R 如何在一个闪亮的应用程序中汇总来自渲染函数外部的反应数据？

对于这个特别的闪亮的例子，我尝试应用一个循环模型，并在ggplot和汇总表中显示和汇总它。在尝试添加反应式“刷图”功能之前，这是很简单的。每个数据点代表一个日期，选择图的点是能够丢弃不需要的日期。据我所知，这要求过滤和模型拟合在

渲染图

中，这会导致复杂（无法找到数据/模型）尝试调用过滤后的数据和循环模型的统计输出（在函数外部和/或在另一个反应函数内）。这会产生

错误：找不到对象“k_circ.lm”

，因此我的问题是：

如何从

renderPlot

函数中读取过滤后的数据 到

汇总表

矩阵

我如何同样地添加

k_circ.lm

中的拟合模型值和残差

有没有更好或更简单的方法来安排应用程序来避免这种情况

工作（如果格式不好）汇总表的可选代码行被注释掉

library(dplyr)           # For data manipulation
library(ggplot2)         # For drawing plots
library(shiny)           # For running the app
library(plotly)          # For data manipulation         
library(circular)        # For Circular regressions
library(gridExtra)

# Define UI ----
ui <- fluidPage(

  # App title ----
  titlePanel("Circular Brushplot Demo"),

  # Sidebar layout with input and output definitions ----
  sidebarLayout(
    sidebarPanel(
      actionButton("exclude_toggle", "Toggle points"),
      actionButton("exclude_reset", "Reset")
    ),


  # Main panel for displaying outputs ----
  mainPanel(

      #reactive plot output with point and 'brush' selection
      fluidRow(plotOutput("k", height = 400,
                          click = "k_click",
                          brush = brushOpts(
                            id = "k_brush" ))),
      plotOutput("s", height = 400)
    )
  )
)

# Define server logic 
server <- function(input, output) {

  psideg <- c(356,97,211,232,343,292,157,302,335,302,324,85,324,340,157,238,254,146,232,122,329)
  thetadeg <- c(119,162,221,259,270,29,97,292,40,313,94,45,47,108,221,270,119,248,270,45,23)

  ## Data in radians then to "circular format"
  psirad <- psideg*2*pi/360
  thetarad <- thetadeg*2*pi/360
  cpsirad <- circular(psirad)
  cthetarad <- circular(thetarad)
  cdat <- data.frame(cpsirad, cthetarad)



  ###### reactive brush plot ########
  # For storing which rows have been excluded
  vals <- reactiveValues(
    keeprows = rep(TRUE, nrow(cdat)))

  output$k <- renderPlot({
    # Plot the kept and excluded points as two separate data sets
    keep    <- cdat[ vals$keeprows, , drop = FALSE]
    exclude <- cdat[!vals$keeprows, , drop = FALSE]

    ## Fits circular model specifically for 'keeprows' of selected data
    k_circlm <- lm.circular(type = "c-c", y = keep$cthetarad, x = keep$cpsirad, order = 1)

    k_circlm

    ggplot(keep, aes(cthetarad, cpsirad)) + 
      geom_point(aes(cthetarad, cpsirad, colour = keep$Vmag, size = 5))+
      scale_colour_gradient(low ="blue", high = "red")+
      geom_smooth(method = lm, fullrange = TRUE, color = "black") +
      geom_point(data = exclude, shape = 13, size = 5, fill = NA, color = "black", alpha = 0.25) +
      annotate("text", x = min(keep$cthetarad), y = Inf, hjust = .1, vjust = 1, 
               label = paste0("p value 1 = ", round(k_circlm$p.values[1], 2)), size = 7)+
      annotate("text", x = min(keep$cthetarad), y = Inf, hjust = .1, vjust = 2.5, 
               label = paste0("p value 2 = ", round(k_circlm$p.values[2], 2)), size = 7)+
      annotate("text", x = min(keep$cthetarad), y = Inf, hjust = .1, vjust = 4, 
               label = paste0("rho = ", round(k_circlm$rho, 2)), size = 7)+
      xlab("Lighthouse Direction (radians)")+ ylab("ADCP site direction (radians)")+
      theme(axis.title.x = element_text(size = 20), axis.title.y = element_text(size = 20))
  })

