闪亮应用程序中的 renderImage() 和 .svg

Question

我没有让renderImage()使用 .svg 文件。 我的最小示例（adapted from the corresponding RStudio-tutorial）：

ui.R

shinyUI(pageWithSidebar(
  headerPanel("renderSVG example"),
  sidebarPanel(
    sliderInput("obs", "Number of observations:",
                min = 0, max = 1000,  value = 500),
    actionButton("savePlot", "savePlot")
  ),
  mainPanel(
    # Use imageOutput to place the image on the page
    imageOutput("plot"),
    imageOutput("plot_as_svg")
  )
))

服务器.R

require("ggplot2")
library(svglite)

shinyServer(function(input, output, session) {
  
  ## create plot with renderPlot() 
  

      output$plot<- renderPlot({
        hist(rnorm(input$obs), main="Generated in renderPlot()")
        })

  
  ## create .svg file of the plot and render it with renderImage() 
  
  output$plot_as_svg <- renderImage({
    # A temp file to save the output.
    # This file will be removed later by renderImage
    outfile <- tempfile(fileext='.svg')
    
    # Generate the svg
    svglite(outfile, width=400, height=300)
    hist(rnorm(input$obs), main="Generated in renderImage()")
    dev.off()
    
    # Return a list containing the filename
    list(src = outfile,
         contentType = 'text/svg+xml',
         width = 400,
         height = 300,
         alt = "This is alternate text")
  }, deleteFile = TRUE)
  
})

有什么想法吗？

Answer 1

我在同样的问题上苦苦挣扎，我发现网络上没有任何东西可以解决这个令人沮丧的问题。这是对我有用的解决方案：

ui.R:

shinyUI(pageWithSidebar(
  headerPanel("renderSVG example"),
  sidebarPanel(
    sliderInput("obs", "Number of observations:",
                min = 0, max = 1000,  value = 500),
    actionButton("savePlot", "savePlot")
  ),
  mainPanel(
    # Use imageOutput to place the image on the page
    imageOutput("plot"),
    imageOutput("plot_as_svg")
  )
))

server.R：

require("ggplot2")

shinyServer(function(input, output, session) {

  ## create plot with renderPlot()


      output$plot<- renderPlot({
        hist(rnorm(input$obs), main="Generated in renderPlot()")
        })


  ## create .svg file of the plot and render it with renderImage()

  output$plot_as_svg <- renderImage({

      width  <- session$clientData$output_plot_width
      height <- session$clientData$output_plot_height
      mysvgwidth <- width/96
      mysvgheight <- height/96

    # A temp file to save the output.
    # This file will be removed later by renderImage

    outfile <- tempfile(fileext='.svg')

    # Generate the svg
    svg(outfile, width=mysvgwidth, height=mysvgheight)
    hist(rnorm(input$obs), main="Generated in renderImage()")
    dev.off()

    # Return a list containing the filename
    list(src = normalizePath(outfile),
         contentType = 'image/svg+xml',
         width = width,
         height = height,
         alt = "My Histogram")
  })

})

请注意，我没有使用 svglite 包，只使用了 grDevices（基本）包中的 svg 设备。我还对源中的路径进行了规范化，因为我在 Windows 机器上（我相信这会将我的源从正斜杠更改为反斜杠，但也许有人会对此发表评论）。

另外，我创建了四个新变量来容纳 svg 的宽度和高度以及图像的宽度和高度，以便仍然与页面保持流畅。我确信有比这更简单的解决方法，但这是我发现的有效方法。

Answer 2

受上述基本图形的 R_User123456789s 解决方案（此处）的启发，我使用 ggplot2 通过以下方式得到它

ui.r

shinyUI(pageWithSidebar(
  headerPanel("renderSVG example"),
  sidebarPanel(
    sliderInput("obs", "Number of observations:",
                min = 0, max = 1000,  value = 500)
  ),
  mainPanel(
    # Use imageOutput to place the image on the page
    imageOutput("plot"),
    imageOutput("plot_as_svg")
  )
))

server.r

require("ggplot2")

shinyServer(function(input, output, session) {

  ## create plot with renderPlot()


  output$plot<- renderPlot({
    hist(rnorm(input$obs), main="Generated in renderPlot() as png")
  })


  ## create .svg file of the plot and render it with renderImage()

  output$plot_as_svg <- renderImage({

    width  <- session$clientData$output_plot_width
    height <- session$clientData$output_plot_height
    mysvgwidth <- width/96
    mysvgheight <- height/96

    # A temp file to save the output.
    # This file will be removed later by renderImage

    outfile <- tempfile(fileext='.svg')

    # Generate the svg
    #to see actually what will be plotted and compare 
    qplot(clarity, data=diamonds, fill=cut, geom="bar")
    #save the plot in a variable image to be able to export to svg
    image=qplot(clarity, data=diamonds[1:input$obs,], fill=cut, geom="bar", main = "ggplot as svg")
    #This actually save the plot in a image
    ggsave(file=outfile, plot=image, width=mysvgwidth, height=mysvgheight)

    # Return a list containing the filename
    list(src = normalizePath(outfile),
         contentType = 'image/svg+xml',
         width = width,
         height = height,
         alt = "My svg Histogram")
  })

})