app.R

# app.R

library(shiny)
library(dplyr)
# library(lubridate)  # 不要なので削除
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
    ),
    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) {
  
  # 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
    )
  })
  
  # 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"
        )
    }
    
    # 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"
        )
    }
    
    m %>% addLayersControl(
      overlayGroups = c("sites", "guards"),
      options = layersControlOptions(collapsed = FALSE)
    )
  })
  
  # 集計テーブル
  output$summary <- renderTable({
    summary_tbl()
  })
}

shinyApp(ui, server)