R Shiny 应用程序 ggplot2 超时答案

【问题标题】：R Shiny app ggplot2 times outR Shiny 应用程序 ggplot2 超时
【发布时间】：2018-01-05 14:32:26
【问题描述】：

我正在构建一个应用程序以更好地了解对数正态分布和正态分布的差异。该应用程序应使用 ggplot2 显示模拟数据（正态或对数正态）的直方图，并将正态、对数正态密度和内核密度拟合到假数据。出于某种原因，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)

【问题讨论】：

标签： r shiny

【解决方案1】：

您好，您的问题来了

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

现在你告诉情节的高度是什么都没有的 80%，什么都不是。例如，将高度更改为 400px 即可。

Shiny 注意到情节不是可视的，所以它甚至没有计算情节吃掉的那一刻。

【讨论】：