R Shiny：从选定的输入创建动态 UI答案

【问题标题】：R Shiny: create dynamic UI from selected inputR Shiny：从选定的输入创建动态 UI
【发布时间】：2020-10-14 03:12:42
【问题描述】：

我正在尝试创建一个动态 UI，该 UI 根据来自 selectInput() 命令的选定变量的数量生成 N 个部分。对于选择的每个变量，我希望有自己的部分，让您进一步指定该变量的其他属性（例如，如果它是数字或字符，如何估算缺失值等）

我有使用insertUI() 和removeUI() 的经验，并且能够制作一个我希望它看起来像的小例子。执行此操作的代码部分如下所示：

    insertUI(
      selector = '#ui_test',
      ui = tags$div(id = "extra_criteria",
                    h4("Covariate 1 (example)"),
                    selectInput("cov_1_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_1_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_1_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 2 (example)"),
                    selectInput("cov_2_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_2_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_2_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 3 (example)"),
                    selectInput("cov_3_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_3_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_3_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 4 (example)"),
                    selectInput("cov_4_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_4_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_4_impute_default_level", "Impute default level","0")
      )
    )

我想要完成的是使上面的部分变得健壮和动态，如果用户只选择 2 个变量，那么我只想创建部分 h4("Covariate 1 (example)") 和 h4("Covariate 2 (example)")。例如，如果选择了 age 和 sex，那么我希望我的部分看起来像：

    insertUI(
      selector = '#ui_test',
      ui = tags$div(id = "extra_criteria",
                    h4("Age"),
                    selectInput("age_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("age_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("age_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Sex"),
                    selectInput("sex_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("sex_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("sex_impute_default_level", "Impute default level","0")
                    
      )
    )

我最初打算通过循环选定输入中的变量并创建所需输出的长字符串（即h4(Covariate N) 的块），然后将其传递给eval(parse(text="...")) 来解决此问题。最终会是这样的：

    insertUI(
      selector = '#ui_test',
      ui = tags$div(id = "extra_criteria",
                    eval(parse(text="..."))
      )
    )

其中"..." 部分是h4("Covariate N) 的块，被视为字符串。现在，我不知道这是否可行，但这是我目前唯一的方法。有没有更好的方法来解决这个问题，也许是shiny 中的一些函数？任何帮助或建议将不胜感激。我的模拟示例可以在下面找到：

library(shiny)
library(shinyjs)

ui <- shinyUI(fluidPage(
  shinyjs::useShinyjs(),
  navbarPage("Test",id="navbarPage",
             tabPanel("First tab", id = "first_tab",
                      sidebarLayout(
                        sidebarPanel(
                          selectInput('covariates', 'Select covariates', choices = c("age","sex","race","bmi"), multiple=TRUE, selectize=TRUE), 
                          actionButton("set.covariates","Set"),
                          tags$hr(),
                          tags$div(id = 'ui_test')
                        ),
                        mainPanel(
                          verbatimTextOutput("list")
                        )
                      )
             ))
))

# Define server logic required to draw a histogram
server <- shinyServer(function(input, output, session) {
  
  observe({
    if (is.null(input$covariates) || input$covariates == "") {
      shinyjs::disable("set.covariates")
      
    } else {
      shinyjs::enable("set.covariates")
    }
  })
  
  observeEvent(input$set.covariates, {
    shinyjs::disable("set.covariates")
  })
  
  prep.list <- eventReactive(input$set.covariates,{
    cov <- input$covariates
    timeIndep.list <- NULL
    for(L0.i in seq_along(cov)){
      timeIndep.list[[L0.i]] <- list("categorical"=FALSE,
                                     "impute"=NA,
                                     "impute_default_level"=NA)
    }
    names(timeIndep.list) <- cov
    return(timeIndep.list)
  })
  
  output$list <- renderPrint({
    prep.list()
  })
  
  observeEvent(req(input$set.covariates), {
    insertUI(
      selector = '#ui_test',
      ui = tags$div(id = "extra_criteria",
                    h4("Covariate 1 (example)"),
                    selectInput("cov_1_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_1_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_1_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 2 (example)"),
                    selectInput("cov_2_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_2_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_2_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 3 (example)"),
                    selectInput("cov_3_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_3_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_3_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 4 (example)"),
                    selectInput("cov_4_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_4_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_4_impute_default_level", "Impute default level","0")
      )
    )})
  
  observeEvent({input$covariates}, {
    removeUI(selector = '#extra_criteria')
  })
  
