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r - 发布到 Web 时闪亮主面板出错

问题描述

我正在为当前项目发布一个闪亮的应用程序，虽然它在本地运行没有错误，但当它发布到 shinyapps.io 时，我得到一个一般错误（'发生错误'）。

我试过调整绘图边距，摆弄代码和调试。

可以在此处找到源数据：[编辑 - 已删除源数据]

shinyapps 日志：https ://ctxt.io/2/AABA5KQDFA

可以在这里找到 Shiny 应用程序：https ://arcaravaggi.shinyapps.io/exploration_app/


library(shiny)
library(markdown)
library(dplyr)
library(lubridate)
library(ggplot2)

pdat <- read.csv("data/all_data.csv")
pdat <- pdat[order(pdat$species),]
pdat$visit_date <- as.Date(pdat$visit_date, format="%d/%m/%Y")
sp.nam <- unique(pdat$species)

pdat2 <- pdat %>%  group_by(species) %>%  filter(n() > 16) # Only include species with >16 records (power analysis - 0.95 power, 0.01 significance, r = 0.8)
pdat2$visit_date <- as.Date(pdat2$visit_date, format="%d/%m/%Y")

# Dataframe for summary data
pdat3 <- pdat %>%  group_by(species) %>% summarize(
  Count = length(species),
  Male = length(sex[sex == "M"]),
  Female = length(sex[sex == "F"]),
  Weight_m = round(mean(weight, na.rm=TRUE),1),
  Weight_SD = round(sd(weight, na.rm=TRUE),1),
  Wing_m = round(mean(wing, na.rm=TRUE),1),
  Wing_SD = round(sd(wing, na.rm=TRUE),1),
  Max_t_m = round(mean(max_t, na.rm=TRUE),1),
  Max_t_SD = round(sd(max_t, na.rm=TRUE),1),
  Min_t_m = round(mean(min_t, na.rm=TRUE),1),
  Min_t_SD = round(sd(min_t, na.rm=TRUE),1)
)

names(pdat3)[1] <- "Species"

ui <- navbarPage("Passerine biometrics",
                 tabPanel("Correlation plot",
                          sidebarLayout(
                            sidebarPanel(
                              h4("Subsetted to only include species with more than 16 records."),
                              selectInput('var', 'Species', unique(pdat2$species),
                                          selected = unique(pdat2$species)[[1]]),
                              selectInput('xcol', 'X variable', names(pdat2)[c(8:11)], 
                                          selected = names(pdat2)[10]),
                              selectInput('ycol', 'Y variable', names(pdat2)[c(8:11)],
                                          selected = names(pdat2)[11]),
                              hr(),
                              helpText("Wing, weight and tarsus measurements for passerine species collected as part of an ongoing study.")
                            ),
                            mainPanel(
                              plotOutput('plot1'),
                              textOutput('count'),
                              textOutput("correlation")
                            )
                          )
                 ),
                 tabPanel("Resampling",
                          sidebarLayout(
                            sidebarPanel(
                              h4("Variance in tarsus measurements"),
                              selectInput('sp', 'Species', unique(pdat2$species),
                                          selected = unique(pdat2$species)[[1]]),
                              actionButton("update", "Update"),
                              sliderInput(inputId = 'max_grp',
                                          label = "Maximum group size:",
                                          min = 5, max = 250,value = 16),
                              sliderInput(inputId = 'reps',
                                          label = "Number of iterations:",
                                          min = 1, max = 100, value = 10),
                              hr(),
                              helpText("Mean & SD R^2 for a given species, based on minimum and maximum tarsus measurements. Data are randomly resampled-with-replacement, across X individuals ('group size') and Y iterations. Data are cleaned prior to processing - outliers are identified according to Tukey's 1.5*IQR threshold applied to the interaction between minimum and maximum tarsus measurements.")
                              ),
                          mainPanel(
                              plotOutput('plot2')
                              )
                            )
                          ),
                 tabPanel("Summary data",
                          sidebarLayout(
                            sidebarPanel(
                              checkboxGroupInput("show_vars", label = "Columns to show:",
                                                 choices = names(pdat3), selected = names(pdat3)),
                              hr(),
                              helpText("m = mean; SD = standard deviation.")
                            ),
                            mainPanel(
                              DT::dataTableOutput("summary")
                            )
                          )
                 ),
                 tabPanel("Raw data",
                          DT::dataTableOutput("raw")
                 )
)


