# quickgen_metrics_ui.R
library(shinyjs)
library(shinyAce)

# 新增：统计结果文本格式化函数
format_stat_text <- function(result, dataset_name) {
  # 1. 处理“无法计算”的情况
  if (is.character(result) && grepl("无法计算", result)) {
    return(result)
  }
  
  # 2. 单样本t检验（htest类）
  if (inherits(result, "htest") && grepl("One Sample t-test", result$method)) {
    # 提取关键指标
    var_name <- gsub("^x = df\\$|^df\\$", "", as.character(result$data.name))
    mean_val <- round(mean(result$data, na.rm = TRUE), 3)
    n_val <- length(na.omit(result$data))
    n_missing <- sum(is.na(result$data))
    sd_val <- round(sd(result$data, na.rm = TRUE), 3)
    se_val <- round(result$stderr, 3)
    me_val <- round(se_val * qt(0.975, df = result$parameter), 3)  # 边际误差
    diff_val <- round(result$estimate, 3)
    t_val <- round(result$statistic, 3)
    p_val <- if (result$p.value < 0.001) "< .001" else round(result$p.value, 4)
    df_val <- result$parameter
    ci_lower <- round(result$conf.int[1], 3)
    ci_upper <- round(result$conf.int[2], 3)
    conf_level <- round(attr(result$conf.int, "conf.level") * 100, 1)
    # 显著性标记
    signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
    
    # 组织文本（完全匹配示例格式）
    text <- sprintf(paste0(
      "Single mean test\n",
      "Data      : %s \n",
      "Variable  : %s \n",
      "Confidence: %.1f%% \n",
      "Null hyp. : the mean of %s = %.1f \n",
      "Alt. hyp. : the mean of %s is not equal to %.1f \n",
      "   mean     n n_missing     sd    se    me\n",
      " %6.3f %5s         %d %6.3f %5.3f %5.3f\n",
      "   diff    se t.value p.value   df   2.5%%  97.5%%    \n",
      " %6.3f %5.3f %6.3f %8s %5.0f %6.3f %6.3f %s\n",
      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
    ),
    dataset_name, var_name, conf_level, var_name, result$null.value,
    var_name, result$null.value, mean_val, format(n_val, big.mark = ","),
    n_missing, sd_val, se_val, me_val, diff_val, se_val, t_val, p_val,
    df_val, ci_lower, ci_upper, signif
    )
    return(text)
  }
  
  # 3. 独立样本t检验（htest类）
  if (inherits(result, "htest") && grepl("Welch Two Sample t-test|Two Sample t-test", result$method)) {
    # 提取分组变量和数值变量
    data_parts <- strsplit(result$data.name, " ~ ")[[1]]
    var_name <- data_parts[1]
    group_var <- data_parts[2]
    group_vals <- levels(factor(df[[group_var]]))
    # 分组统计
    group1_data <- df[[var_name]][df[[group_var]] == group_vals[1]]
    group2_data <- df[[var_name]][df[[group_var]] == group_vals[2]]
    mean1 <- round(mean(group1_data, na.rm = TRUE), 3)
    mean2 <- round(mean(group2_data, na.rm = TRUE), 3)
    n1 <- length(na.omit(group1_data))
    n2 <- length(na.omit(group2_data))
    n_missing1 <- sum(is.na(group1_data))
    n_missing2 <- sum(is.na(group2_data))
    sd1 <- round(sd(group1_data, na.rm = TRUE), 3)
    sd2 <- round(sd(group2_data, na.rm = TRUE), 3)
    se1 <- round(sd1 / sqrt(n1), 3)
    se2 <- round(sd2 / sqrt(n2), 3)
    me1 <- round(se1 * qt(0.975, df = n1 - 1), 3)
    me2 <- round(se2 * qt(0.975, df = n2 - 1), 3)
    # 检验结果
    diff_val <- round(result$estimate[1] - result$estimate[2], 3)
    t_val <- round(result$statistic, 3)
    p_val <- if (result$p.value < 0.001) "< .001" else round(result$p.value, 4)
    df_val <- round(result$parameter, 0)
    ci_lower <- round(result$conf.int[1], 3)
    ci_upper <- round(result$conf.int[2], 3)
    conf_level <- round(attr(result$conf.int, "conf.level") * 100, 1)
    signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
    
