3

Species当光标在该点上而不是 x 和 y 值上时，我想显示每个数据点的 。我使用iris数据集。此外，我希望能够单击数据点以使标签持久化，并且当我在图中选择一个新点时不会消失。（如果可能的话 ）。基本是标签。持久性问题是一个优点。这是我的应用程序：

## Note: extrafont is a bit finnicky on Windows, 
## so be sure to execute the code in the order 
## provided, or else ggplot won't find the font

# Use this to acquire additional fonts not found in R
install.packages("extrafont");library(extrafont)
# Warning: if not specified in font_import, it will 
# take a bit of time to get all fonts
font_import(pattern = "calibri")
loadfonts(device = "win")

#ui.r
library(shiny)
library(ggplot2)
library(plotly)
library(extrafont)
library(ggrepel)
fluidPage(

  # App title ----
  titlePanel(div("CROSS CORRELATION",style = "color:blue")),

  # Sidebar layout with input and output definitions ----
  sidebarLayout(

    # Sidebar panel for inputs ----
    sidebarPanel(

      # Input: Select a file ----
      fileInput("file1", "Input CSV-File",
                multiple = TRUE,
                accept = c("text/csv",
                           "text/comma-separated-values,text/plain",
                           ".csv")),

      # Horizontal line ----
      tags$hr(),

      # Input: Checkbox if file has header ----
      checkboxInput("header", "Header", TRUE),

      # Input: Select separator ----
      radioButtons("sep", "Separator",
                   choices = c(Comma = ",",
                               Semicolon = ";",
                               Tab = "\t"),
                   selected = ","),


      # Horizontal line ----
      tags$hr(),

      # Input: Select number of rows to display ----
      radioButtons("disp", "Display",
                   choices = c(Head = "head",
                               All = "all"),
                   selected = "head")





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

      tabsetPanel(type = "tabs",
                  tabPanel("Table",
                           shiny::dataTableOutput("contents")),
                  tabPanel("Correlation Plot",
                           tags$style(type="text/css", "
           #loadmessage {
                                      position: fixed;
                                      top: 0px;
                                      left: 0px;
                                      width: 100%;
                                      padding: 5px 0px 5px 0px;
                                      text-align: center;
                                      font-weight: bold;
                                      font-size: 100%;
                                      color: #000000;
                                      background-color: #CCFF66;
                                      z-index: 105;
                                      }
                                      "),conditionalPanel(condition="$('html').hasClass('shiny-busy')",
                                                          tags$div("Loading...",id="loadmessage")
                                      ),
                           fluidRow(
                             column(3, uiOutput("lx1")),
                           column(3,uiOutput("lx2"))),
                           hr(),
                           fluidRow(
                             tags$style(type="text/css",
                                        ".shiny-output-error { visibility: hidden; }",
                                        ".shiny-output-error:before { visibility: hidden; }"
                             ),
                           column(3,uiOutput("td")),
                           column(3,uiOutput("an"))),
                           fluidRow(
                           plotlyOutput("sc"))
      ))
  )))
#server.r
function(input, output) {


  output$contents <- shiny::renderDataTable({

    iris
  })


  output$lx1<-renderUI({
    selectInput("lx1", label = h4("Select 1st Expression Profile"), 
                choices = colnames(iris[,1:4]), 
                selected = "Lex1")
  })
  output$lx2<-renderUI({
    selectInput("lx2", label = h4("Select 2nd Expression Profile"), 
                choices = colnames(iris[,1:4]), 
                selected = "Lex2")
  })

  output$td<-renderUI({
    radioButtons("td", label = h4("Trendline"),
                 choices = list("Add Trendline" = "lm", "Remove Trendline" = ""), 
                 selected = "")
  })

  output$an<-renderUI({

    radioButtons("an", label = h4("Correlation Coefficient"),
                 choices = list("Add Cor.Coef" = cor(subset(iris, select=c(input$lx1)),subset(iris, select=c(input$lx2))), "Remove Cor.Coef" = ""), 
                 selected = "")
  })  


