我正在尝试模拟Shiny中的Polya urn模型，因此用户可以输入urn包含的黑白球数量，他想要多少次迭代和试验，然后情节将显示每个试验如何进行，以瓮中白球的比例 .

这是我第一次使用Shiny，我想出了如何使用程序的核心，即如何使用户能够设置变量，如何打印出我使用的矩阵表（我不需要，只是试了一下） .

这是我的Shiny代码（没有任何输出）：

library(shiny)
library(plotly)
library(ggplot2)
library(reshape2)

################ UI
ui <- fluidPage(
  # App title 
  titlePanel("Hello Shiny!"),
  ###### this following part is asking the user for input

  # input for the number of black balls
  numericInput(inputId = "BB", label = "Number of black balls", 1, min = 1, max = 500),
  # input for the number of white balls
  numericInput(inputId = "WB", label= "Number of white balls", 1, min = 1, max = 500),
  # input for the number of iterations
  numericInput(inputId = "nIt", label= "Number of iterations", 50, min = 5, max = 500),
  # input for the number of runs/trials
  numericInput(inputId = "nRun", label= "Number of runs", 10, min = 1, max = 50),
  # slider for the number of BBs as feedback
  sliderInput(inputId = "BBfeedback", label = "BB Feedback", 1, min = 1, max = 10),
  # slider for the number of WBs as feedback
  sliderInput(inputId = "WBfeedback", label = "WB Feedback", 1, min = 1, max = 10),

  # reserve a spot for the output
  plotOutput(outputId = "mainPlot")  
)

################ SERVER
server <- function(input, output) {

  # PLOT
  output$mainPlot <-  renderPlot({
    plot() # this is the code for plotting what i want to plot

  })

}

################  SHINYAPP
shinyApp(ui = ui, server = server)

这是我的代码 - 它在R中运行没有问题 . 它是一个嵌套的for循环，它根据输入值创建一个矩阵，然后绘制结果 . 我的问题是：我应该在哪里放置嵌套的for循环？当我把它放在renderPlot部分时，它不起作用 .

M <- matrix(ncol=input$nRun, nrow=input$nIt) # matrix that will contain the proportion of WBs per each iteration (=rows) and run (=cols)

urn <- c(rep("BB", input$BB), rep("WB", input$WB)) # put together the urn based on previous input of BB and WB
    for (r in 1:input$nRun) { # loop through number of runs/trials
      # same as the initial BB and WB number but it will change as we draw balls from the urn
      nBlack <- input$BB # this is important so that for each run, the previous run's results won't mess with the proportions 
      nWhite <- input$WB 
      # iterate thgourh the runs and iterations, fill up the matrix with the proportion of white balls
      frac <- nWhite/(nBlack+nWhite) # this variable shows the proportion of white balls in the urn overall
      frac_list <- c() # contains the proportion of WBs in a vector thorughout the iterations
      for (i in 1:nIt){  # loop thourgh number of internvals (so for each run R calculates the whole interval one after the other)
        s <- sample(urn, 1) # sample one ball randomly from the urn
        if (s == "WB"){  
          nWhite <- nWhite + WB_feedback # update the number of WB
        }else {
          nBlack <- nBlack + BB_feedback # update the number of BB in case the sampled ball is black
        }
        urn <- append(urn, s, after = length(urn)) # put the last sampled ball into the urn (NOTE: since the sample s doesn't actually 'take out' the ball from the urn, there is no need to add an additional ball)
        frac <- nWhite/(nWhite+nBlack) # update frac to get the proportion of white balls in this run
        frac_list <- append(frac_list, frac)
      }

      M[,r] <- frac_list
    }

这是将矩阵转换为数据帧并使用ggplot绘制结果的代码 . 这个部分应该与嵌套的for循环一起使用，还是在renderPlot部分中？

df <- as.data.frame(M) #transform matrix into a data frame
    df$id = 1:nrow(df)
    final_data <- melt(df, id='id') # putting the data into long format
    names(final_data) <- c('id', 'func', 'value') # naming the columns so they can be used in the ggplot 
    g <- ggplot() + geom_line(data = final_data, aes(x = id, y = value, color = func, group = func), size = 1) # MAKES THE GRAPH
    ggplotly(g) # plotlify the ggplot
r shiny