
      valueBox(
        value = round(raster_stats()$highest, 3),
        subtitle = "Highest IWI",
        icon = icon("arrow-up"),
        color = "green"
      )
    })
    
    # Lowest IWI
    output$lowest_iwi_vb <- renderValueBox({
      valueBox(
        value = round(raster_stats()$lowest, 3),
        subtitle = "Lowest IWI",
        icon = icon("arrow-down"),
        color = "red"
      )
    })
    
    # Average IWI
    output$avg_iwi_vb <- renderValueBox({
      valueBox(
        value = round(raster_stats()$average, 3),
        subtitle = "Average IWI",
        icon = icon("balance-scale"),
        color = "blue"
      )
    })
    
    # ----------------------------------
    # 4. IMPROVEMENT DATA TABLE
    # ----------------------------------
    output$improvement_table <- renderDT({
      datatable(
        improvement_data,
        filter = "top",
        options = list(
          scrollX = TRUE,
          pageLength = 20,
          autoWidth = TRUE
        )
      )
    })
    
    # Download CSV
    output$download_data <- downloadHandler(
      filename = function() {
        paste0("poverty_improvement_", Sys.Date(), ".csv")
      },
      content = function(file) {
        write.csv(improvement_data, file, row.names = FALSE)
      }
    )
    
    # ----------------------------------
    # 5. TRENDS OVER TIME (line chart of mean IWI across all Africa)
    # ----------------------------------
    output$trend_plot <- renderPlot({
      df <- data.frame(
        Period = factor(time_periods, levels = time_periods),
        MeanIWI = band_means
      )
      
      ggplot(df, aes(x = Period, y = MeanIWI, group = 1)) +
        geom_line(color = "#2c7bb6", size = 1.1) +
        geom_point(color = "#2c7bb6", size = 2) +
        labs(
          title = "Average IWI Over Time (Africa)",
          x = "Time Period",
          y = "Mean IWI"
        ) +
        ylim(0.1, 0.3) +
        theme_minimal(base_size = 14) +
        theme(axis.text.x = element_text(angle = 45, hjust = 1))
    })
  }
  
  # ------------------------------
  # 6. Run the App
  # ------------------------------
  shinyApp(ui = ui, server = server)
}