############################################
##  Homogeneity of variance test - ui
############################################

## 1. 翻译标签
hv_method <- c("levene", "bartlett", "fligner")
names(hv_method) <- c(i18n$t("Levene"),
                      i18n$t("Bartlett"),
                      i18n$t("Fligner"))

hv_plots <- c("hist", "density", "boxplot")
names(hv_plots) <- c(i18n$t("Histogram"),
                     i18n$t("Density"),
                     i18n$t("Boxplot"))

## 2. 函数形参
hv_args <- as.list(formals(homo_variance_test))

## 3. 收集输入
hv_inputs <- reactive({
  hv_args$data_filter <- if (input$show_filter) input$data_filter else ""
  hv_args$dataset     <- input$dataset
  for (i in r_drop(names(hv_args))) {
    hv_args[[i]] <- input[[paste0("hv_", i)]]
  }
  hv_args
})

## 4. 变量选择（numeric + grouping）
output$ui_hv_var <- renderUI({
  isNum <- .get_class() %in% c("integer", "numeric", "ts")
  vars <- c("None" = "", varnames()[isNum])
  selectInput(
    inputId = "hv_var", label = i18n$t("Variable (select one):"),
    choices = vars, selected = state_single("hv_var", vars), multiple = FALSE
  )
})

output$ui_hv_group <- renderUI({
  vars <- groupable_vars()
  selectInput(
    inputId = "hv_group", label = i18n$t("Grouping variable:"),
    choices = vars, selected = state_single("hv_group", vars), multiple = FALSE
  )
})

## 5. 主 UI
output$ui_homo_variance_test <- renderUI({
  req(input$dataset)
  tagList(
    wellPanel(
      conditionalPanel(
        condition = "input.tabs_homo_variance_test == 'Summary'",
        uiOutput("ui_hv_var"),
        uiOutput("ui_hv_group"),
        selectInput(
          inputId = "hv_method", label = i18n$t("Test method:"),
          choices = hv_method,
          selected = state_single("hv_method", hv_method, "levene"),
          multiple = FALSE
        ),
        sliderInput(
          "hv_conf_lev", i18n$t("Confidence level:"),
          min = 0.85, max = 0.99,
          value = state_init("hv_conf_lev", 0.95), step = 0.01
        )
      ),
      conditionalPanel(
        condition = "input.tabs_homo_variance_test == 'Plot'",
        selectizeInput(
          inputId = "hv_plots", label = i18n$t("Select plots:"),
          choices = hv_plots,
          selected = state_multiple("hv_plots", hv_plots, "boxplot"),
          multiple = TRUE,
          options = list(placeholder = i18n$t("Select plots"),
                         plugins = list("remove_button", "drag_drop"))
        )
      )
    ),
    help_and_report(
      modal_title = i18n$t("Homogeneity of variance test"),
      fun_name = "homo_variance_test",
      help_file = inclMD(file.path(getOption("radiant.path.basics"),
                                   "app/tools/help/homo_variance_test.md"))
    )
  )
})

## 6. 画图尺寸
hv_plot <- reactive({
  list(plot_width = 650,
       plot_height = 400 * max(length(input$hv_plots), 1))
})
hv_plot_width  <- function() hv_plot()$plot_width
hv_plot_height <- function() hv_plot()$plot_height

## 7. 输出面板
output$homo_variance_test <- renderUI({
  register_print_output("summary_homo_variance_test", ".summary_homo_variance_test")
  register_plot_output("plot_homo_variance_test", ".plot_homo_variance_test",
                       height_fun = "hv_plot_height")
  
  hv_output_panels <- tabsetPanel(
    id = "tabs_homo_variance_test",
    tabPanel(title = i18n$t("Summary"),
             value = "Summary",
             verbatimTextOutput("summary_homo_variance_test")),
    tabPanel(title = i18n$t("Plot"),
             value = "Plot",
             download_link("dlp_homo_variance_test"),
             plotOutput("plot_homo_variance_test", height = "100%"))
  )
  
  stat_tab_panel(
    menu = i18n$t("Basics > Homogeneity"),
    tool = i18n$t("Homogeneity of variance test"),
    tool_ui = "ui_homo_variance_test",
    output_panels = hv_output_panels
  )
})

## 8. 可用性检查
hv_available <- reactive({
  if (not_available(input$hv_var))
    return(i18n$t("This analysis requires a numeric variable. If none are\navailable please select another dataset.") %>% suggest_data("demand_uk"))
  if (not_available(input$hv_group))
    return(i18n$t("Please select a grouping variable."))
  "available"
})

## 9. 计算核心
.homo_variance_test <- reactive({
  hvi <- hv_inputs()
  hvi$envir <- r_data
  do.call(homo_variance_test, hvi)
})

.summary_homo_variance_test <- reactive({
  if (hv_available() != "available") return(hv_available())
  summary(.homo_variance_test())
})

.plot_homo_variance_test <- reactive({
  if (hv_available() != "available") return(hv_available())
  validate(need(input$hv_plots, i18n$t("Nothing to plot. Please select a plot type")))
  withProgress(message = i18n$t("Generating plots"), value = 1,
               plot(.homo_variance_test(), plots = input$hv_plots, shiny = TRUE))
})

## 10. Report
homo_variance_test_report <- function() {
  if (is.empty(input$hv_var)) return(invisible())
  figs <- length(input$hv_plots) > 0
  outputs <- if (figs) c("summary", "plot") else "summary"
  inp_out <- if (figs) list("", list(plots = input$hv_plots, custom = FALSE)) else list("", "")
  update_report(inp_main = clean_args(hv_inputs(), hv_args),
                fun_name = "homo_variance_test",
                inp_out  = inp_out,
                outputs  = outputs,
                figs     = figs,
                fig.width = hv_plot_width(),
                fig.height = hv_plot_height())
}

## 11. 下载 & 截图
download_handler(
  id = "dlp_homo_variance_test",
  fun = download_handler_plot,
  fn = function() paste0(input$dataset, "_homo_variance_test"),
  type = "png",
  caption = i18n$t("Save homogeneity of variance plot"),
  plot = .plot_homo_variance_test,
  width = hv_plot_width,
  height = hv_plot_height
)

observeEvent(input$homo_variance_test_report, {
  r_info[["latest_screenshot"]] <- NULL
  homo_variance_test_report()
})

observeEvent(input$homo_variance_test_screenshot, {
  r_info[["latest_screenshot"]] <- NULL
  radiant_screenshot_modal("modal_homo_variance_test_screenshot")
})

observeEvent(input$modal_homo_variance_test_screenshot, {
  homo_variance_test_report()
  removeModal()
})