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如何在闪亮的应用程序中使用plotlyProxy（）与ggplotly（）来使绘图渲染更快

[英]How to use plotlyProxy() in shiny app with ggplotly() to make plots render faster

 原文  2018-12-04 14:01:52  4   1    r/ plotly/ r-plotly/ ggplotly

问题描述

我一直在寻找一个处理这个问题，但我没有看到任何问题。我正在创建一个闪亮的应用程序，它使用ggplotly()来使我的图形交互。 该图表基于用户selectInput()下拉菜单而被动。 一切正常，但是当我在下拉菜单中单击一个新参数时，绘图需要很长时间才能渲染。 通过查看本文，我发现了这篇文章， 改进ggplotly转换 ，这解释了为什么绘图需要很长时间才能渲染（我有很多数据）。 在网站上它说要使用plotlyProxy() 。 但是，我很难在我的代码中实现它。 更具体地说，我不明白如何使用必须plotlyProxyInvoke()一起使用的plotlyProxyInvoke()函数。 我非常感谢任何指导！

样本数据： 

  df<-structure(list(stdate = structure(c(17694, 14581, 14162, 14222, 
    17368, 16134, 17414, 13572, 17613, 15903, 14019, 12457, 15424, 
    13802, 12655, 14019, 16143, 17191, 13903, 12362, 12929, 13557, 
    16758, 13025, 15493, 16674, 15959, 15190, 16386, 11515, 12640, 
    15295, 15664, 15145, 17077, 14914, 14395, 14992, 13271, 12730
    ), class = "Date"), sttime = structure(c(35460, 42360, 32880, 
    30600, 26760, 45000, 36000, 32700, 39000, 35460, 34200, 28800, 
    26400, 33900, 39600, 29280, 34500, 28920, 31320, 34800, 37800, 
    42000, 34560, 27000, 35280, 37800, 36000, 32940, 30240, 42900, 
    28800, 35100, 35400, 39600, 30420, 41100, 34500, 32040, 37800, 
    36000), class = c("hms", "difftime"), units = "secs"), locid = c("BTMUA-SB1", 
    "BTMUA-INTAKE", "BTMUA-SA", "USGS-01394500", "BTMUA-NA", "USGS-01367785", 
    "NJDEP_BFBM-01411461", "BTMUA-SD", "NJDEP_BFBM-01443293", "BTMUA-SL", 
    "USGS-01396660", "USGS-01390400", "BTMUA-SA", "21NJDEP1-01407670", 
    "USGS-01477440", "BTMUA-NA", "BTMUA-SA", "BTMUA-SE", "BTMUA-SA", 
    "USGS-01405340", "USGS-01444990", "BTMUA-SG", "BTMUA-SB1", "USGS-01467359", 
    "BTMUA-SA", "USGS-01382000", "USGS-01412800", "BTMUA-NA", "BTMUA-SI", 
    "31DRBCSP-DRBCNJ0036", "21NJDEP1-01410230", "USGS-01465861", 
    "BTMUA-NF", "USGS-01445210", "BTMUA-NA", "USGS-01464020", "BTMUA-SL", 
    "BTMUA-SA", "USGS-01382500", "USGS-01408598"), charnam = c("Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids", 
    "Total dissolved solids", "Total dissolved solids", "Total dissolved solids"
    ), val = c(126, 84, 97, 392, 185, 157, 62, 149.4, 274, 60, 134, 
    516, 121, 144, 143, 99, 154, 120, 96, 99, 278, 96.2, 135, 101, 
    110, 460, 147, 117, 102, 250, 75, 121, 129, 242, 172, 279, 51, 
    205, 88, 38), valunit = c("mg/l", "mg/l", "mg/l", "mg/l", "mg/l", 
    "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", 
    "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", 
    "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", 
    "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", "mg/l", 
    "mg/l", "mg/l", "mg/l"), HUC14 = c("02040301030050", "02040301040020", 
    "02040301030050", "02030104050040", "02040301020050", "02020007020030", 
    "02040206130020", "02040301030050", "02040105040040", "02040301030010", 
    "02030105020030", "02030103140040", "02040301030050", "02030104090040", 
    "02040202160010", "02040301020050", "02040301030050", "02040301030040", 
    "02040301030050", "02030105140020", "02040105070040", "02040301030040", 
    "02040301030050", "02040202120010", "02040301030050", "02030103040010", 
    "02040206080040", "02040301020050", "02040301030030", "02040105050050", 
    "02040301200110", "02040202060040", "02040301020020", "02040105080020", 
    "02040301020050", "02040105240060", "02040301030010", "02040301030050", 
    "02030103050060", "02040301080050"), WMA = c("13", "13", "13", 
    "7", "13", "2", "17", "13", "1", "13", "8", "4", "13", "12", 
    "18", "13", "13", "13", "13", "9", "1", "13", "13", "18", "13", 
    "6", "17", "13", "13", "1", "14", "19", "13", "1", "13", "11", 
    "13", "13", "3", "13"), year = c(2018L, 2009L, 2008L, 2008L, 
    2017L, 2014L, 2017L, 2007L, 2018L, 2013L, 2008L, 2004L, 2012L, 
    2007L, 2004L, 2008L, 2014L, 2017L, 2008L, 2003L, 2005L, 2007L, 
    2015L, 2005L, 2012L, 2015L, 2013L, 2011L, 2014L, 2001L, 2004L, 
    2011L, 2012L, 2011L, 2016L, 2010L, 2009L, 2011L, 2006L, 2004L
    )), .Names = c("stdate", "sttime", "locid", "charnam", "val", 
    "valunit", "HUC14", "WMA", "year"), row.names = c(NA, -40L), class = c("tbl_df", 
    "tbl", "data.frame"))

