在不同选项卡中显示使用自定义函数生成的不同图

Question

我是闪亮仪表板的初学者。当前，我希望有2个不同的选项卡，如果插入了适当的CSV文件，这些选项卡可以生成多个图。

我具有格式化用户CSV文件的功能，这些功能会将它们转换为包含在列表中的数据帧。然后，我还有另一个功能可以绘制这些数据框（将它们转换为副本编号图）。这是我目前为仪表板提供的简化版本...

ui <-
  dashboardPage(
    skin = "blue",
    dashboardHeader(title = "Dashboard"),
    dashboardSidebar(
      sidebarMenu(
        menuItem("Guide", tabName = "Guide", icon = icon("info")),
        menuItem("Copy-Number-Analysis", icon = icon("dna"),
                 menuSubItem("Filtered-Amplicon", tabName = "Filtered-Amplicon", icon = icon("arrow-alt-circle-right")),
                 menuSubItem("Whole-Chromosome", tabName = "Whole-Chromosome", icon = icon("arrow-alt-circle-right"))
                 )
      )
    ),
    dashboardBody(
      tabItems(
        tabItem(tabName = "Guide",
                fluidRow(box(
                  title = strong("How do I use this application?",style = "font-size: 160%;"),
                ))
        ),
        tabItem(tabName = "Filtered-Amplicon",
                fluidRow(box(
                  title = strong("Filtered Amplicon Copy Number Plot", style = "font-size: 160%;"),
                  status = "danger",
                  solidHeader = T,
                  width = 12,
                  fileInput("file1", h4("Input your file(s) in csv format!"),
                            accept = c(
                              "text/csv",
                              "text/comma-separated-values,text/plain",
                              ".csv"),
                            multiple = TRUE
                  ),
                  uiOutput("PlotVisualizeAmplicon") #Visualize plot
                ))),
        tabItem(tabName = "Whole-Chromosome",
                fluidRow(box(
                  title = strong("Whole Chromosome Copy Number Plot", style = "font-size: 160%;"),
                  status = "danger",
                  solidHeader = T,
                  width = 12,
                  fileInput("file2", h4("Input your file(s) in csv format!"),
                            accept = c(
                              "text/csv",
                              "text/comma-separated-values,text/plain",
                              ".csv"),
                            multiple = TRUE
                  ),
                  uiOutput("PlotVisualizeWhole") #Visualize plot
                ))
                )
        )
      )
    )
  )

server <- function(input, output) {
  #Set the number of max input
  maxPlot <- 100

  #AMPLICON PLOT
  #Data Input
  dataPlotInput2 <- reactive({
    if(is.null(input$file1)){return()}

    #Input CSVs
    files_name <- as.list(rep(NA, length(input$file1$datapath)))
    for (i in 1:length(input$file1$datapath)){
      files_name[[i]] <- as.character(input$file1[i,4])
    }

    files_list <- as.list(rep(NA, length(input$file1$datapath)))
    for(i in 1:length(input$file1$datapath)){
      files_list[[i]] <-  read_csv(
        file = as.character(files_name[[i]]))%>%
        select(1:5)
    }
    names(files_list) <- files_name

    #Copy Number analysis
    files_formated <- format_all(files_list)
    comparison_tbl_Amplicon <- ref_compare_all(files_formated, reference = reference1)
    comparison_tbl_Amplicon
  })
  # Produce plot(s)
  for (i in 1:maxPlot) {
    local({
      my_i <- i
      plotnameAmplicon <- paste("plot", my_i, sep="")
      output[[plotnameAmplicon]] <- renderPlot({
        plot_aneuploid(dataPlotInput2()[[my_i]], size = 2) + ggtitle(as.character(input$file1[my_i,1]))
      })
    })
  }
  output$PlotVisualizeAmplicon <- renderUI({
    if(is.null(input$file1)){return()}

    FileNumber <- nrow(input$file1)

    plot_output_list_Amplicon <- lapply(1:FileNumber, function(i) {
      plotnameAmplicon <- paste("plot", i, sep="")
      plotOutput(plotnameAmplicon, width = "100%", height = "400px")
    })
    do.call(tagList, plot_output_list_Amplicon)
  })

  ##WHOLE CHROMOSOME PLOT
  #Data input
  dataPlotInput3 <- reactive({
    if(is.null(input$file2)){return()}

    #Input CSVs
    files_name <- as.list(rep(NA, length(input$file2$datapath)))
    for (i in 1:length(input$file2$datapath)){
      files_name[[i]] <- as.character(input$file2[i,4])
    }

    files_list <- as.list(rep(NA, length(input$file2$datapath)))
    for(i in 1:length(input$file2$datapath)){
      files_list[[i]] <-  read_csv(
        file = as.character(files_name[[i]]))%>%
        select(1:5)
    }
    names(files_list) <- files_name

    #Copy Number analysis
    files_formated <- format_all(files_list)
    comparison_tbl_Whole <- ref_compare_whole_chr_all(files_formated, reference = reference1)
    comparison_tbl_Whole
  })
  #Produce plot(s)
  for (i in 1:maxPlot) {
    local({
      my_j <- i
      plotnameWhole <- paste("plot", my_j, sep="")

      output[[plotnameWhole]] <- renderPlot({
        plot_aneuploid_whole_chr(dataPlotInput3()[[my_j]], size = 2) + ggtitle(as.character(input$file2[my_j,1]))
      })
    })
  }
  output$PlotVisualizeWhole <- renderUI({
    if(is.null(input$file2)){return()}

    FileNumber <- nrow(input$file2)

    plot_output_list_Whole <- lapply(1:FileNumber, function(i) {
      plotnameWhole <- paste("plot", i, sep="")
      plotOutput(plotnameWhole, width = "100%", height = "400px")
    })
    do.call(tagList, plot_output_list_Whole)
  })


}

我的最终目标是能够在我拥有的两个选项卡中生成不同的图，这些图应该看起来像这样，使得我能够交替使用它们...我目前无法同时在不同的选项卡中生成两个图。只有在其他选项卡不存在时，我才能够生成它们（我将未使用的选项卡转换为注释以生成这些图像）。

我可视化绘图的方式是通过在ui函数中使用uiOutput。我使用renderPlot在output[[plotnameAmplicon]]和output[[plotnameWhole]]内部生成了绘图。然后，我使用renderUi显示所有图。仅当其他绘图选项卡不存在时，此方法才有效。如果运行了我当前拥有的代码，由于某种原因，tab2的结果将显示在tab1中，并且我将无法生成Tab 1的图。有没有办法来解决这个问题。由于我不熟悉闪亮仪表板，因此任何改进绘图逻辑的建议也受到高度赞赏。

Answer 1

我找到了解决方案。通过将renderPlot封装在renderUi内，并为renderPlot提供不同的变量名（我犯了一个严重错误），我能够产生所需的输出。

  output$PlotVisualizeWhole <- renderUI({
    if(is.null(input$file2)){return()}

    FileNumber <- nrow(input$file2)

    plot_output_list_Whole <- lapply(1:FileNumber, function(i) {
      plotnameWhole <- paste("plotwhole", i, sep="")
      output[[plotnameWhole]] <- renderPlot({
        plot_aneuploid_whole_chr(dataPlotInput3()[[i]], size = 2) + ggtitle(as.character(input$file2[i,1]))})
      plotDownload <- paste("Downloaded", i, sep = "")
      plotOutput(plotnameWhole, width = "100%", height = "400px")
    })
    do.call(tagList, plot_output_list_Whole)
  })