server <- function(input, output, session) {

  selectedData <- reactive({
    a <- subset(pdat2, pdat2$species %in% input$var)
    a <- droplevels(a)
    a <- a[, c(input$xcol, input$ycol)]
    names(a) <- c("x", "y")
    a <- a[complete.cases(a), ]
  })

  selectedData2 <- reactive({
    a <- subset(pdat2, pdat2$species %in% input$sp)
    a <- droplevels(a)
    a$temp <- a$min_t*a$max_t
    })

  pTResample <- function(df, mi = 1, ma = input$max_grp){
    outlierKD <- function(dt, var) {
      var_name <- eval(substitute(var),eval(dt))
      na1 <- sum(is.na(var_name))
      m1 <- mean(var_name, na.rm = T)
      outlier <- boxplot.stats(var_name)$out
      mo <- mean(outlier)
      var_name <- ifelse(var_name %in% outlier, NA, var_name)
      na2 <- sum(is.na(var_name))
      m2 <- mean(var_name, na.rm = T)
      dt[as.character(substitute(var))] <- invisible(var_name)
      assign(as.character(as.list(match.call())$dt), dt, envir = .GlobalEnv)
      dt <- dt[complete.cases(dt),] # data frame minus outliers
      return(invisible(dt))
    }
    b <- outlierKD(a, temp)
    b$temp <- NULL
    grpResample <- function(f, v1, v2){
      d <- data.frame(groupsize = c(mi:ma), s = NA)
      for(i in nrow(d)){
        for(i in mi:ma){
          a <- f[sample(x = 1:nrow(f), size = i, replace = T), ]
          d$s[i] <- cor(a$min_t,a$max_t)^2
        }
        return(d)
      }
    }
    r <- replicate(input$reps, grpResample(b))
    d <- data.frame(t((matrix(unlist(r), nrow=length(r), byrow=T))))
    d <- d[,seq(2,ncol(d),2)]
    w <- d %>% mutate(avg = apply(.,1,mean),
                      sd = apply(.,1,sd))
    w$groupsize <- c(mi:ma)
    w[is.na(w)] <- 0
    return(w)
  }

  selectedData3 <- reactive({
    input$update
    tmp <- pTResample(selectedData2())
  })

  output$plot1 <- renderPlot({
    par(mar = c(5.1, 4.1, 0, 1))
    ggplot(selectedData(), aes(x=x, y=y)) + 
      stat_smooth(method=lm, fullrange=FALSE) + 
      geom_point()
  })


  output$plot2 <- renderPlot({
    par(mar = c(5.1, 4.1, 3, 3))
    ggplot(selectedData3(), aes(x = groupsize, y = avg)) +
      geom_point(size = 2) +
      geom_errorbar(aes(ymin = avg-sd, ymax = avg+sd)) + 
      geom_smooth()
  })


  output$count <- renderText({
    paste("Count (n) = ", count(selectedData()))
  })

  output$correlation <- renderText({
    paste("Correlation (R) = ", round(cor(selectedData()$x,selectedData()$y),2))
  })


  output$summary <- DT::renderDataTable({
    DT::datatable(pdat3[, input$show_vars, drop = FALSE])
  })

  output$raw <- DT::renderDataTable({
    DT::datatable(pdat)
  })
}

shinyApp(ui, server)

我期望在第二个选项卡“重采样”上绘制一个 avg ~ groupize 的图，其中 groupsize 变量并取决于幻灯片输入。相反，主面板包含错误“发生错误。检查您的日志或联系应用作者进行澄清。

更新 [08/08/19 16:12]

