{"app.R": "library(shiny)\nlibrary(leaflet)\nlibrary(dplyr)\nlibrary(bslib)\n\nsource(\"data.R\")\nsource(\"ui.R\")\nsource(\"server.R\")\n\nshinyApp(ui = ui, server = server)", "data.R": "library(dplyr)\n\n# Generate mock food truck locations\nset.seed(123)\nnyc_center <- c(lat = 40.7128, lng = -74.0060)\nnyc_bounds <- list(\n lat = c(40.4774, 40.9176),\n lng = c(-74.2591, -73.7004)\n)\n\n# Food truck data\nfood_trucks <- data.frame(\n id = 1:100,\n lat = runif(100, nyc_bounds$lat[1], nyc_bounds$lat[2]),\n lng = runif(100, nyc_bounds$lng[1], nyc_bounds$lng[2]),\n name = paste('Food Truck', 1:100),\n cuisine = sample(\n c('Mexican', 'American', 'Asian', 'Mediterranean', 'Italian'),\n 100, replace = TRUE\n ),\n rating = round(runif(100, 3, 5), 1)\n)\n\n# Generate mock pedestrian heatmap data points\nheatmap_points <- data.frame(\n lat = rnorm(1000, nyc_center['lat'], 0.1),\n lng = rnorm(1000, nyc_center['lng'], 0.1),\n intensity = runif(1000)\n)\n\n# Generate mock taxi routes\ntaxi_routes <- lapply(1:20, function(i) {\n n_points <- sample(5:15, 1)\n data.frame(\n route_id = i,\n lat = rnorm(n_points, nyc_center['lat'], 0.05),\n lng = rnorm(n_points, nyc_center['lng'], 0.05)\n )\n})\n\n# Borough boundaries (simplified mock data)\nboroughs <- list(\n Manhattan = c(lat = 40.7831, lng = -73.9712),\n Brooklyn = c(lat = 40.6782, lng = -73.9442),\n Queens = c(lat = 40.7282, lng = -73.7949),\n Bronx = c(lat = 40.8448, lng = -73.8648),\n Staten_Island = c(lat = 40.5795, lng = -74.1502)\n)\n\n# Calculate summary statistics\ncalc_summary_stats <- function(food_trucks) {\n list(\n total_trucks = nrow(food_trucks),\n avg_rating = mean(food_trucks$rating),\n cuisine_counts = table(food_trucks$cuisine)\n )\n}", "server.R": "library(magrittr)\nsource('data.R')\nlibrary(shiny)\nlibrary(leaflet)\nlibrary(dplyr)\n\nserver <- function(input, output, session) {\n # Initialize the map\n output$map <- renderLeaflet({\n leaflet() %>%\n addTiles(group = \"Street\") %>%\n addProviderTiles(providers$Esri.WorldImagery, group = \"Satellite\") %>%\n setView(lng = nyc_center['lng'], lat = nyc_center['lat'], zoom = 11) %>%\n addLayersControl(\n baseGroups = c(\"Street\", \"Satellite\"),\n options = layersControlOptions(collapsed = FALSE)\n )\n })\n \n # Update map based on inputs\n observe({\n # Clear previous layers\n leafletProxy(\"map\") %>%\n clearMarkers() %>%\n clearHeatmap() %>%\n clearGroup(\"routes\") %>%\n clearGroup(\"clusters\")\n \n # Add food trucks if selected\n if (\"trucks\" %in% input$layers) {\n leafletProxy(\"map\") %>%\n addMarkers(\n data = food_trucks,\n ~lng, ~lat,\n popup = ~paste(\n \"\", name, \"
\",\n \"Cuisine: \", cuisine, \"
\",\n \"Rating: \", rating\n ),\n clusterOptions = markerClusterOptions()\n )\n }\n \n # Add heatmap if selected\n if (\"heatmap\" %in% input$layers) {\n leafletProxy(\"map\") %>%\n addHeatmap(\n data = heatmap_points,\n lng = ~lng, lat = ~lat,\n intensity = ~intensity,\n blur = 20,\n max = input$heatmap_intensity\n )\n }\n \n # Add taxi routes if selected\n if (\"routes\" %in% input$layers) {\n for (route in taxi_routes) {\n leafletProxy(\"map\") %>%\n addPolylines(\n data = route,\n ~lng, ~lat,\n color = \"#FF4B4B\",\n weight = 2,\n opacity = 0.6,\n group = \"routes\"\n )\n }\n }\n })\n \n # Update stats panel\n output$stats_table <- renderTable({\n stats <- calc_summary_stats(food_trucks)\n data.frame(\n Metric = c(\"Total Food Trucks\", \"Average Rating\"),\n Value = c(stats$total_trucks, round(stats$avg_rating, 2))\n )\n })\n \n # Cuisine distribution plot\n output$cuisine_plot <- renderPlot({\n stats <- calc_summary_stats(food_trucks)\n barplot(\n stats$cuisine_counts,\n main = \"Cuisine Distribution\",\n las = 2,\n col = \"steelblue\"\n )\n })\n}\n", "ui.R": "library(shiny)\nlibrary(bslib)\nlibrary(leaflet)\n\nui <- page_sidebar(\n title = \"NYC Interactive Map\",\n sidebar = sidebar(\n # Time controls\n sliderInput(\n \"time_range\",\n \"Time Range:\",\n min = 0,\n max = 24,\n value = c(9, 17),\n step = 1\n ),\n \n # Borough filters\n checkboxGroupInput(\n \"boroughs\",\n \"Boroughs:\",\n choices = c(\"Manhattan\", \"Brooklyn\", \"Queens\", \"Bronx\", \"Staten Island\"),\n selected = \"Manhattan\"\n ),\n \n # Layer toggles\n checkboxGroupInput(\n \"layers\",\n \"Map Layers:\",\n choices = c(\n \"Food Trucks\" = \"trucks\",\n \"Pedestrian Heatmap\" = \"heatmap\",\n \"Taxi Routes\" = \"routes\",\n \"Taxi Clusters\" = \"clusters\"\n ),\n selected = c(\"trucks\", \"heatmap\")\n ),\n \n # Map style selector\n radioButtons(\n \"map_style\",\n \"Map Style:\",\n choices = c(\n \"Street\" = \"street\",\n \"Satellite\" = \"satellite\"\n ),\n selected = \"street\"\n ),\n \n # Heatmap settings\n sliderInput(\n \"heatmap_intensity\",\n \"Heatmap Intensity:\",\n min = 0,\n max = 1,\n value = 0.5,\n step = 0.1\n ),\n \n # Cluster settings\n sliderInput(\n \"cluster_radius\",\n \"Cluster Radius:\",\n min = 10,\n max = 100,\n value = 50\n )\n ),\n \n # Main content\n layout_column_wrap(\n width = NULL,\n heights_equal = \"row\",\n # Map\n card(\n full_screen = TRUE,\n card_header(\"Interactive NYC Map\"),\n leafletOutput(\"map\", height = \"70vh\")\n ),\n # Stats panel\n card(\n card_header(\"Statistics\"),\n tableOutput(\"stats_table\"),\n plotOutput(\"cuisine_plot\", height = \"200px\")\n )\n )\n)", "install.R": "install.packages('bslib')\ninstall.packages('dplyr')\ninstall.packages('leaflet')\ninstall.packages('magrittr')\ninstall.packages('shiny')", "startApp.R": "\nlibrary(shiny)\noptions(shiny.host = '0.0.0.0')\noptions(shiny.port = 80)\nrunApp('app.R')\n"}