使用textInput（）动态重置上传文件的名称

Question

我有一个闪亮的应用程序，加载后包含6个csv文件（DB，TC，RH，DGI，DCH，LDP）。这6个文件正在处理中，并提供最终的数据帧finalDF()，如下所示：

然后我加载第7个文件，我将其标为“新建”，处理后的结果是这样的：

我的问题是我希望能够使用textInput()动态更改“新”名称，但不能使其正常工作。

下面，我提供了我的应用的实验版本（无效）。

#ui.r
# Load R libraries
library(shiny)        # Create interactive Shiny visualizations
library(tidyverse)    # Collection of packages for processing data
library(rowr)         # Facilitates data manipulation
library(rlist)        # Enables the append method
library(shinydashboard)# Creates the shinydashboard
library(ggplot2)
dashboardPage(
  dashboardHeader(title = "Stacked Bar Plot to Compare Datasets",
                  #width of the title
                  titleWidth = 375),
  dashboardSidebar(
    #same width for the sidebar
    width = 375,
    # Allow the user to select the variable to compare
    # Bold and bigger section title
    h4(strong("Select the identifier & datasets to compare:")),
    selectInput("comparisonSelector", h5("Select identifier:"), choices = c("None",
                                                                            "Drug Name",
                                                                            "ChEMBL ID",
                                                                            "DrugBank ID", 
                                                                            "Drug SMILES",
                                                                            "Target Symbol"),
                #select Drug with selected =
                selected = "Drug Name"),

    uiOutput("checkbox"),

    # Render the options for the Reference dataset
    uiOutput("reference"),

    h4(strong("Upload and process new dataset")),
    # Input: Select a file ----

    fileInput("file1", h5("Upload a file to compare"),
              multiple = FALSE,
              accept = c("text/csv",
                         "text/comma-separated-values,text/plain",
                         ".csv")),
    textInput("filename2",h5("Set Filename"),"Set Dataset Name")

  ),
  dashboardBody(
    fluidRow(
      tableOutput("contents")
    )

    )
  )
#server.r
function (input, output, session){

  # Load in the datasets and return a dataframe with 5 columns, corresponding to the 5 variables of interest.
  # Note that the columns extracted from each file are hard-coded values specific to each file's format.
  DB <- reactive({
    if("DB"%in% input$datasetSelector){
      x <- read.csv("1_DB_Subset_v1.csv", stringsAsFactors = F)
    }
  })

  TC <- reactive({
    if("TC" %in% input$datasetSelector){
      #x <- read.csv("2_TC_Subset_v1.csv", stringsAsFactors = F)
    }
  })
  RH <- reactive({
    if("RH" %in% input$datasetSelector){
      x <- read.csv("3_RH_Subset_v1.csv", stringsAsFactors = F)
    }
  })
  New <- reactive({
    req(input$file1)
    df <- read.csv(input$file1$datapath)

  })
  output$text2<-renderUI({
    textInput("filename2",
              "Specify name for uploaded dataset"

    )

  })

  #Create a list with all the datasets which will be updated when we upload a new one
  fileOptions <- reactiveValues(currentOptions=c("DB","TC","RH"))

  #Use an observer to watch for file uploads

  observeEvent(input$file1, {
    fileOptions$currentOptions = list.append(fileOptions$currentOptions,"New")

  })

  # Output a UI drop-down box that allows a user to select the Reference database to compare all other datasets to. 
  # This set of options consists of the user-selected datasets. Select reference dataset with selected=
  output$reference <- renderUI({
    selectInput("referenceDataset", h5("Select the Reference Dataset"), choices = input$datasetSelector,selected = "DB")
  })

  # Here I set fileOptions as choices in both choices and in selected. Selected choices are used to create the plot when the app starts.
  output$checkbox<-renderUI({
    checkboxGroupInput("datasetSelector",h5("Specify the datasets to compare:"), choices = fileOptions$currentOptions,
                       selected = c("DB","TC","RH"))
  })

  # Check for which variable has been selected by the user to be analyzed, and output a value to signify this. 
  # The number it outputs is used as an index for the dataframes.
  Variable <- reactive({

    if(input$comparisonSelector == "Drug Name"){
      1
    }
    else if(input$comparisonSelector == "ChEMBL ID"){
      2
    }
    else if(input$comparisonSelector == "DrugBank ID"){
      3
    }
    else if(input$comparisonSelector == "Drug SMILES"){
      4
    }
    else if(input$comparisonSelector == "Target Symbol"){
      5
    }
    else{
      NULL
    }


  })

  # Return a string for the name of the Reference dataset.
  referenceSet <- reactive({
    x <-  input$referenceDataset
    y <- eval(parse(text = paste0(x,"()")))

  })

  # Remove the name of the Reference dataset from the list of all datasets selected. 
  # e.g., if DrugBank is the Reference dataset, DrugBank is removed from the list of datasets loaded.
  # This ensures that the Reference dataset is not compared to itself in the resulting plot.
  comparisonSets <- reactive({
    x <- input$datasetSelector[!input$datasetSelector %in% input$referenceDataset]
  })


  # The following 3 blocks (125 - 168) calculate the overlap between datasets and the unique values of each dataset. 
  # This code generates a logical vector of whether a value is in both compared datasets or not. 
  # Then it counts the number of True values and appends that value to a vector.
  # This is looped for each dataset contained within the comparisonSets vector. All of the values are appended, and the vector is returned.
  # When calculating the unique values, just subtract the overlap value from the number of values for each database.
  OverlapVector <- reactive({
    y <- as.vector(NULL)  

    for(i in 1:len(comparisonSets())){  # For each of the Comparison datasets specified by the user

      # Convert the string name received from the checkbox input into a variable name 
      # Subset the dataframe to the specific column holding the user-selected variable
      # Remove duplicates
      # Compare the Comparison set vector with the Reference set vector using %in%. This checks each value in the referenceSet() against all of the values in the comparisonSets(), and returns a vector of the same length as the referenceSet().
      x <- unique(referenceSet()[,Variable()]) %in% unique(eval(parse(text = paste0(comparisonSets()[i],"()")))[,Variable()])

      x <- table(x)            # Create a frequency table to report the # of True and False values present in vector x
      x <- x[names(x) == TRUE] # Filter the vector for only the True values; returns the number of True values
      y <- append(y,x)         # Append the # of True values to the vector
    }
    y

  })

  UniqueToReferenceVector <- reactive({

    y <- as.vector(NULL)  

    for(i in 1:len(comparisonSets())){  # For each of the Comparison datasets specified by the user
      x <- unique(referenceSet()[,Variable()]) %in% unique(eval(parse(text = paste0(comparisonSets()[i],"()")))[,Variable()])
      x <- table(x)
      z <- len(unique(referenceSet()[,Variable()])) - (x[names(x) == TRUE])
      y <- append(y,z)
    }
    y

  })

  UniqueToComparisonVector <- reactive({

    y <- as.vector(NULL)  

    for(i in 1:len(comparisonSets())){  # For each of the Comparison datasets specified by the user
      x <- unique(referenceSet()[,Variable()]) %in% unique(eval(parse(text = paste0(comparisonSets()[i],"()")))[,Variable()])
      x <- table(x)
      z <- len(unique(eval(parse(text = paste0(comparisonSets()[i],"()")))[,Variable()])) - (x[names(x) == TRUE])
      y <- append(y,z)
    }
    y

  })

  # This section generates the dataframe structure that the plotting function will use. 
  # finalDF is an N x 4 dataframe in which each row is the name of the set being compared, and its 3 values (2 unique values and 1 overlap value).      
  **finalDF <- reactive({

    x <- cbind.data.frame(UniqueToReferenceVector(),
                          OverlapVector(),
                          UniqueToComparisonVector(),
                          comparisonSets())

    #The input$referenceDataset takes its value from the reference dataset selected every time by the user.
    colnames(x) <- (c(paste("Unique to",input$referenceDataset),"Overlap","Unique to Comparison Dataset",'ComparisonDatabaseName'))

    # Reorganize the data to prepare it for plotting
    finalDF <- x %>% 
      gather(c(paste("Unique to",input$referenceDataset),"Overlap","Unique to Comparison Dataset"), key = 'Class', value = count) %>%  # Transform the dataframe x into key-value pairs
      select(ComparisonDatabaseName, Class, count) %>%
      rename(Name = ComparisonDatabaseName) %>%
      arrange(Name, Class) %>%   # Rearrange the order of the Class column to match the following order: Class1, Overlap, Class 2
      mutate(
        Class = factor(Class, levels=c(paste("Unique to",input$referenceDataset),"Overlap","Unique to Comparison Dataset",'Name'), ordered = T),
        Name = factor(Name, levels = (comparisonSets()), ordered = T))

    finalDF$Name <- factor(finalDF$Name, levels = comparisonSets())

    View(finalDF)
    finalDF  
  })**
  output$contents <- renderTable({
    finalDF()
  })


}