按照凯利的建议，我重新命名了这个t论点，这似乎有所帮助。但是当我清理环境时，我仍然遇到了问题。在我的本地机器上逐个加载内容，看起来 selectedData2 和 selectedData3 之间存在问题。如果我手动加载数据框a，那么它可以工作。如果环境很清楚，那么我会收到一个关闭错误。

在我的编辑之后，我已经更新了上面的代码。

最新日志：

2019-08-08T15:18:43.544466+00:00 shinyapps[631266]: Warning: Error in eval: invalid 'envir' argument of type 'closure'
2019-08-08T15:18:43.554480+00:00 shinyapps[631266]:   199: outlierKD [/srv/connect/apps/exploration_app/app.R#112]
2019-08-08T15:18:43.554481+00:00 shinyapps[631266]:   198: pTResample [/srv/connect/apps/exploration_app/app.R#125]
2019-08-08T15:18:43.554482+00:00 shinyapps[631266]:   197: <reactive:selectedData3> [/srv/connect/apps/exploration_app/app.R#148]
2019-08-08T15:18:43.554478+00:00 shinyapps[631266]:   200: eval
2019-08-08T15:18:43.554483+00:00 shinyapps[631266]:   195: .func
2019-08-08T15:18:43.554484+00:00 shinyapps[631266]:   192: contextFunc
2019-08-08T15:18:43.554485+00:00 shinyapps[631266]:   191: env$runWith
2019-08-08T15:18:43.554485+00:00 shinyapps[631266]:   184: ctx$run
2019-08-08T15:18:43.554486+00:00 shinyapps[631266]:   183: self$.updateValue
2019-08-08T15:18:43.554489+00:00 shinyapps[631266]:   137: drawPlot
2019-08-08T15:18:43.554487+00:00 shinyapps[631266]:   181: selectedData3
2019-08-08T15:18:43.554488+00:00 shinyapps[631266]:   179: renderPlot [/srv/connect/apps/exploration_app/app.R#161]
2019-08-08T15:18:43.554489+00:00 shinyapps[631266]:   177: func
2019-08-08T15:18:43.554490+00:00 shinyapps[631266]:   123: <reactive:plotObj>
2019-08-08T15:18:43.554491+00:00 shinyapps[631266]:   107: drawReactive
2019-08-08T15:18:43.554518+00:00 shinyapps[631266]:    94: origRenderFunc
2019-08-08T15:18:43.554519+00:00 shinyapps[631266]:    93: output$plot2
2019-08-08T15:18:43.554521+00:00 shinyapps[631266]:    13: runApp
2019-08-08T15:18:43.554522+00:00 shinyapps[631266]:    12: fn
2019-08-08T15:18:43.554522+00:00 shinyapps[631266]:     7: connect$retry
2019-08-08T15:18:43.554523+00:00 shinyapps[631266]:     6: eval
2019-08-08T15:18:43.554524+00:00 shinyapps[631266]:     5: eval

更新 [08/08/2019 16:50]

解决它。我删除了 selectedData2 并将创建嵌套a在 selectedData3 中。然后我将 pTResample 函数应用于 pdat2，而不是 selectedData2

标签： rshinyshinyapps

解决方案

[OP 的错误日志，在推特上分享：https://ctxt.io/2/AABA5KQDFA]

我认为问题在这里发生：

var_name <- eval(substitute(var),eval(dt))

“eval”的第二个参数应该是一个环境。你在这里调用父函数：

b <- outlierKD(a, t)

我没有t在任何地方看到定义，所以大概它正在尝试使用转置功能t()。

因此，您的日志中出现错误：

警告：eval 中的错误：“closure”类型的“envir”参数无效

eval()was的第二个参数t()，它是一个函数（或闭包）。

（这是样式指南通常建议不使用短变量名的原因之一——它们与函数冲突并导致关于“闭包”的混淆错误！）

在您的家用计算机上，您可能已经t在之前的测试中正确定义了您的环境，因此它当时没有抛出错误。

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