############################################
##  Normality test - ui  
############################################

## 1. 翻译标签
nt_method <- c("shapiro", "ks", "ad")   # 先给 3 个常用方法
names(nt_method) <- c(i18n$t("Shapiro-Wilk"),
                      i18n$t("Kolmogorov-Smirnov"),
                      i18n$t("Anderson-Darling"))

nt_plots <- c("qq", "hist", "pp", "density")
names(nt_plots) <- c(i18n$t("Q-Q plot"),
                     i18n$t("Histogram"),
                     i18n$t("P-P plot"),
                     i18n$t("Density"))

## 2. 函数形参
nt_args <- as.list(formals(normality_test))

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

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

## 5. 主 UI
output$ui_normality_test <- renderUI({
  req(input$dataset)
  tagList(
    wellPanel(
      conditionalPanel(
        condition = "input.tabs_normality_test == 'Summary'",
        uiOutput("ui_nt_var"),
        selectInput(
          inputId = "nt_method", label = i18n$t("Test method:"),
          choices = nt_method,
          selected = state_single("nt_method", nt_method, "shapiro"),
          multiple = FALSE
        ),
        sliderInput(
          "nt_conf_lev", i18n$t("Confidence level:"),
          min = 0.85, max = 0.99,
          value = state_init("nt_conf_lev", 0.95), step = 0.01
        )
      ),
      conditionalPanel(
        condition = "input.tabs_normality_test == 'Plot'",
        selectizeInput(
          inputId = "nt_plots", label = i18n$t("Select plots:"),
          choices = nt_plots,
          selected = state_multiple("nt_plots", nt_plots, "qq"),
          multiple = TRUE,
          options = list(placeholder = i18n$t("Select plots"),
                         plugins = list("remove_button", "drag_drop"))
        )
      )
    ),
    help_and_report(
      modal_title = i18n$t("Normality test"),
      fun_name = "normality_test",
      help_file = inclMD(file.path(getOption("radiant.path.basics"),
                                   "app/tools/help/normality_test.md"))
    )
  )
})

## 6. 画图尺寸（直接抄）
nt_plot <- reactive({
  list(plot_width = 650,
       plot_height = 400 * max(length(input$nt_plots), 1))
})
nt_plot_width  <- function() nt_plot()$plot_width
nt_plot_height <- function() nt_plot()$plot_height


## 7. 输出面板
output$normality_test <- renderUI({
  register_print_output("summary_normality_test", ".summary_normality_test")
  register_plot_output("plot_normality_test", ".plot_normality_test",
                       height_fun = "nt_plot_height")
  
  nt_output_panels <- tabsetPanel(
    id = "tabs_normality_test",
    tabPanel(title = i18n$t("Summary"),
             value = "Summary",
             verbatimTextOutput("summary_normality_test")),
    tabPanel(title = i18n$t("Plot"),
             value = "Plot",
             download_link("dlp_normality_test"),
             plotOutput("plot_normality_test", height = "100%"))
  )
  
  stat_tab_panel(
    menu = i18n$t("Basics > Normality"),
    tool = i18n$t("Normality test"),
    tool_ui = "ui_normality_test",
    output_panels = nt_output_panels
  )
})

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

## 9. 计算核心
.normality_test <- reactive({
  nti <- nt_inputs()
  nti$envir <- r_data
  do.call(normality_test, nti)
})

.summary_normality_test <- reactive({
  if (nt_available() != "available") return(nt_available())
  summary(.normality_test())
})

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

## 10. Report
normality_test_report <- function() {
  if (is.empty(input$nt_var)) return(invisible())
  figs <- length(input$nt_plots) > 0
  outputs <- if (figs) c("summary", "plot") else "summary"
  inp_out <- if (figs) list("", list(plots = input$nt_plots, custom = FALSE)) else list("", "")
  update_report(inp_main = clean_args(nt_inputs(), nt_args),
                fun_name = "normality_test",
                inp_out  = inp_out,
                outputs  = outputs,
                figs     = figs,
                fig.width = nt_plot_width(),
                fig.height = nt_plot_height())
}

## 11. 下载 & 截图
download_handler(
  id = "dlp_normality_test",
  fun = download_handler_plot,
  fn = function() paste0(input$dataset, "_normality_test"),
  type = "png",
  caption = i18n$t("Save normality test plot"),
  plot = .plot_normality_test,
  width = nt_plot_width,
  height = nt_plot_height
)

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

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

observeEvent(input$modal_normality_test_screenshot, {
  normality_test_report()
  removeModal()
})