    # 组织文本
    text <- sprintf(paste0(
      "Pairwise mean comparisons (t-test)\n",
      "Data      : %s \n",
      "Variables : %s, %s \n",
      "Samples   : independent \n",
      "Confidence: %.1f%% \n",
      "Adjustment: None \n",
      "           mean     n n_missing     sd    se    me\n",
      " %6s %6.3f %5s         %d %6.3f %5.3f %5.3f\n",
      " %6s %6.3f %5s         %d %6.3f %5.3f %5.3f\n",
      " Null hyp.               Alt. hyp.                  diff  p.value    \n",
      " %s = %s   %s not equal to %s   %6.3f %8s  %s\n",
      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
    ),
    dataset_name, group_var, var_name, conf_level,
    group_vals[1], mean1, format(n1, big.mark = ","), n_missing1, sd1, se1, me1,
    group_vals[2], mean2, format(n2, big.mark = ","), n_missing2, sd2, se2, me2,
    group_vals[1], group_vals[2], group_vals[1], group_vals[2], diff_val, p_val, signif
    )
    return(text)
  }
  
  # 4. 线性回归（lm类）
  if (inherits(result, "lm")) {
    # 提取模型信息
    model_formula <- as.character(result$call$formula)
    var_dep <- model_formula[2]
    vars_indep <- gsub("^ ~ ", "", model_formula[1])
    # 系数表
    coef_sum <- summary(result)$coefficients
    coef_text <- "            Estimate Std.Error t.value p.value    Signif.\n"
    for (i in 1:nrow(coef_sum)) {
      term <- rownames(coef_sum)[i]
      est <- round(coef_sum[i, 1], 4)
      se <- round(coef_sum[i, 2], 4)
      t_val <- round(coef_sum[i, 3], 3)
      p_val <- if (coef_sum[i, 4] < 0.001) "< .001" else round(coef_sum[i, 4], 4)
      signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
      coef_text <- paste0(coef_text, sprintf(" %12s %8.4f %8.4f %6.3f %8s  %3s\n", term, est, se, t_val, p_val, signif))
    }
    # 模型拟合度
    r2 <- round(summary(result)$r.squared, 4)
    r2_adj <- round(summary(result)$adj.r.squared, 4)
    n_val <- nrow(result$model)
    n_missing <- nrow(df) - n_val
    
    # 组织文本
    text <- sprintf(paste0(
      "Linear Regression Model\n",
      "Data      : %s \n",
      "Formula   : %s ~ %s \n",
      "Dependent : %s \n",
      "Independent: %s \n",
      "Sample    : n = %s, n_missing = %d \n",
      "Fit       : R² = %.4f, Adjusted R² = %.4f \n",
      "%s",
      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
    ),
    dataset_name, var_dep, vars_indep, var_dep, vars_indep,
    format(n_val, big.mark = ","), n_missing, r2, r2_adj, coef_text
    )
    return(text)
  }
  
  # 5. 其他统计方法（卡方检验、方差分析等，按示例风格扩展）
  if (inherits(result, "htest") && grepl("Chi-squared test", result$method)) {
    # 卡方检验文本格式化（类似逻辑，提取列联表、卡方值、p值等）
    data_parts <- strsplit(result$data.name, " ~ ")[[1]]
    var1 <- data_parts[1]
    var2 <- data_parts[2]
    contingency <- table(df[[var1]], df[[var2]], useNA = "no")
    chi_val <- round(result$statistic, 3)
    df_val <- result$parameter
    p_val <- if (result$p.value < 0.001) "< .001" else round(result$p.value, 4)
    signif <- if (p_val == "< .001") "***" else if (p_val <= 0.001) "***" else if (p_val <= 0.01) "**" else if (p_val <= 0.05) "*" else if (p_val <= 0.1) "." else " "
    
    text <- sprintf(paste0(
      "Chi-squared Test of Independence\n",
      "Data      : %s \n",
      "Variables : %s (row), %s (column) \n",
      "Contingency Table:\n%s\n",
      "Test Statistic: Chi-squared = %.3f, df = %.0f, p-value = %s %s\n",
      "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
    ),
    dataset_name, var1, var2, capture.output(print(contingency)),
    chi_val, df_val, p_val, signif
    )
    return(text)
  }
  
