Update app.R

app.R

@@ -1,58 +1,176 @@
+# app.R
+
 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(lubridate)
+library(leaflet)
+
+set.seed(123)
+
+# =========================
+# 1. ダミーデータ作成
+# =========================
+
+# 工事現場（北海道の適当な範囲でランダム）
+sites <- tibble::tibble(
+  site_id = 1:5,
+  site_name = paste0("工事現場", 1:5),
+  city = c("札幌市", "札幌市", "旭川市", "函館市", "帯広市"),
+  lat = runif(5, 42.0, 44.5),   # 北海道っぽい緯度
+  lng = runif(5, 141.0, 143.5), # 北海道っぽい経度
+  start = as.Date("2025-12-01"),
+  end   = as.Date("2025-12-31"),
+  required_guards = c(3, 4, 2, 5, 3)
+)
+
+cities <- sites$city
+
+# 警備員（住所は市レベルで、対応可能期間は12月中でバラバラ）
+guards <- tibble::tibble(
+  guard_id = 1:20,
+  guard_name = paste0("警備員", 1:20),
+  city = sample(cities, 20, replace = TRUE),
+  lat = runif(20, 42.0, 44.5),
+  lng = runif(20, 141.0, 143.5),
+  available_from = sample(seq(as.Date("2025-12-01"), as.Date("2025-12-15"), by = "day"),
+                          20, replace = TRUE),
+  available_to   = sample(seq(as.Date("2025-12-16"), as.Date("2025-12-31"), by = "day"),
+                          20, replace = TRUE)
+) %>%
+  # from <= to になるように補正
+  mutate(
+    tmp_min = pmin(available_from, available_to),
+    tmp_max = pmax(available_from, available_to),
+    available_from = tmp_min,
+    available_to   = tmp_max
+  ) %>%
+  select(-tmp_min, -tmp_max)
+
+# =========================
+# 2. UI
+# =========================
+
+ui <- fluidPage(
+  titlePanel("北海道・工事現場 × 警備員マッチング（ダミーデータ）"),
+  sidebarLayout(
+    sidebarPanel(
+      dateInput(
+        "selected_date",
+        "日付を選択",
+        value = as.Date("2025-12-01"),
+        min   = as.Date("2025-12-01"),
+        max   = as.Date("2025-12-31")
+      ),
+      checkboxInput("show_guards", "警備員の位置も地図に表示", TRUE),
+      width = 3
     ),
-    hr(), # Add a horizontal rule
-    checkboxInput("by_species", "Show species", TRUE),
-    checkboxInput("show_margins", "Show marginal plots", TRUE),
-    checkboxInput("smooth", "Add smoother"),
-  ),
-  plotOutput("scatter")
+    mainPanel(
+      leafletOutput("map", height = 500),
+      br(),
+      h4("工事現場別マッチング状況（選択日ベース）"),
+      tableOutput("summary"),
+      width = 9
+    )
+  )
 )
 
+# =========================
+# 3. Server
+# =========================
+
 server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
+  
+  # 選択日ごとのデータ
+  daily_data <- reactive({
+    d <- input$selected_date
+    
+    # その日に稼働中の現場（期間内）
+    active_sites <- sites %>%
+      filter(start <= d, end >= d)
+    
+    # その日に勤務可能な警備員
+    available_guards <- guards %>%
+      filter(available_from <= d, available_to >= d)
+    
+    list(
+      date = d,
+      active_sites = active_sites,
+      available_guards = available_guards
+    )
   })
-
-  output$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()
+  
+  # マッチング集計（ここでは「同じ市にいる警備員数」で集計）
+  summary_tbl <- reactive({
+    dd <- daily_data()
+    active_sites <- dd$active_sites
+    available_guards <- dd$available_guards
+    
+    guards_by_city <- available_guards %>%
+      count(city, name = "available_guards")
+    
+    active_sites %>%
+      left_join(guards_by_city, by = "city") %>%
+      mutate(
+        available_guards = ifelse(is.na(available_guards), 0L, available_guards),
+        shortage = pmax(required_guards - available_guards, 0L)
+      ) %>%
+      select(
+        現場ID = site_id,
+        現場名 = site_name,
+        市区町村 = city,
+        必要人数 = required_guards,
+        "対応可能人数(同一市内)" = available_guards,
+        "不足人数" = shortage
+      )
+  })
+  
+  # 地図描画
+  output$map <- renderLeaflet({
+    dd <- daily_data()
+    
+    # ベースマップ（北海道あたりを初期表示）
+    m <- leaflet() %>%
+      addTiles() %>%
+      setView(lng = 142.0, lat = 43.0, zoom = 6)
+    
+    # 工事現場
+    if (nrow(dd$active_sites) > 0) {
+      m <- m %>%
+        addCircleMarkers(
+          data = dd$active_sites,
+          ~lng, ~lat,
+          radius = 8,
+          color = "blue",
+          fillOpacity = 0.8,
+          label = ~paste0(site_name, "（必要人数: ", required_guards, "人）"),
+          group = "sites"
         )
-
-      if (input$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$by_species
+    }
+    
+    # 警備員
+    if (input$show_guards && nrow(dd$available_guards) > 0) {
+      m <- m %>%
+        addCircleMarkers(
+          data = dd$available_guards,
+          ~lng, ~lat,
+          radius = 5,
+          color = "red",
+          fillOpacity = 0.7,
+          label = ~paste0(guard_name, "（", city, "在住）"),
+          group = "guards"
         )
-      }
-
-      p
-    },
-    res = 100
-  )
+    }
+    
+    m %>% addLayersControl(
+      overlayGroups = c("sites", "guards"),
+      options = layersControlOptions(collapsed = FALSE)
+    )
+  })
+  
+  # 集計テーブル
+  output$summary <- renderTable({
+    summary_tbl()
+  })
 }
 
-shinyApp(ui, server)
+shinyApp(ui, server)