  # Toggle points that are clicked
  observeEvent(input$k_click, {
    res <- nearPoints(cdat, input$k_click, allRows = TRUE)

    vals$keeprows <- xor(vals$keeprows, res$selected_)})

  # Toggle points that are brushed, when button is clicked
  observeEvent(input$exclude_toggle, {
    res <- brushedPoints(cdat, input$k_brush, allRows = TRUE)

    vals$keeprows <- xor(vals$keeprows, res$selected_)})

  # Reset all points
  observeEvent(input$exclude_reset, {
    vals$keeprows <- rep(TRUE, nrow(cdat))})

  output$s <- renderPlot({

    # Create Summary table
    summarytable <- data.frame(matrix(ncol = 4, nrow = nrow(keep)))
    colnames(summarytable) <- c(  "Psi_dir", "Theta_dir", "Fitted_values", "Residuals")

    # Un-comment lines below to read from non-reactive data for working summary table
    #summarytable$Psi_dir <- round(cdat$cpsirad, 2)
    #summarytable$Theta_dir <- round(cdat$cthetarad, 2)

    # attempting to pull from circlm within render plot
    # comment out for summarytable to work
    summarytable$Psi_dir <- round(keep$cpsirad, 2)
    summarytable$Theta_dir <- round(keep$cthetarad, 2)
    summarytable$Fitted_values <- round(k_circ.lm$fitted)
    summarytable$Residuals <- round(k_circ.lm$residuals)

    # outputing table with minimal formatting 
    summarytable <-na.omit(summarytable)
    t <- tableGrob(summarytable)
    Q <- grid.arrange(t, nrow = 1)
    Q

    }
  )
}

shinyApp(ui = ui, server = server)

library（dplyr）#用于数据操作
图库（ggplot2）#用于绘制绘图
库（闪亮）#用于运行应用程序
库（plotly）#用于数据操作
图书馆（循环）#用于循环回归
图书馆（gridExtra）
#定义用户界面----
ui这里有一些想法-但是有多种方法来处理这个问题，在进一步处理这个问题之后，您可能希望重新构造
服务器的功能

首先，您可能需要一个
reactive
表达式，该表达式将根据
vals$keeprows
更新您的模型，因为它会随着您的单击而更改。然后，您可以从绘图和数据表访问此表达式的模型结果

以下是一个例子：

  fit_model <- reactive({
    ## Keep and exclude based on reactive value keeprows
    keep = cdat[ vals$keeprows, , drop = FALSE]
    exclude = cdat[!vals$keeprows, , drop = FALSE]

    ## Fits circular model specifically for 'keeprows' of selected data
    k_circlm <- lm.circular(type = "c-c", y = keep$cthetarad, x = keep$cpsirad, order = 1)

    ## Returns list of items including what to keep, exclude, and model
    list(k_circlm = k_circlm, keep = keep, exclude = exclude)
  })

并且可以从表中访问相同的内容（尽管您有as
renderPlot
？）：

output$s谢谢您的帮助，功能不错！您的回答也是正确的，因为我想使用
nrow（keep）
，所以我会相应地更改它。
output$s
的
renderPlot
可能不是最好的方法，但与我试图为其构建可复制演示的大型应用程序最为相似。。。您如何建议以不同的方式进行渲染？
  output$k <- renderPlot({

    exclude <- fit_model()[["exclude"]]
    keep <- fit_model()[["keep"]]
    k_circlm <- fit_model()[["k_circlm"]]

    ggplot(keep, aes(cthetarad, cpsirad)) + 
    ...

  output$s <- renderPlot({
    keep = fit_model()[["keep"]]
    k_circ.lm <- fit_model()[["k_circlm"]]

    # Create Summary table
    summarytable <- data.frame(matrix(ncol = 4, nrow = nrow(keep)))
    ...