 output$sc<-renderPlotly({

   p1 <- ggplot(iris, aes_string(x = input$lx1, y = input$lx2))+

     # Change the point options in geom_point
     geom_point(color = "darkblue") +
     # Change the title of the plot (can change axis titles
     # in this option as well and add subtitle)
     labs(title = "Cross Correlation") +
     # Change where the tick marks are
     scale_x_continuous(breaks = seq(0, 2.5, 30)) +
     scale_y_continuous(breaks = seq(0, 2.5, 30)) +
     # Change how the text looks for each element
     theme(title = element_text(family = "Calibri", 
                                size = 10, 
                                face = "bold"), 
           axis.title = element_text(family = "Calibri Light", 
                                     size = 16, 
                                     face = "bold", 
                                     color = "darkgrey"), 
           axis.text = element_text(family = "Calibri", 
                                    size = 11))+
     theme_bw()+
     geom_smooth(method = input$td)+
     annotate("text", x = 10, y = 10, label = as.character(input$an))
   ggplotly(p1) %>%
     layout(hoverlabel = list(bgcolor = "white", 
                              font = list(family = "Calibri", 
                                          size = 9, 
                                          color = "black")))

 }) 




}
4

1 回答 1

10

1. 工具提示

您可以通过多种方式更改工具提示，如此处所述。要Species在工具提示中显示，这样的事情应该可以工作：

library(ggplot2)
library(plotly)
p1 <- ggplot(iris, aes_string(x = "Sepal.Length", 
                                y = "Sepal.Width",
                                key = "Species")) +
      geom_point()
ggplotly(p1, source = "select", tooltip = c("key"))

2. 持久标签

我不确定如何在单击时将plotly工具提示留在该点上，但是您可以使用plotly单击事件来获取单击的点，然后将geom_text图层添加到您的ggplot.

3. 最小示例

我已经修改了您的代码以制作一个更简单的示例。通常，如果您创建一个最小示例并删除重新创建问题不需要的应用程序部分（例如更改字体），这会很有帮助。

library(shiny)
library(plotly)
library(ggplot2)

ui <- fluidPage(
  plotlyOutput("iris")
)

server <- function(input, output, session) {
  output$iris <- renderPlotly({
      # set up plot
      p1 <- ggplot(iris, aes_string(x = "Sepal.Length", 
                                    y = "Sepal.Width",
                                    key = "Species")) +
          geom_point()

      # get clicked point
      click_data <- event_data("plotly_click", source = "select")
      # if a point has been clicked, add a label to the plot
      if(!is.null(click_data)) {
          label_data <- data.frame(x = click_data[["x"]],
                                   y = click_data[["y"]],
                                   label = click_data[["key"]],
                                   stringsAsFactors = FALSE)
         p1 <- p1 + 
             geom_text(data = label_data,
                       aes(x = x, y = y, label = label),
                       inherit.aes = FALSE, nudge_x = 0.25)
      }
      # return the plot
      ggplotly(p1, source = "select", tooltip = c("key"))
  })
  }

shinyApp(ui, server)

在此处输入图像描述

编辑：保留所有标签

您可以将每次点击存储在响应式 data.frame 中reactiveValues，并将此 data.frame 用于您的geom_text图层。

library(shiny)
library(plotly)
library(ggplot2)

ui <- fluidPage(
    plotlyOutput("iris")
)

server <- function(input, output, session) {
    # 1. create reactive values
    vals <- reactiveValues()
    # 2. create df to store clicks
    vals$click_all <- data.frame(x = numeric(),
                                y = numeric(),
                                label = character())
    # 3. add points upon plot click
    observe({
        # get clicked point
        click_data <- event_data("plotly_click", source = "select")
        # get data for current point
        label_data <- data.frame(x = click_data[["x"]],
                                 y = click_data[["y"]],
                                 label = click_data[["key"]],
                                 stringsAsFactors = FALSE)
        # add current point to df of all clicks
        vals$click_all <- merge(vals$click_all,
                                label_data, 
                                all = TRUE)
    })
    output$iris <- renderPlotly({
        # set up plot
        p1 <- ggplot(iris, aes_string(x = "Sepal.Length", 
                                      y = "Sepal.Width",
                                      key = "Species")) +
            geom_point() + 
            # 4. add labels for clicked points
            geom_text(data = vals$click_all,
                      aes(x = x, y = y, label = label),
                      inherit.aes = FALSE, nudge_x = 0.25)
        # return the plot
        ggplotly(p1, source = "select", tooltip = c("key"))
    })
}

shinyApp(ui, server)

在此处输入图像描述

于 2018-03-24T01:16:26.337 回答