下面的闪亮代码使用以下命令生成两点之间的路线googleway功能。请注意，此外，还计算了两点之间的距离，但这是欧氏距离，而不是使用googleway功能。计算距离的正确方法是执行以下操作：
test<-google_directions(origin = c(-24.872139, -50.038787), destination = c(-24.9062992895515, -50.0125745903862), mode = "driving", alternatives = TRUE)
Distance<-sum(as.numeric(direction_steps(test)$distance$value))
[1] 6153
但是，我希望在下面的闪亮代码中使用这种计算形式，以便正确计算路线。因此，你能帮我调整闪亮的代码吗？
闪亮的代码
library(shiny)
library(dplyr)
library(geosphere)
library(shinythemes)
library(googleway)
set_key( "YOUR_API_KEY")
k=3
function.cl<-function(df,k,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
} else {
plot1 <- NULL
}
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$Latitude_df1),
.f = ~distm(c(..1,..2),c(..3,..4))))
return(list(
"Plot1" = plot1,
"DIST" = DISTANCE,
"Data" = data_table_1,
"Data1" = data_table
))
}
ui <- bootstrapPage(
navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
"Cl",
tabPanel("Solution",
sidebarLayout(
sidebarPanel(
selectInput("Filter1", label = h4("Select just one cluster to show"),""),
selectInput("Filter2",label=h4("Select the cluster property designated above"),""),
h4("The distance is:"),
textOutput("dist"),
),
mainPanel(
tabsetPanel(
tabPanel("Gmaps", (google_mapOutput("Gmaps",width = "95%", height = "600")))
))))))
server <- function(input, output, session) {
Modelcl<-reactive({
function.cl(df,k,input$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)))})
output$dist <- renderText({
DIST <- data.frame(Modelcl()[[2]])
DIST$distance[DIST$cluster == input$Filter1 & DIST$Properties == input$Filter2]
})
}
shinyApp(ui = ui, server = server)
