update

Dockerfile

@@ -10,17 +10,16 @@ RUN R -e "install.packages(c('shiny', 'shinydashboard', 'remotes','readxl'), rep
 RUN echo 'options(radiant.shinyFiles = FALSE)' >> /usr/local/lib/R/etc/Rprofile.site
 COPY . /srv/shiny-server/
 COPY set_path.R /usr/local/lib/R/etc/Rprofile.site.d/00-radiant-path.R
+RUN echo 'source("/srv/shiny-server/radiant.model/R/coxp.R")' >> /usr/local/lib/R/etc/Rprofile.site
 
-# 安装所有子模块
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.data',dependencies=TRUE, type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.basics',dependencies=TRUE, type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.model',dependencies=TRUE, type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.multivariate',dependencies=TRUE, type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.design',dependencies=TRUE, type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.quickgen',dependencies=TRUE, type='source', upgrade='never')"
-
-# 安装主 radiant 应用
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant-master',dependencies=TRUE, type='source', upgrade='never')"
+# 安装所有模块
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.data',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.basics',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.model',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.multivariate',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.design',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.quickgen',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant-master',dependencies=TRUE, type='source', upgrade='never',force=TRUE)"
 
 WORKDIR /data
 CMD ["R", "-e", "radiant::radiant(host='0.0.0.0', port=3838)"]

radiant-master/inst/translations/translation_zh.csv

@@ -137,6 +137,7 @@ Probabilities:,概率：,"goodness_ui.R,randomizer_ui.R"
 "Enter probabilities (e.g., 1/2 1/2)",输入概率（例如：1/2 1/2）,"goodness_ui.R,randomizer_ui.R"
 Discrete,离散分布,"prob_calc_ui.R,simulater_ui.R"
 F,F 分布,prob_calc_ui.R
+t,t 分布,prob_calc_ui.R
 Log normal,对数正态分布,"prob_calc_ui.R,simulater_ui.R"
 Poisson,泊松分布,"prob_calc_ui.R,simulater_ui.R"
 Values,数值,prob_calc_ui.R
@@ -456,7 +457,7 @@ All,全部,"view_ui.R,evalbin_ui.R, evalreg_ui.R"
 "Table slice {input$view_tab_slice} will be applied on Download, Store, or Report",表格切片 {input$view_tab_slice} 将应用于下载、存储或报告,view_ui.R
 Dataset ',数据集 ',view_ui.R
 ' was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the dataset by clicking the report icon on the bottom left of your screen.,' 已成功添加到数据集下拉菜单中。通过点击左下角的报告图标，在 Report > Rmd 或 Report > R 中添加代码以（重新）创建数据集。,view_ui.R
-Distribution,分布,"visualize_ui.R,logistic_ui.R"
+Distribution,分布图,"visualize_ui.R,logistic_ui.R"
 Surface,表面图,visualize_ui.R
 Line,折线图,"visualize_ui.R,regress_ui.R"
 Box-plot,箱线图,visualize_ui.R
@@ -818,7 +819,7 @@ Odds, "赔率", "logistic_ui.R"
 Correlations, "相关性", "logistic_ui.R"
 Model fit, "模型拟合", "logistic_ui.R"
 Coefficient (OR) plot, "系数（OR）图", "logistic_ui.R"
-Influential observations, "影响观察值", "logistic_ui.R"
+Influential observations, "影响点图", "logistic_ui.R"
 This analysis requires a response variable with two levels and one or more explanatory variables. If these variables are not available please select another dataset.,该分析需要一个具有两个级别的响应变量以及一个或多个解释变量。如果这些变量不可用，请选择另一个数据集。, "logistic_ui.R"
 Drop intercept,去除截距项,mnl_ui.R
 RRRs,相对风险比 (RRR),mnl_ui.R
@@ -1182,8 +1183,12 @@ Estimate class probabilities,估计类别概率,svm_ui.R
 Choose Excel file:,选择Excel文件：,manage_ui.R
 Sheet index (1-based):,工作表索引（从1开始）：,manage_ui.R
 First row as header,第一行为表头,manage_ui.R
-Time variable:,生存时间变量：,cox_ui.R
-Status variable:,事件状态变量：,cox_ui.R
+Time variable:,生存时间变量：,coxp_ui.R
+Status variable:,事件状态变量：,coxp_ui.R
 AI running...,大模型运行中...,quickgen_ai_ui.R
 Warning:Please enter a request related to descriptive statistics or visualization.,警告：请输入与描述性统计或可视化相关的请求。,quickgen_ai_ui.R
 Boxplot,箱型图,homo_variance_test_ui.R
+Survival curves,生存曲线,coxp_ui.R
+Cumulative hazard,累积风险,coxp_ui.R
+Schoenfeld residuals,Schoenfeld残差图,coxp_ui.R
+Martingale residuals,鞅残差图,coxp_ui.R

radiant.model/inst/app/tools/analysis/coxp_ui.R

@@ -8,11 +8,11 @@ coxp_lines <- setNames(c("line", "loess", "jitter"),
                        c(i18n$t("Line"), i18n$t("Loess"), i18n$t("Jitter")))
 
 coxp_plots <- setNames(
-  c("none", "dist", "vip", "pred_plot", "pdp", "coef", "influence"),
+  c("none", "dist", "vip", "coef", "survival", "cumhaz", "schoenfeld", "martingale"),
   c(i18n$t("None"), i18n$t("Distribution"), 
-    i18n$t("Permutation Importance"), i18n$t("Prediction plots"),
-    i18n$t("Partial Dependence"), i18n$t("Coefficient plot"), 
-    i18n$t("Influential observations"))
+    i18n$t("Permutation Importance"), i18n$t("Coefficient plot"),
+    i18n$t("Survival curves"), i18n$t("Cumulative hazard"),
+    i18n$t("Schoenfeld residuals"), i18n$t("Martingale residuals"))
 )
 
 ## 2. 参数收集 -------------------------------------------------------------
@@ -34,7 +34,41 @@ coxp_inputs <- reactive({
   args
 })
 
-coxp_plot_inputs <- reactive({ list() })
+coxp_plot_inputs <- reactive({
+  args <- list()
+
+  # 传递用户设置的置信水平
+  args$conf_lev <- input$coxp_conf_lev %||% 0.95
+  
+  # 1. 处理 plots 参数
+  if (is.empty(input$coxp_plots, "none")) {
+    args$plots <- character(0) 
+  } else {
+    args$plots <- c(input$coxp_plots) 
+  }
+  
+  # 2. 处理 incl 参数 (用于 coef)
+  if (input$coxp_plots == "coef") {
+    args$incl <- input$coxp_incl
+    args$intercept <- input$coxp_intercept 
+  }
+  
+  # 3. 处理 lines 参数 (用于 martingale)
+  if (input$coxp_plots == "martingale") {
+    args$lines <- input$coxp_lines
+  }
+  
+  # 4. 处理 nrobs 参数
+  if (input$coxp_plots %in% c("dist", "martingale")) {
+    args$nrobs <- input$coxp_nrobs
+  }
+  
+  # 5. 添加 shiny 标志
+  args$shiny <- TRUE
+  
+  return(args)
+})
+
 
 coxp_pred_inputs <- reactive({
   args <- coxp_pred_args
@@ -99,27 +133,6 @@ output$ui_coxp_incl <- renderUI({
   )
 })
 
