Adjust the way to calculate the distance between two points in shiny code-CodePudding

The

CodePudding user response：

You could first simplify calculation of euclidian distance : purrr::map isn't needed here as the calculation is only between two points.

Then, road distance calculation is straight forward with the code you provided :

library(shiny) library(dplyr) library(geosphere) library(shinythemes) library(googleway) set_key( "AIzaSyBD6kgTlgcTa6iwLwoWtKrKQI6QNodEkmo") k=3 function.cl<-function(Filter1,Filter2){ df<-structure(list(Properties = c(1, 2, 3, 4, 5, 6, 7), Latitude = c(-23.8, -23.8, -23.9, -23.9, -23.9, -23.4, -23.5), Longitude = c(-49.6, -49.3, -49.4, -49.8, -49.6, -49.4, -49.2), cluster = c(1L, 2L, 2L, 1L, 1L, 3L,3L)), row.names = c(NA, -7L), class = "data.frame") df1<-structure(list(Latitude = c(-23.8666666666667, -23.85, -23.45 ), Longitude = c(-49.6666666666667, -49.35, -49.3), cluster = c(1, 2, 3)), class = "data.frame", row.names = c(NA, -3L)) #specific cluster and specific propertie df_spec_clust <- df1[df1$cluster == Filter1,] df_spec_prop<-df[df$Properties==Filter2,] #Table to join data_table <- df[order(df$cluster, as.numeric(df$Properties)),] data_table_1 <- aggregate(. ~ cluster, df[,c("cluster","Properties")], toString) # Map for route if(nrow(df_spec_clust>0) & nrow(df_spec_prop>0)) { df2<-google_directions(origin = df_spec_clust[,1:2], destination = df_spec_prop[,2:3], mode = "driving") df_routes <- data.frame(polyline = direction_polyline(df2)) m1<-google_map() %>% add_polylines(data = df_routes, polyline = "polyline") plot1<-m1 # Euclidian distance distance_road <- sum(as.numeric(direction_steps(df2)$distance$value)) # Road distance distance_straight <- distm(df_spec_clust[,2:1],df_spec_prop[,3:2]) } else { plot1 <- NULL distance_road <- NA distance_straight <- NA } # Not needed? DISTANCE<- merge(df,df1,by = c("cluster"), suffixes = c("_df","_df1")) (DISTANCE$distance <- purrr::pmap_dbl(.l = list(DISTANCE$Longitude_df, DISTANCE$Latitude_df, DISTANCE$Longitude_df1, DISTANCE$Latitude_df1), .f = ~distm(c(..1,..2),c(..3,..4)))) return(list( "Plot1" = plot1, "DIST" = DISTANCE, "distance_road" = distance_road, "distance_straight" = distance_straight, "Data" = data_table_1, "Data1" = data_table )) } ui <- bootstrapPage( navbarPage(theme = shinytheme("flatly"), collapsible = TRUE, "Cl", tabPanel("Solution", sidebarLayout( sidebarPanel( selectInput("Filter1", label = h4("Select just one cluster to show"),""), selectInput("Filter2",label=h4("Select the cluster property designated above"),""), h4("The distance is:"), textOutput("dist"), textOutput("distance_straight"), textOutput("distance_road") ), mainPanel( tabsetPanel( tabPanel("Gmaps", (google_mapOutput("Gmaps",width = "95%", height = "600"))) )))))) server <- function(input, output, session) { Modelcl<-reactive({ function.cl(input$Filter1,input$Filter2) }) output$Gmaps <- renderGoogle_map({ Modelcl()[[1]] }) observeEvent(k, { abc <- req(Modelcl()$Data) updateSelectInput(session,'Filter1', choices=sort(unique(abc$cluster))) }) observeEvent(c(k,input$Filter1),{ abc <- req(Modelcl()$Data1) %>% filter(cluster == as.numeric(input$Filter1)) updateSelectInput(session,'Filter2', choices=sort(unique(abc$Properties)))}) # Original calculation output$dist <- renderText({ DIST <- data.frame(Modelcl()[[2]]) paste0("Original distance calculation: ",round(DIST$distance[DIST$cluster == input$Filter1 & DIST$Properties == input$Filter2])," meters") }) # Simplified version output$distance_straight <- renderText({ paste0("Simplified distance calculation: ",round(Modelcl()$distance_straight)," meters") }) output$distance_road <- renderText({ paste0("Road distance calculation: ",Modelcl()$distance_road," meters") }) } shinyApp(ui = ui, server = server)