  
})

# Run the application
shinyApp(ui = ui, server = server)

【问题讨论】：

也许来自this 的东西可以提供帮助（尤其是来自 Paul 的 cmets）

标签： r shiny shiny-reactivity shinyjs

【解决方案1】：

在insertUI函数的描述页面中，写着：

与 renderUI() 不同，使用 insertUI() 生成的 UI 是持久的：一旦它被创建，它就会一直留在那里，直到被 removeUI() 删除。每个对 insertUI() 的新调用会创建更多 UI 对象，除了已经存在的（都相互独立）。更新一个 UI 的一部分（例如：输入对象），您必须使用适当的渲染函数或自定义反应函数。

所以你不能在这里使用insertUI。而是使用renderUI 函数和uiOutput 来动态生成ui 元素。

接下来，要根据选择多次生成ui，可以使用lapply。由于迭代次数将取决于向量中的项目数，即input$对象；生成的 ui 的数量将基于选择的数量。

我认为下面的代码可以解决你的问题：

library(shiny)
library(shinyjs)

ui <- shinyUI(fluidPage(
  shinyjs::useShinyjs(),
  navbarPage("Test",id="navbarPage",
             tabPanel("First tab", id = "first_tab",
                      sidebarLayout(
                        sidebarPanel(
                          selectInput('covariates', 'Select covariates', choices = c("age","sex","race","bmi"), multiple=TRUE, selectize=TRUE), 
                          actionButton("set.covariates","Set"),
                          tags$hr(),
                          uiOutput("covariateop")
                        ),
                        mainPanel(
                          verbatimTextOutput("list")
                        )
                      )
             ))
))

# Define server logic required to draw a histogram
server <- shinyServer(function(input, output, session) {
  
  observe({
    if (is.null(input$covariates) || input$covariates == "") {
      shinyjs::disable("set.covariates")
      
    } else {
      shinyjs::enable("set.covariates")
    }
  })
  
  observeEvent(input$set.covariates, {
    shinyjs::disable("set.covariates")
  })
  
  prep.list <- eventReactive(input$set.covariates,{
    cov <- input$covariates
    timeIndep.list <- NULL
    for(L0.i in seq_along(cov)){
      timeIndep.list[[L0.i]] <- list("categorical"=FALSE,
                                     "impute"=NA,
                                     "impute_default_level"=NA)
    }
    names(timeIndep.list) <- cov
    return(timeIndep.list)
  })
  
  output$list <- renderPrint({
    prep.list()
  })
  
  observeEvent(req(input$set.covariates), {
    insertUI(
      selector = '#ui_test',
      ui = tags$div(id = "extra_criteria",
                    h4("Covariate 1 (example)"),
                    selectInput("cov_1_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_1_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_1_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 2 (example)"),
                    selectInput("cov_2_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_2_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_2_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 3 (example)"),
                    selectInput("cov_3_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_3_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_3_impute_default_level", "Impute default level","0"),
                    tags$hr(),
                    h4("Covariate 4 (example)"),
                    selectInput("cov_4_class", "Covariate class",
                                choices = c("numeric","character")),
                    selectInput("cov_4_impute", "Impute",
                                choices = c("default","mean","mode","median")),
                    textInput("cov_4_impute_default_level", "Impute default level","0")
      )
    )})
  
  observeEvent(req(input$set.covariates), {
    output$covariateop <- renderUI({  
      lapply(input$covariates, function(x){
      
        tags$div(id = paste0("extra_criteria_for_", x),
                 h4(x),
                 selectInput("cov_1_class", "Covariate class",
                             choices = c("numeric","character")),
                 selectInput("cov_1_impute", "Impute",
                             choices = c("default","mean","mode","median")),
                 textInput("cov_1_impute_default_level", "Impute default level","0"),
                 tags$hr()
        )
      })
    })
    
  })
  
  observeEvent({input$covariates}, {
    removeUI(selector = '#extra_criteria')
  })
  
  
})

# Run the application
shinyApp(ui = ui, server = server)

【讨论】：