Question

我正在构建一个应用程序，以便更好地理解对数正态分布和正态分布的差异。应用程序应显示使用ggplot2模拟数据的直方图（正常或对数正态），并为假数据拟合正态，对数正态密度和核密度。由于某种原因，下面的应用程序不会显示ggplot2图表。

# Define UI for application that draws a histogram

library(shiny)
library(ggplot2)
library(stats)
library(gridExtra)


set.seed(15)

ui <- fluidPage(

   # Application title
   titlePanel("Curve fit with different distributions"),

   # Sidebar with a slider input for number of bins
   sidebarLayout(
      sidebarPanel(

         sliderInput("mean",
                     "Mean value:",
                     min = 1,
                     max = 250,
                     value = 10)
      ,
      sliderInput("spread",
                  "Standard deviation:",
                  min = 0,
                  max = 25,
                  step=0.1,
                  value = 2.5)
   ,
   sliderInput("n",
               "How many datapoints:",
               min = 10,
               max = 10000,
               value = 2500)
,
selectInput("dist",
"Which data distribution?" ,
list("Normal"="dnorm"  ,
                  "Lognormal"="dlnorm"
                  )
                  )),
      # Show a plot of the generated distribution
      mainPanel(

  plotOutput("distPlot",  height = "80%"))

  )
)

# Define server logic required to draw a histogram with normal and log normal density

server <- function(input, output) {

  sim_data<-reactive({
    if(is.null(input$dist) |is.null(input$spread) | is.null(input$mean)) { 
      return(NULL)
    }

    mlog<-log(input$mean )
    lspread <- log(input$spread)
     dat <-    data.frame(xn = rnorm(input$n, mean = input$mean, sd = input$spread), ln=rlnorm(input$n, meanlog =mlog , sdlog = lspread))
       return(dat)  
  })
  output$distPlot <- renderPlot({
    if(is.null(sim_data()) |is.null(input$dist) ){
      return(NULL)
    }
    # generate bins based on input$bins from ui.R


    if(input$dist == "dnorm"){
    hist_plot<- ggplot(sim_data(), aes(x = xn)) +
      geom_histogram(aes(y =..density..),

                     colour = "black",
                     fill = "white") +

      stat_function(fun = dnorm, colour ="#377EB8", args = list(mean = mymean, sd = mysd))+
      stat_function(fun = dlnorm, colour ="#E41A1C", args = list(mean =  mylmean, sd = mylsd))+
      geom_density(colour="black")+

      theme_minimal()
    } 
    else{ 
      hist_plot<- ggplot(sim_data(), aes(x = ln)) +
        geom_histogram(aes(y =..density..),

                       colour = "black",
                       fill = "white") +
        labs(title=distname) +
        theme_minimal()+
        stat_function(fun = dnorm, colour ="#377EB8", args = list(mean = mymean, sd = mysd))+
        stat_function(fun = dlnorm, colour ="#E41A1C", args = list(mean =  mylmean, sd = mylsd))+
        geom_density(colour="black")+
      theme_minimal() 
      }

    if(input$dist == "dnorm"){
        box_plot<- ggplot(sim_data(), aes(x="",y = xn)) +
          geom_boxplot()+      
          theme_minimal()
      }
        else{
          box_plot<- ggplot(sim_data(), aes(x="",y = ln)) +
            geom_boxplot(

            )+      
      theme_minimal()
        }


    p=grid.arrange(hist_plot+      
                     theme_minimal(),box_plot+      
                     theme_minimal(), ncol=1,nrow=2, heights = c(4,2))
    plot(p)


  })


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

Answer 1

嗨，你的问题在这里

plotOutput("distPlot",  height = "80%")

此刻你正在告诉情节80％的高度什么都没有。例如，将高度更改为400px，它将全部有效。

闪亮的注意到情节不是直观的，所以它甚至不能计算出那个时刻的情节。

R Shiny app ggplot2超时

1 个答案: