.getReactiveEnvironment（）$ currentContext（）中的闪亮错误错误：

Question

我基本上打算做的是根据用户选择一个子集＆＃39;输入并做一些操作，比如计算每个数据集的百分比并绘制ggplot。但是当我写这个闪亮的应用程序服务器时，它一直给我错误：

Listening on http://127.0.0.1:5884
Warning: Error in .getReactiveEnvironment()$currentContext: Operation not allowed without an active reactive context. (You tried to do something that can only be done from inside a reactive expression or observer.)
Stack trace (innermost first):
    48: .getReactiveEnvironment()$currentContext
    47: .subset2(x, "impl")$get
    46: $.reactivevalues
    45: $
    44: eval
    43: eval
    42: subset.data.frame
    41: subset
    40: server [/Users/Qiner/Downloads/ME Analyst Assessment Files/server.R#7]
     1: runApp
Error in .getReactiveEnvironment()$currentContext() : 
  Operation not allowed without an active reactive context. (You tried to do something that can only be done from inside a reactive expression or observer.)

我已尝试按现有答案建议的reactive({})功能，但错误仍然存​​在。有人知道答案吗？非常感谢！这是我的代码：

    server <- function(input, output) {
      library(shiny)
      library(radarchart)
      library(ggplot2)
      library(reshape2)
    top_version<-read.csv("top_version.csv",header = T)
      #plot1 data
      ds<-subset(top_version,top_version$ageInd==input$select1)
      labs<-c('familiarity','favorability','consideration')
      scores<-reactive({
      scores<-list('Women'=c(nrow(ds[ds$familiarity==1 & ds$gender==2,])/nrow(ds[ds$gender==2,]),nrow(ds[ds$favorability==1 & ds$gender==2,])/nrow(ds[ds$gender==2,]),nrow(ds[ds$consideration==1 & ds$gender==2,])/nrow(ds[ds$gender==2,])),
                   'Men'=c(nrow(ds[ds$familiarity==1 & ds$gender==1,])/nrow(ds[ds$gender==1,]),nrow(ds[ds$favorability==1 & ds$gender==1,])/nrow(ds[ds$gender==1,]),nrow(ds[ds$consideration==1 & ds$gender==1,])/nrow(ds[ds$gender==1,])))
      })
       #plot2 data
      scores2<-list("Age 18-24"=c(nrow(top_version[top_version$familiarity==1 & top_version$ageInd=="Age 18-24",])/nrow(top_version[top_version$ageInd=="Age 18-24",]),nrow(top_version[top_version$favorability==1 & top_version$ageInd=="Age 18-24",])/nrow(top_version[top_version$ageInd=="Age 18-24",]),nrow(top_version[top_version$consideration==1 & top_version$ageInd=="Age 18-24",])/nrow(top_version[top_version$ageInd=="Age 18-24",])),
                    "Age 25-44"=c(nrow(top_version[top_version$familiarity==1 & top_version$ageInd=="Age 25-44",])/nrow(top_version[top_version$ageInd=="Age 25-44",]),nrow(top_version[top_version$favorability==1 & top_version$ageInd=="Age 25-44",])/nrow(top_version[top_version$ageInd=="Age 25-44",]),nrow(top_version[top_version$consideration==1 & top_version$ageInd=="Age 25-44",])/nrow(top_version[top_version$ageInd=="Age 25-44",])),
                    "Age 45-64"=c(nrow(top_version[top_version$familiarity==1 & top_version$ageInd=="Age 45-64",])/nrow(top_version[top_version$ageInd=="Age 45-64",]),nrow(top_version[top_version$favorability==1 & top_version$ageInd=="Age 45-64",])/nrow(top_version[top_version$ageInd=="Age 45-64",]),nrow(top_version[top_version$consideration==1 & top_version$ageInd=="Age 45-64",])/nrow(top_version[top_version$ageInd=="Age 45-64",])),
                    "Age 65+"=c(nrow(top_version[top_version$familiarity==1 & top_version$ageInd=="Age 65+",])/nrow(top_version[top_version$ageInd=="Age 65+",]),nrow(top_version[top_version$favorability==1 & top_version$ageInd=="Age 65+",])/nrow(top_version[top_version$ageInd=="Age 65+",]),nrow(top_version[top_version$consideration==1 & top_version$ageInd=="Age 65+",])/nrow(top_version[top_version$ageInd=="Age 65+",])))
      #plot3 data
com_1<-subset(top_version,familiarity==as.integer(input$select2) & favorability==as.integer(input$select3) & as.integer(input$select4))
    com_2<-subset(top_version,familiarity==as.integer(input$select5) & favorability==as.integer(input$select6) & as.integer(input$select7))
    abc_0<-reactive({
      de_1<-rep(nrow(com_1),19)
      sum_0<-apply(com_1[,1:19],2,sum)
      portion_0<-sum_0/de_1
      #return(portion_0)
    })
    abc_1<-reactive({
      de_2<-rep(nrow(com_2),19)
      sum_1<-apply(com_2[,1:19],2,sum)
      portion_1<-sum_1/de_1
      #return(portion_1)
    })

      df<-reactive({
        df<-melt(data.frame(i=names(top_version)[1:19],name1=abc_0(),name2=abc_1()),id="i")
      })

   #begin plot
      output$plot1 <- renderPlot({
        chartJSRadar(scores=scores(), labs=labs,showToolTipLabel = T)
      })
      output$plot2 <- renderPlot({
        chartJSRadar(scores=scores2, labs=labs,showToolTipLabel = T)
      })
      output$plot3 <- renderPlot({
        ggplot(df(), aes(x=i,y=value,colour=variable,group=variable)) + 
          geom_line()+theme(axis.text.x = element_text(angle = 90, hjust = 1))
      })

    }