  # 6. 直接输出原始结果
  return(capture.output(print(result)))
}

## ==================== 右下角浮框 ====================
ui_metrics_progress <- tags$div(
  id = "metrics_progress_box",
  style = "display:none;
           position:fixed;
           bottom:15px; right:15px;
           width:220px; z-index:9999;
           background:#f5f5f5; color:#333;
           border:1px solid #337ab7; border-radius:4px;
           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
  tags$strong(i18n$t("AI calculating...")),
  tags$div(class = "progress",
           tags$div(class = "progress-bar progress-bar-striped active",
                    style = "width:100%"))
)
## ======== 警告弹窗========
ui_metrics_warn <- tags$div(
  id = "metrics_warn_box",
  style = "display:none;
           position:fixed;
           bottom:15px; right:15px;
           width:220px; z-index:9999;
           background:#fff3cd; color:#856404;
           border:1px solid #ffeaa7; border-radius:4px;
           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
  tags$strong(i18n$t("Warning:Please enter a request related to scientific research statistical calculation."))
)
## ==================== 统一入口 ====================
output$quickgen_metrics <- renderUI({
  stat_tab_panel(
    menu      = i18n$t("Oneclick generation > AI assistance"),
    tool      = i18n$t("AI generates descriptive statistics(metrics)"),
    tool_ui   = "metrics_main_ui",
    output_panels = tabPanel(
      title = i18n$t("Metrics Assistant"),
      value = "metrics_panel",
      uiOutput("metrics_result_area")
    )
  )
})
## ==================== 右侧 Metrics 面板 ====================
output$metrics_main_ui <- renderUI({
  tagList(
    useShinyjs(),
    ui_metrics_progress,
    ui_metrics_warn,
    wellPanel(
      i18n$t("Describe your analysis request:"),
      returnTextAreaInput("metrics_prompt",
                          label   = NULL,
                          placeholder = i18n$t("e. g. 1. Single mean test for age (null mean=35) in insurance; 2. Chi-squared test between sex and smoker; 3. Linear regression of charges on bmi+age"),
                          rows    = 4,
                          value   = state_init("metrics_prompt", "")),
      fluidRow(
        column(6, uiOutput("ui_metrics_submit")),
        column(6, uiOutput("metrics_loading"))
      )
    ),
    
    wellPanel(
      i18n$t("Generated R code"),
      uiOutput("metrics_r_code_block"),
      fluidRow(
        column(6, actionButton("metrics_run_code", i18n$t("Run code"), icon = icon("play"), class = "btn-success")),
        column(6, actionButton("metrics_edit_code", i18n$t("Edit code"), icon = icon("edit"), class = "btn-default"))
      )
    ),
    
    help_and_report(
      modal_title = i18n$t("AI generates descriptive statistics(metrics)"),
      fun_name    = "quickgen_metrics",
      help_file   = inclMD(file.path(getOption("radiant.path.quickgen"), "app/tools/help/quickgen_metrics.md")),
      lic = "by-sa"
    )
  )
})
## ==================== 控件渲染 ====================
output$ui_metrics_submit <- renderUI({
  req(input$dataset)
  actionButton("metrics_submit", i18n$t("Send"), icon = icon("magic"), class = "btn-primary")
})
output$metrics_loading <- renderUI({
  if (isTRUE(r_values$metrics_loading))
    tags$div(class = "progress",
             tags$div(class = "progress-bar progress-bar-striped active",
                      style = "width:100%",
                      i18n$t("Calling metrics calculation model...")))
})
## ==================== reactiveValues ====================
r_values <- reactiveValues(
  metrics_r_code      = "",
  metrics_result_type = "text",  # 仅保留text/plot/error
  metrics_result_ready = FALSE,
  metrics_loading     = FALSE
)
## ==================== 生成代码 ====================
observeEvent(input$metrics_submit, {
  if (is.empty(input$metrics_prompt))
    return(showNotification(i18n$t("Please enter a statistical calculation request"), type = "error"))
  
  r_values$metrics_loading <- TRUE
  shinyjs::show("metrics_progress_box")          # 显示右下角进度框
  on.exit({
    r_values$metrics_loading <- FALSE
    shinyjs::hide("metrics_progress_box")        # 无论成功失败都隐藏
  })
  
  res <- try(do.call(metrics_generate,
                     list(prompt  = input$metrics_prompt,
                          dataset = input$dataset,
                          envir   = r_data)),
             silent = TRUE)
  if (inherits(res, "try-error")) {
    showNotification(paste(i18n$t("Metrics API error:"), res), type = "error")
    return()
  }
  
  r_values$metrics_r_code      <- res$r_code
  r_values$metrics_result_type <- res$type
  r_values$metrics_result_ready <- FALSE
  r_values$auto_run       <- res$auto_run
  
  if (res$type == "empty") {
    shinyjs::show("metrics_warn_box")
    shinyjs::delay(3000, shinyjs::hide("metrics_warn_box"))
    return()
  }
  