UI 

library(shiny)
library(shinydashboard)
library(tidyverse)
library(plotly)

header<-dashboardHeader(title="test app")
sidebar<-dashboardSidebar(selectInput("huc","Please Select HUC14:",choices=df$HUC14,selected = df$HUC14))
body<- dashboardBody(plotlyOutput("plot"))

ui <- dashboardPage(header = header,
                   sidebar = sidebar,
                   body = body)

服务器： 

server<- function(input,output,session) {
  df_reac<-reactive({
    df%>%
      filter(HUC14 == input$huc)
  })

  output$plot<-renderPlotly({
    ggplot(df_reac(), aes(x = year, y = val)) +
      geom_point(aes(color="Discrete"),size=3) +
      geom_hline(aes(yintercept = 500,color="Freshwater Aquatic Life Criteria\nfor TDS = 500 mg/L"),size=1.3)+
      xlab("Year") + ylab(" TDS Concentration (mg/L)")})


  observeEvent(input$huc,{
    plotlyProxy("plot",session)%>%
      plotlyProxyInvoke("relayout")
  })
}

shinyApp(ui,server)

我实际使用的数据超过300,000次观察，而且应用程序要复杂得多......但我会用它来保持简短和甜蜜。 我希望这足以成为一个可重复的例子..如果不是，请告诉我！

1 个解决方案

解决方案1
 3 已采纳  2018-12-19 12:35:20

下面的shinyApp展示了如何使用plotlyProxyInvoke与方法relayout ， restyle ， addTraces ， deleteTraces和moveTraces 。

你没有真正的情节对象，因为你没有在ggplotly调用中包装ggplot对象。 我还包括了highlight_key函数，尽管这个例子并不是必需的。

  • 重新布局发生在你放大例如，这将改变标题和yaxis.range为0 - 500。你可以找到一个票友重新布局法在这里 。

  • 单击橙色点时会发生Restyle 1方法，这会将不透明度更改为0.1，将标记颜色更改为蓝色，将线条颜色更改为橙​​色。

  • 当您使用Box / Lasso-Select时，会发生Restyle 2 ，它会将不透明度更改为1，将标记颜色更改为红色，将线条颜色更改为蓝色。

  • 将鼠标悬停在点（或其他迹线）上时会发生AddTraces ，这将添加随机曲线。

  • 按钮单击（ delete ）时会发生DeleteTraces ，这将删除数据数组中的最后一个跟踪。

  • 按钮单击（ move ）时会发生MoveTraces ，这将更改索引为0和1的轨迹的顺序，并将它们附加到数据数组的末尾。

要查看可以调用的所有可用方法，请输入： 

plotly:::plotlyjs_methods()

[1] "restyle"       "relayout"      "update"        "addTraces"     "deleteTraces"  "moveTraces"    "extendTraces"  "prependTraces"               
[9] "purge"         "toImage"       "downloadImage" "animate"

有关进一步说明，请查看Plotly参考和此有光泽的App示例 。

ui.R 

library(shiny)
library(shinydashboard)
library(tidyverse)
library(plotly)

header<-dashboardHeader(title="test app")
sidebar<-dashboardSidebar(selectInput("huc","Please Select HUC14:",choices=df$HUC14,selected = df$HUC14),
                          actionButton("delete", "Delete the last trace"),
                          actionButton("move", " Move traces"))
body<- dashboardBody(plotlyOutput("plot"))

ui <- dashboardPage(header = header,
                   sidebar = sidebar,
                   body = body)

server.R 

server<- function(input,output,session) {
  df_reac<-reactive({
    df%>%
      filter(HUC14 == input$huc)
  })

  output$plot<-renderPlotly({
    key = highlight_key(df_reac())
    p <- ggplot(key, aes(x = year, y = val)) +
      geom_point(aes(color="Discrete"),size=3) +
      geom_hline(aes(yintercept = 500,color="Freshwater Aquatic Life Criteria\nfor TDS = 500 mg/L"),size=1.3)+
      xlab("Year") + ylab(" TDS Concentration (mg/L)")

    ggplotly(p)
  })

  observeEvent(event_data("plotly_relayout"), {
    print("relayout")
    plotlyProxy("plot", session) %>%
      plotlyProxyInvoke("relayout", list(title = 'New title', 
                                         yaxis.range = list(0,500)))
  })

  observeEvent(event_data("plotly_click"), {
    print("restyle 1")
    plotlyProxy("plot", session) %>%
      plotlyProxyInvoke("restyle", list(opacity=0.1, marker.color="blue", line.color="orange"))
  })

  observeEvent(event_data("plotly_selected"), {
    print("restyle 2")
    plotlyProxy("plot", session) %>%
      plotlyProxyInvoke("restyle", list(opacity=1, marker.color="red", line.color="blue"))
  })

  observeEvent(event_data("plotly_hover"), {
    print("addTraces")
    time = as.numeric(format(df_reac()$stdate, "%Y"))
    plotlyProxy("plot", session) %>%
      plotlyProxyInvoke("addTraces", list(y = as.list(sort(sample(100:500, 3, F))), 
                                          x = as.list(sort(sample(seq(time-0.05,time+0.05, by = 0.02), 3, F)))))
  })

  observeEvent(input$delete, {
    print("deleteTraces")
    plotlyProxy("plot", session) %>%
      plotlyProxyInvoke("deleteTraces", list(-1))
  })

  observeEvent(input$move, {
    print("moveTraces")
    plotlyProxy("plot", session) %>%
      plotlyProxyInvoke("moveTraces", list(0, 1))
  }) 

}

shinyApp(ui,server)

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