-output$ui_coxp_incl_int <- renderUI({
-  req(available(input$coxp_evar))
-  choices <- character(0)
-  vars <- input$coxp_evar
-  if (length(vars) > 1) {
-    choices <- iterms(vars, 2)
-  } else {
-    updateSelectInput(session, "coxp_incl_int", choices = choices, selected = choices)
-    return()
-  }
-  selectInput(
-    "coxp_incl_int",
-    label = i18n$t("2-way interactions to explore:"),
-    choices = choices,
-    selected = state_multiple("coxp_incl_int", choices),
-    multiple = TRUE,
-    size = min(8, length(choices)),
-    selectize = FALSE
-  )
-})
-
 ## 5. 预测 / 绘图 / 刷新按钮 ----------------------------------------------
 observeEvent(input$dataset, {
   updateSelectInput(session, "coxp_predict", selected = "none")
@@ -187,15 +200,10 @@ output$ui_coxp <- renderUI({
         selectInput("coxp_plots", i18n$t("Plots:"), choices = coxp_plots,
                     selected = state_single("coxp_plots", coxp_plots)),
         conditionalPanel(
-          condition = "input.coxp_plots == 'coef' || input.coxp_plots == 'pdp' || input.coxp_plots == 'pred_plot'",
-          uiOutput("ui_coxp_incl"),
-          conditionalPanel(
-            condition = "input.coxp_plots == 'coef'",
-            checkboxInput("coxp_intercept", i18n$t("Include intercept"), state_init("coxp_intercept", FALSE))
-          ),
-          conditionalPanel(
-            condition = "input.coxp_plots == 'pdp' | input.coxp_plots == 'pred_plot'",
-            uiOutput("ui_coxp_incl_int")
+          condition = "input.coxp_plots == 'martingale'",
+          checkboxGroupInput(
+            "coxp_lines", i18n$t("Add lines:"), coxp_lines,
+            selected = state_group("coxp_lines", "loess")
           )
         )
       )
@@ -214,30 +222,34 @@ coxp_plot <- reactive({
   if (is.empty(input$coxp_plots, "none")) return()
   plot_width <- 650
   plot_height <- 500
-  nr_vars <- length(input$coxp_evar) + 1
-  
-  if (input$coxp_plots == "dist") {
-    plot_height <- (plot_height / 2) * ceiling(nr_vars / 2)
-  } else if (input$coxp_plots == "dashboard") {
-    plot_height <- 1.5 * plot_height
-  } else if (input$coxp_plots == "correlations") {
-    plot_height <- 150 * nr_vars
-    plot_width <- 150 * nr_vars
-  } else if (input$coxp_plots == "coef") {
-    incl <- paste0("^(", paste0(input$coxp_incl, "[|]*", collapse = "|"), ")")
-    nr_coeff <- sum(grepl(incl, .coxp()$coeff$label))
-    plot_height <- 300 + 20 * nr_coeff
-  } else if (input$coxp_plots %in% c("scatter", "resid_pred")) {
-    plot_height <- (plot_height / 2) * ceiling((nr_vars - 1) / 2)
-  } else if (input$coxp_plots == "vip") {
-    plot_height <- max(500, 30 * nr_vars)
-  } else if (input$coxp_plots %in% c("pdp", "pred_plot")) {
-    nr_vars <- length(input$coxp_incl) + length(input$coxp_incl_int)
-    plot_height <- max(250, ceiling(nr_vars / 2) * 250)
-    if (length(input$coxp_incl_int) > 0) {
-      plot_width <- plot_width + min(2, length(input$coxp_incl_int)) * 90
-    }
-  }
+  nr_vars <- length(input$coxp_evar)
+  switch(input$coxp_plots,
+         "dist" = {
+           plot_height <- (plot_height / 2) * ceiling((nr_vars + 2) / 2)  # +2 for time/status
+         },
+         "coef" = {
+           incl <- paste0("^(", paste0(input$coxp_incl, "[|]*", collapse = "|"), ")")
+           nr_coeff <- if (is.empty(input$coxp_incl)) nr_vars else length(input$coxp_incl)
+           plot_height <- 300 + 20 * nr_coeff
+         },
+         "vip" = {
+           plot_height <- max(500, 30 * nr_vars)
+         },
+         "survival" = {
+           plot_height <- 400
+           plot_width <- 600
+         },
+         "cumhaz" = {
+           plot_height <- 400
+           plot_width <- 600
+         },
+         "schoenfeld" = {
+           plot_height <- 400
+         },
+         "martingale" = {
+           plot_height <- 400
+         }
+  )
   list(plot_width = plot_width, plot_height = plot_height)
 })
 
@@ -398,7 +410,7 @@ coxp_available <- reactive({
   if (not_pressed(input$coxp_run)) return(i18n$t("** Press the Estimate button to estimate the model **"))
   if (is.empty(input$coxp_plots, "none")) return(i18n$t("Please select a plot from the drop-down menu"))
   if (coxp_available() != "available") return(coxp_available())
-  valid_plots <- c("coef", "dist", "vip", "pdp", "pred_plot", "influence")
+  valid_plots <- c("dist", "vip", "coef", "survival", "cumhaz", "schoenfeld", "martingale")
   if (!input$coxp_plots %in% valid_plots) {
     return(i18n$t("Selected plot type is not supported for Cox models."))
   }
@@ -406,7 +418,7 @@ coxp_available <- reactive({
     check_for_pdp_pred_plots("coxp")
   }
   withProgress(message = i18n$t("Generating plots"), value = 1, {
-    do.call(plot, c(list(x = .coxp()), coxp_plot_inputs(), shiny = TRUE))
+    do.call(plot, c(list(x = .coxp()), coxp_plot_inputs()))
   })
 })
 
@@ -417,7 +429,11 @@ coxp_report <- function() {
   inp_out <- list(list(prn = TRUE), "")
   figs <- FALSE
   if (!is.empty(input$coxp_plots, "none")) {
-    inp <- check_plot_inputs(coxp_plot_inputs())
+    plot_inp <- coxp_plot_inputs()
+    if (is.null(plot_inp$plots) || length(plot_inp$plots) == 0) {
+      plot_inp$plots <- ""
+    }
+    inp <- check_plot_inputs(plot_inp)
     inp_out[[2]] <- clean_args(inp, list())
     inp_out[[2]]$custom <- FALSE
     outputs <- c(outputs, "plot")