Question

我正在尝试使用Shiny为线性和多元回归编写应用程序，但多个条件面板存在问题，

那个

它不检查条件，并执行第一个条件面板。

这不是一个单一的问题，它也无法读取文件，并保持所选第一个条件面板的状态。

library(shiny)    
# Define UI for application that draws a histogram
  ui <- fluidPage(

 # # Application title
 # column(9,
 #   titlePanel("Multiple Regression")
 #   
 #   ),


 sidebarLayout(
    sidebarPanel(
       selectInput("sel_type",
                   "Select Regression Type ",
                   c("Linear Regression"="LR","Multiple Regression"="MR"),
                   selected = "LR"),
       fileInput("file1", "Choose CSV File",
                 accept = c(
                   "text/csv",
                   "text/comma-separated-values,text/plain",
                   ".csv")
       ),
       uiOutput("select_predict"),
       conditionalPanel(
         condition = "input.sel_type=='LR'",
         uiOutput("select_test")  
       )

    ),

    mainPanel(
       conditionalPanel(
         condition = "input.sel_type=='LR'",
         h1("Simple Linear Regression"),
         br(),
         h3(textOutput("scat_plot"))
          ,plotOutput("scatter_plot",width = 500, height = 500),
         br(),
         # verbatimTextOutput("dataSet"),
         h3("Data Set"),
         br(),
         column(4,
                h4("Test variable"),
                tableOutput("tbl1"),
                offset = 1
         ),
         h4("Predicting variable"),
         tableOutput("tbl"),
         br(),
         h3("correlation analysis"),
         verbatimTextOutput("cor"),
         br(),
         h3("Linear model and Regression Analysis"),
         br(),
         verbatimTextOutput("lm_ra"),
         br(),
         uiOutput("predict"),
         br(),
         verbatimTextOutput("predicted_value")
         ),

       conditionalPanel(
         condition = "input.sel_type == 'MR' ",
          h1("Multiple Regression"),
          br(),
         verbatimTextOutput("summary"),
          h2("COrrelation Analysis"),          
          br(),
          verbatimTextOutput("cor")
       )
    )
 )
)

# Define server logic required to draw a histogram
  server <- function(input, output) {

# sample1 <- read.csv(input$file1$datapath)

output$select_predict = renderUI({
  df <- read.csv(input$file1$datapath)
  selectInput("sel_test_var","Select Test variable",choices =  names(df))
})

output$select_test = renderUI({
  df <- read.csv(input$file1$datapath)
  selectInput("ip2","Select Predicting Variable",names(df)[!names(df)==input$sel_test_var])#,multiple = T)

})

output$scat_plot = renderText({
  sprintf(
    "Scatter plot between '%s' and '%s'", input$sel_test_var, input$ip2
  )

})
output$scatter_plot = renderPlot({
  df <- read.csv(input$file1$datapath)
  x<- df[,input$sel_test_var]
  y<- df[,input$ip2]

 if (!is.null(y)) {
  plot(x,y,xlab=input$sel_test_var, ylab=input$ip2)
  abline(lm(y~x))
  }
    })
# output$dataSet = renderPrint({
#   df <- read.csv(input$file1$datapath)
#   sprintf("Data of %s",input$sel_test_var)
#   df[,input$sel_test_var]
# #  sprintf("Data of %s",input$ip2)
#  #   df[,input$ip2]
# })


output$tbl = renderTable({
  df <- read.csv(input$file1$datapath)
  z <- as.data.frame(df[,input$ip2])
  names(z) <- input$ip2
  z
})
output$tbl1 = renderTable({
  df <- read.csv(input$file1$datapath)
  z <- as.data.frame(df[,input$sel_test_var])
  names(z) <- input$sel_test_var
  z
})
 output$cor=renderPrint({
 df <- read.csv(input$file1$datapath)
 result <- cor.test(df[,input$ip2],df[,input$sel_test_var],method = "pearson")
 result
 }) 
 output$lm_ra = renderPrint({
 df <- read.csv(input$file1$datapath)
 model1 <- lm(df[,input$sel_test_var] ~ df[,input$ip2])
 model1
 #sprintf("Summury linear model")
 cat(sprintf("Model summary"))
 summary(model1)
 })

    output$predict = renderUI({

   numericInput(inputId = "predict_value",label = "Enter Predicting value",value = 10)
 })

 output$predicted_value = renderPrint({
 df <- read.csv(input$file1$datapath)
 x <- df[,input$ip2]
 model1 <- lm(df[,input$sel_test_var] ~ x)
 y=predict(model1,data.frame(x = input$predict_value),interval = "confidence", level=0.95)
 y
 })

 ########################## Multiple Regression #################################

 output$summary = renderPrint({
 df <- read.csv(input$file1$datapath)
 cat(paste("Structure of Data Set\n"))
    str(df)
 #cat(paste("\n\n"))
 # cat(paste("Dimension of Data Set\n"))
 #  dim(df)
  cat(paste("\n\n"))
 cat(paste("Summary of Data Set\n"))
  summary(df)
 })

 output$cor = renderPrint({
 df <- read.csv(input$file1$datapath)
 cor(df)
 })

}




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

预先感谢您！

有光泽：主面板中的多个条件面板不起作用

0 个答案: