闪亮的重置按钮

Question

[朋友，您能帮助我在代码中使用“清除”按钮吗？我创建了按钮，但无法正常工作。当按下“清除”按钮时，我想清除生成的表格和图形。另外，如果使用了过滤器，我希望它们恢复到原来的标准。

library(shiny)
library(ggplot2)
library(rdist)
library(geosphere)
library(kableExtra)
library(readxl)
library(tidyverse)
library(DT)

#database
df<-structure(list(Properties = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35), Latitude = c(-23.8, -23.8, -23.9, -23.9, -23.9,  -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, -23.9, 
                                                                                                                                                 + -23.9, -23.9, -23.9, -23.9, -23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9,-23.9), Longitude = c(-49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.6, -49.7, 
                                                                                                                                                                                                                                                                                                     + -49.7, -49.7, -49.7, -49.7, -49.6, -49.6, -49.6, -49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6,-49.6), Waste = c(526, 350, 526, 469, 285, 175, 175, 350, 350, 175, 350, 175, 175, 364, 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                          + 175, 175, 350, 45.5, 54.6,350,350,350,350,350,350,350,350,350,350,350,350,350,350,350,350)), class = "data.frame", row.names = c(NA, -35L))

function.clustering<-function(df,k,Filter1,Filter2){

  if (Filter1==2){
    Q1<-matrix(quantile(df$Waste, probs = 0.25)) 
    Q3<-matrix(quantile(df$Waste, probs = 0.75))
    L<-Q1-1.5*(Q3-Q1)
    S<-Q3+1.5*(Q3-Q1)
    df_1<-subset(df,Waste>L[1]) 
    df<-subset(df_1,Waste<S[1])
  }

  #cluster
  coordinates<-df[c("Latitude","Longitude")]
  d<-as.dist(distm(coordinates[,2:1]))
  fit.average<-hclust(d,method="average") 


  #Number of clusters
  clusters<-cutree(fit.average, k) 
  nclusters<-matrix(table(clusters))  
  df$cluster <- clusters 

  #Localization
  center_mass<-matrix(nrow=k,ncol=2)
  for(i in 1:k){
    center_mass[i,]<-c(weighted.mean(subset(df,cluster==i)$Latitude,subset(df,cluster==i)$Waste),
                       weighted.mean(subset(df,cluster==i)$Longitude,subset(df,cluster==i)$Waste))}
  coordinates$cluster<-clusters 
  center_mass<-cbind(center_mass,matrix(c(1:k),ncol=1)) 

  #Coverage
  coverage<-matrix(nrow=k,ncol=1)
  for(i in 1:k){
    aux_dist<-distm(rbind(subset(coordinates,cluster==i),center_mass[i,])[,2:1])
    coverage[i,]<-max(aux_dist[nclusters[i,1]+1,])}
  coverage<-cbind(coverage,matrix(c(1:k),ncol=1))
  colnames(coverage)<-c("Coverage_meters","cluster")

  #Sum of Waste from clusters
  sum_waste<-matrix(nrow=k,ncol=1)
  for(i in 1:k){
    sum_waste[i,]<-sum(subset(df,cluster==i)["Waste"])
  }
  sum_waste<-cbind(sum_waste,matrix(c(1:k),ncol=1))
  colnames(sum_waste)<-c("Potential_Waste_m3","cluster")

  #Table1
  data_table <- Reduce(merge, list(df, coverage, sum_waste))
  data_table <- data_table[order(data_table$cluster, as.numeric(data_table$Properties)),]
  data_table_1 <- aggregate(. ~ cluster + Coverage_meters + Potential_Waste_m3, data_table[,c(1,7,6,2)], toString)

  #Plot1
  #Scatter Plot
  suppressPackageStartupMessages(library(ggplot2))
  df1<-as.data.frame(center_mass)
  colnames(df1) <-c("Latitude", "Longitude", "cluster")
  g<-ggplot(data=df,  aes(x=Longitude, y=Latitude,  color=factor(clusters))) + geom_point(aes(x=Longitude, y=Latitude), size = 4)
  Centro_View<- g +  geom_text(data=df, mapping=aes(x=eval(Longitude), y=eval(Latitude), label=Waste), size=3, hjust=-0.1)+ geom_point(data=df1, mapping=aes(Longitude, Latitude), color= "green", size=4) + geom_text(data=df1, mapping = aes(x=Longitude, y=Latitude, label = 1:k), color = "black", size = 4)
  plot1<-print(Centro_View + ggtitle("Scatter Plot") + theme(plot.title = element_text(hjust = 0.5)))

  return(list(
    "Data" = data_table_1,
    "Plot" = plot1

  ))

}


ui <- fluidPage(

  titlePanel("Clustering "),


  sidebarLayout(
    sidebarPanel(
      helpText(h3("Generation of clustering")),

      radioButtons("filter1", h3("Waste Potential"),
                   choices = list("Select all properties" = 1, 
                                  "Exclude properties that produce less than L and more than S" = 2),
                   selected = 1),

      tags$hr(),

      radioButtons("filter2", h3("Are you satisfied with the solution"),
                   choices = list("Yes" = 1, 
                                  "No" = 2),
                   selected = 1),

      sliderInput("Slider", h3("Number of clusters"),
                  min = 2, max = 34, value = 8),

    tags$hr(),
    actionButton("reset", "Clean all"),

    downloadButton("downloadData", "Download")),


    mainPanel(
      tabsetPanel( 
        tabPanel("Table",DTOutput("tabela")),
        tabPanel("Figure",plotOutput("ScatterPlot"))

    ))))

server <- function(input, output) {

  values <- reactiveValues(df = NULL)

  Modelclustering<-reactive(function.clustering(df,input$Slider,input$filter1,input$filter2))

  output$tabela <- renderDataTable({
    data_table_1 <- req(Modelclustering())[[1]]
    x <- datatable(data_table_1[order(data_table_1$cluster), c(1, 4, 2, 3)],
                   options = list(
                     paging =TRUE,
                     pageLength =  5,lengthChange=FALSE)
                   ) %>% formatRound(c(3:4), 2)
    return(x)
  })

   output$ScatterPlot <- renderPlot({
    Modelclustering()[[2]]
  })
}

observeEvent(input$reset,{
  values$df <- NULL
})


# Run the application 
shinyApp(ui = ui, server = server)

非常感谢您的朋友！

Answer 1

@ Jovani-

要重置单选按钮，请在updateRadioButtons中使用server。

您将为此需要session，请确保这是您的server函数中的参数（在下面添加）。

还请确保您的observeEvent是inside您的server函数（我想是因为您说过它在起作用）。

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

  values <- reactiveValues(df = NULL)

  Modelclustering<-reactive(function.clustering(df,input$Slider,input$filter1,input$filter2))

  output$tabela <- renderDataTable({
    data_table_1 <- req(Modelclustering())[[1]]
    x <- datatable(data_table_1[order(data_table_1$cluster), c(1, 4, 2, 3)],
                   options = list(
                     paging =TRUE,
                     pageLength =  5,lengthChange=FALSE)
    ) %>% formatRound(c(3:4), 2)
    return(x)
  })

  output$ScatterPlot <- renderPlot({
    Modelclustering()[[2]]
  })

  observeEvent(input$reset,{
    values$df <- NULL
    updateRadioButtons(session, "filter1", selected = 1)
    updateRadioButtons(session, "filter2", selected = 1)
  })
}