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从Shiny,Plotly-R中提取所有点击事件图

[英]Extract all click event plots from Shiny, Plotly - R

在下面的shiny应用程序中, plotly包用于创建交互式相关热图。 单击单个图块时,将显示相应的散点图。 然后,可以通过单击download plot as pngdownload plot as png单个download plot as png 但有没有办法一次下载所有可能的散点图而不必点击每个单独的瓷砖并保存每个单独的瓷砖? 谢谢

library(plotly)
library(shiny)

# compute a correlation matrix
correlation <- round(cor(mtcars), 3)
nms <- names(mtcars)

ui <- fluidPage(
  mainPanel(
    plotlyOutput("heat"),
    plotlyOutput("scatterplot")
  ),
  verbatimTextOutput("selection")
)

server <- function(input, output, session) {
  output$heat <- renderPlotly({
    plot_ly(x = nms, y = nms, z = correlation, 
            key = correlation, type = "heatmap", source = "heatplot") %>%
      layout(xaxis = list(title = ""), 
             yaxis = list(title = ""))
  })

  output$selection <- renderPrint({
    s <- event_data("plotly_click")
    if (length(s) == 0) {
      "Click on a cell in the heatmap to display a scatterplot"
    } else {
      cat("You selected: \n\n")
      as.list(s)
    }
  })

  output$scatterplot <- renderPlotly({
    s <- event_data("plotly_click", source = "heatplot")
    if (length(s)) {
      vars <- c(s[["x"]], s[["y"]])
      d <- setNames(mtcars[vars], c("x", "y"))
      yhat <- fitted(lm(y ~ x, data = d))
      plot_ly(d, x = ~x) %>%
        add_markers(y = ~y) %>%
        add_lines(y = ~yhat) %>%
        layout(xaxis = list(title = s[["x"]]), 
               yaxis = list(title = s[["y"]]), 
               showlegend = FALSE)
    } else {
      plotly_empty()
    }
  })

}

shinyApp(ui, server)

您可以使用webshot使用webshot说明捕获Plotly的HTML输出的静态图像: https ://plot.ly/r/static-image-export/

下面循环的示例生成来自mtcars随机散点图。

library(plotly)
library(webshot)

## You'll need to run the function the first time if you dont't have phantomjs installed
#webshot::install_phantomjs()
ColumnOptions <- colnames(mtcars)

for (i in seq_len(5)){
  xCol <- sample(ColumnOptions,1)
  yCol <- sample(ColumnOptions,1)
  ThisFileName <- paste0("Scatter_",xCol,"_vs_",yCol,".png")

  plot_ly(x = mtcars[[xCol]], y = mtcars[[yCol]], type = "scatter", mode = "markers") %>% 
    export(., file = ThisFileName)
}

但是,如果您可能会执行此操作数十次,则执行以下步骤所需的计算量确实会增加。

  1. R生成JSON plotly对象
  2. 使用htmlwidgets / htmltools生成一个自包含的HTML网页
  3. 将HTML作为浏览器呈现为外部程序 - webshot
  4. 使用webshot呈现该HTML的图像并将其另存为PNG

这并不是plotly缓慢的反映,但作为一个类比,它有点像使用飞机旅行半英里 - 飞机让你到达那里,但如果你需要让这次旅行超过一些你应该考虑一辆车。

上面的plotly循环需要27秒来渲染5个PNG图像,但下面使用ggplot2的替代方法需要1.2秒。

library(ggplot2)

ColumnOptions <- colnames(mtcars)

for (i in seq_len(5)){
  xCol <- sample(ColumnOptions,1)
  yCol <- sample(ColumnOptions,1)
  ThisFileName <- paste0("ggplot2_Scatter_",xCol,"_vs_",yCol,".png")

  ggplot() + 
    geom_point(aes(x = mtcars[[xCol]], y = mtcars[[yCol]])) +
    labs(x = xCol, y = yCol) -> ThisPlot 

  ggsave(plot = ThisPlot, filename = ThisFileName)
}

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