Question

我正在使用RShiny设置一个交互式仪表板。目的是允许选定的用户输入带有指定参数估计值的文件。我已经在预先存在的R Script文件中开发了一个回归模型。我的计划是使用此预先存在的模型，使用用户已上传的参数来预测因变量。以下站点特别有用：https://datascience-enthusiast.com/R/shiny_ML.html。但是，当我尝试使用load（）命令加载保存的模型（.rda）并使用source（）引用模型来自（.R）的脚本时，我的代码崩溃了。

我收到以下错误 “警告文件（文件名，“ r”，编码=编码）：无法打开文件“ PolyFunct.R”：没有此类文件或目录警告：文件错误：无法打开连接 [没有可用的堆栈跟踪]”

我尝试使用ShinyServer函数上方及其内部的load（）和Source（）。两者都不起作用。我试图将预先存在的模型作为单独的save R脚本和ShinyServer函数之上的函数包括在内。帮助将不胜感激。


    ETL = function(){
      setwd("mydirectory")
      fulldata <- read_excel("NoFines.xlsx")
      finesdata <- read_excel("Model_Param.xlsx")
      fulldata <- data.frame(fulldata)
      finesdata <- data.frame(finesdata)

      fulldata$FinesPerc <- NULL
      fulldata$FinesDirectT <- NULL

      return(fulldata)
      return(finesdata)
    }  ##end of ETL function

    PolyFunct = function(fulldata,finesdata){

      library(caret)
      library(leaps)
      library(MASS)
      library(DMwR)

      mydata1 <- fulldata
      mydata2 <- finesdata

      mydata1$Comments <- NULL
      mydata1$Date <- NULL

      mydata2$Comments <- NULL
      mydata2$Date <- NULL
      ggpairs(mydata2)
      #polynomial  
      PolyMod <- lm(mydata2$Recovery ~ 
      polym(mydata2$007T,mydata2$007G,mydata2$FinesPerc, degree=2, raw=FALSE))
      summary(PolyMod)
      par(mfrow=c(2,2)) # init 4 charts in 1 panel
      plot(PolyMod)

      save(PolyMod , file = 'PolyRegression2.rda')
      return(PolyMod)
    }

    ETL()
    PolyFunct(fulldata,finesdata)
    ```
    #setwd("mydirectory")
    #load("PolyRegression.rda")   # Load saved model

    #source("PolyOnly.R")


    library(shiny)

    shinyServer(function(input, output) {

      options(shiny.maxRequestSize = 800*1024^2) 

      output$sample_input_data_heading = renderUI({   # show only if data has 
      been uploaded
        inFile <- input$file1

        if (is.null(inFile)){
          return(NULL)
        }else{
          tags$h4('Sample data')
        }
      }) #end show data upload

      output$sample_input_data = renderTable({    # show sample of uploaded data
        inFile <- input$file1

        if (is.null(inFile)){
          return(NULL)
        }else{
          input_data =  readr::read_csv(input$file1$datapath, col_names = TRUE)

          colnames(input_data) = c("007T","007G","FinesPerc")


          head(input_data)
        }
      }) #end show sample of uploaded data

      predictions<-reactive({
        load("PolyRegression.rda")   # Load saved model
        source("PolyFunct.R",encoding="utf-8",local = TRUE)


        inFile <- input$file1

        if (is.null(inFile)){
          return(NULL)
        }else{
          withProgress(message = 'Predictions in progress. Please wait ...', {
            input_data =  readr::read_csv(input$file1$datapath, col_names = TRUE)

            colnames(input_data) = c("007T","C007G","FinesPerc")

            input_data$Recovery = predict(PolyMod, input_data)

          })
          }

      })## end of predictions


      output$sample_prediction_heading = renderUI({  # show only if data has been uploaded
        inFile <- input$file1

        if (is.null(inFile)){
          return(NULL)
        }else{
          tags$h4('Sample predictions')
        }
      }) ## end of sample prediction headings
       output$sample_predictions = renderTable({   # the last 6 rows to show
        pred = predictions()  ##call the reactive function above where predictions are made
        head(pred)
        })
        # Downloadable csv of predictions 

      output$downloadData <- downloadHandler(
        filename = function() {
          paste("input_data_with_predictions", ".csv", sep = "")
        },
        content = function(file) {
          write.csv(predictions(), file, row.names = FALSE)
        })
    })

在另一个脚本中使用预先存在的回归模型时，如何修复RShiny中的错误代码

0 个答案: