## alternative hypothesis options
gd_check <- c("observed", "expected", "chi_sq", "dev_std")
names(gd_check) <- c(
  i18n$t("Observed"),
  i18n$t("Expected"),
  i18n$t("Chi-squared"),
  i18n$t("Deviation std.")
)

## list of function arguments
gd_args <- as.list(formals(goodness))

## list of function inputs selected by user
gd_inputs <- reactive({
  ## loop needed because reactive values don't allow single bracket indexing
  gd_args$data_filter <- if (input$show_filter) input$data_filter else ""
  gd_args$dataset <- input$dataset
  for (i in r_drop(names(gd_args))) {
    gd_args[[i]] <- input[[paste0("gd_", i)]]
  }
  gd_args
})

###############################
# Goodness of fit test
###############################
output$ui_gd_var <- renderUI({
  vars <- c("None" = "", groupable_vars())
  selectInput(
    "gd_var", i18n$t("Select a categorical variable:"),
    choices = vars,
    selected = state_single("gd_var", vars),
    multiple = FALSE
  )
})

output$ui_gd_p <- renderUI({
  req(input$gd_var)
  returnTextInput(
    "gd_p", i18n$t("Probabilities:"),
    value = state_init("gd_p", ""),
    placeholder = i18n$t("Enter probabilities (e.g., 1/2 1/2)")
  )
})

output$ui_goodness <- renderUI({
  req(input$dataset)
  tagList(
    wellPanel(
      conditionalPanel(
        condition = "input.tabs_goodness == 'Summary'",
        uiOutput("ui_gd_var"),
        uiOutput("ui_gd_p"),
        br()
      ),
      checkboxGroupInput(
        "gd_check", NULL,
        choices = gd_check,
        selected = state_group("gd_check"),
        inline = FALSE
      )
    ),
    help_and_report(
      modal_title = i18n$t("Goodness of fit"),
      fun_name = "goodness",
      help_file = inclMD(file.path(getOption("radiant.path.basics"), "app/tools/help/goodness.md"))
    )
  )
})

gd_plot <- reactive({
  list(plot_width = 650, plot_height = 400 * max(length(input$gd_check), 1))
})

gd_plot_width <- function() {
  gd_plot() %>%
    (function(x) if (is.list(x)) x$plot_width else 650)
}

gd_plot_height <- function() {
  gd_plot() %>%
    (function(x) if (is.list(x)) x$plot_height else 400)
}

## output is called from the main radiant ui.R
output$goodness <- renderUI({
  register_print_output("summary_goodness", ".summary_goodness")
  register_plot_output(
    "plot_goodness", ".plot_goodness",
    height_fun = "gd_plot_height",
    width_fun = "gd_plot_width"
  )

  ## two separate tabs
  gd_output_panels <- tabsetPanel(
    id = "tabs_goodness",
    tabPanel(i18n$t("Summary"), value = "Summary", verbatimTextOutput("summary_goodness")),
    tabPanel(
      i18n$t("Plot"), value = "Plot",
      download_link("dlp_goodness"),
      plotOutput("plot_goodness", width = "100%", height = "100%")
    )
  )

  stat_tab_panel(
    menu = i18n$t("Basics > Tables"),
    tool = i18n$t("Goodness of fit"),
    tool_ui = "ui_goodness",
    output_panels = gd_output_panels
  )
})

gd_available <- reactive({
  if (not_available(input$gd_var)) {
    i18n$t("This analysis requires a categorical variables with two or more levels.\nIf such a variable type is not available please select another dataset.\n\n") %>% suggest_data("newspaper")
  } else {
    "available"
  }
})

.goodness <- reactive({
  gdi <- gd_inputs()
  gdi$envir <- r_data
  do.call(goodness, gdi)
})

.summary_goodness <- reactive({
  if (gd_available() != "available") {
    return(gd_available())
  }
  summary(.goodness(), check = input$gd_check)
})

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

goodness_report <- function() {
  if (is.empty(input$gd_var)) {
    return(invisible())
  }
  inp_out <- list("", "")
  if (length(input$gd_check) > 0) {
    outputs <- c("summary", "plot")
    inp_out[[1]] <- list(check = input$gd_check)
    inp_out[[2]] <- list(check = input$gd_check, custom = FALSE)
    figs <- TRUE
  } else {
    outputs <- "summary"
    figs <- FALSE
  }

  gdi <- gd_inputs()
  gdi$p <- radiant.data::make_vec(gdi$p)

  update_report(
    inp_main = clean_args(gdi, gd_args),
    inp_out = inp_out,
    fun_name = "goodness",
    outputs = outputs,
    figs = figs,
    fig.width = gd_plot_width(),
    fig.height = gd_plot_height()
  )
}

download_handler(
  id = "dlp_goodness",
  fun = download_handler_plot,
  fn = function() paste0(input$dataset, "_goodness"),
  type = "png",
  caption = i18n$t("Save goodness of fit plot"),
  plot = .plot_goodness,
  width = gd_plot_width,
  height = gd_plot_height
)

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

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

observeEvent(input$modal_goodness_screenshot, {
  goodness_report()
  removeModal() ## remove shiny modal after save
})