  if (isTRUE(r_values$auto_run))
    shinyjs::click("metrics_run_code")
})
## ==================== 显示 R 代码 ====================
output$metrics_r_code_block <- renderUI({
  codes <- r_values$metrics_r_code
  tags$pre(codes, style = "background:#f5f5f5; padding:10px; border-radius:4px;
                           font-family:monospace; white-space:pre-wrap; min-height:100px;")
})
## ==================== 运行代码 ====================
observeEvent(input$metrics_run_code, {
  shinyjs::hide("metrics_progress_box")   
  if (is.empty(r_values$metrics_r_code)) return()
  
  if (trimws(r_values$metrics_r_code) == "" || identical(r_values$metrics_result_type, "empty")) {
    shinyjs::show("metrics_warn_box")
    shinyjs::delay(3000, shinyjs::hide("metrics_warn_box"))
    return()
  }
  
  tryCatch({
    # 执行代码并获取原始结果
    result <- do.call(metrics_run_code,
                      list(r_code = r_values$metrics_r_code, envir = r_data))
    r_data$metrics_temp_result <- result
    dataset_name <- input$dataset  # 获取当前数据集名称
    
    # 分支1：屏蔽图表输出
    if (inherits(result, "gg") || inherits(result, "ggplot") || inherits(result, "lattice")) {
      r_values$metrics_result_type <- "text"
      output$metrics_result_text <- renderText(i18n$t("This tool only supports statistical metrics calculation, not chart generation"))
    } 
    # 分支2：所有统计结果转为结构化文本
    else {
      r_values$metrics_result_type <- "text"
      # 调用格式化函数，生成示例风格的文本
      formatted_text <- format_stat_text(result, dataset_name)
      # 输出文本（保留换行和空格对齐）
      output$metrics_result_text <- renderText(paste(formatted_text, collapse = "\n"))
    }
    
    r_values$metrics_result_ready <- TRUE
  }, error = function(e) {
    r_values$metrics_result_type <- "error"
    # 错误文本格式化
    err_msg <- if (grepl("object .* not found", e$message)) {
      paste0(i18n$t("Error: Target column does not exist - "), e$message)
    } else if (grepl("non-numeric argument", e$message)) {
      paste0(i18n$t("Error: Variable type mismatch (e.g., t-test requires numeric variables) - "), e$message)
    } else {
      paste0(i18n$t("Error: "), e$message)
    }
    output$metrics_result_error <- renderText(err_msg)
    r_values$metrics_result_ready <- TRUE
    showNotification(err_msg, type = "error", duration = NULL)
  })
}, ignoreInit = TRUE)
## ======== 结果展示区（仅文本/错误输出）========
output$metrics_result_area <- renderUI({
  req(r_values$metrics_result_ready)
  tagList(
    # 所有结果均用文本框展示（含图表屏蔽提示、统计结果、错误）
    conditionalPanel(
      condition = "output.metrics_result_type == 'text' || output.metrics_result_type == 'error'",
      verbatimTextOutput("metrics_result_text", placeholder = TRUE)
    )
  )
})
output$metrics_result_type <- reactive({
  r_values$metrics_result_type 
})
outputOptions(output, "metrics_result_type", suspendWhenHidden = FALSE)
## ==================== 编辑代码模态框 ====================
observeEvent(input$metrics_edit_code, {
  showModal(
    modalDialog(
      title = i18n$t("Edit R Code"),
      size  = "l",
      footer = tagList(
        actionButton("metrics_save_code", i18n$t("Save Changes"), class = "btn-primary"),
        modalButton(i18n$t("Cancel"))
      ),
      aceEditor(
        "metrics_code_editor",
        mode = "r",
        theme = getOption("radiant.ace_theme", "tomorrow"),
        wordWrap = TRUE,
        value = r_values$metrics_r_code,
        placeholder = i18n$t("Edit the generated R code here..."),
        vimKeyBinding = getOption("radiant.ace_vim.keys", FALSE),
        tabSize = getOption("radiant.ace_tabSize", 2),
        useSoftTabs = getOption("radiant.ace_useSoftTabs", TRUE),
        showInvisibles = getOption("radiant.ace_showInvisibles", FALSE),
        autoScrollEditorIntoView = TRUE,
        minLines = 15,
        maxLines = 30
      )
    )
  )
})
## ==================== 保存代码 ====================
observeEvent(input$metrics_save_code, {
  r_values$metrics_r_code <- input$metrics_code_editor
  r_values$auto_run <- FALSE
  removeModal()
})
## ==================== 报告 / 截图 ====================
metrics_report <- function() {}
observeEvent(input$metrics_report, metrics_report())
observeEvent(input$metrics_screenshot, radiant_screenshot_modal("modal_metrics_screenshot"))
observeEvent(input$modal_metrics_screenshot, { metrics_report(); removeModal() })