[英]Conflict when generating addPolylines on the map made by Leaflet
朋友們，你能幫我解決以下問題嗎：我在插入addPolylines function生成第二個leaflet map時遇到沖突。一般來說，Map 1涉及顯示所有集群，Map 2涉及特定集群。 對於這個特定的集群，我插入了一個特性來遵守與 map1 上形成的集群相同的 colors。 第一段代碼正確地完成了上述描述。 但是，我還為第二個 map 插入了引用 addPolylines 的第二個代碼。但是當我在第一個代碼中插入第二個代碼時，在涉及 map 2 的生成的部分，它給出了一個錯誤： Warning: Error in eval: object 'm2' not found 。 你能幫我解決這個問題嗎？
library(shiny)
library(ggplot2)
library(rdist)
library(geosphere)
library(shinythemes)
library(leaflet)
function.cl<-function(df,k,Filter1,Filter2){
#database df
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),
Waste = c(526, 350, 526, 469, 285, 433, 456)), class = "data.frame", row.names = c(NA, -7L))
#clusters
coordinates<-df[c("Latitude","Longitude")]
d<-as.dist(distm(coordinates[,2:1]))
fit.average<-hclust(d,method="average")
clusters<-cutree(fit.average, k)
nclusters<-matrix(table(clusters))
df$cluster <- clusters
#specific cluster and specific propertie
df1<-df[c("Latitude","Longitude")]
df1$cluster<-as.factor(clusters)
df_spec_clust <- df1[df1$cluster == Filter1,]
df_spec_prop<-df[df$Properties==Filter2,]
#Table to join df and df1
data_table <- Reduce(merge, list(df, df1))
#Color and Icon for map
ai_colors <-c("red","gray","blue","orange","green","beige","darkgreen","lightgreen", "lightred", "darkblue","lightblue",
"purple","darkpurple","pink", "cadetblue","white","darkred", "lightgray","black")
clust_colors <- ai_colors[df$cluster]
icons <- awesomeIcons(
icon = 'ios-close',
iconColor = 'black',
library = 'ion',
markerColor = clust_colors)
leafIcons <- icons(
iconUrl = ifelse(df1$Properties,
"https://image.flaticon.com/icons/svg/542/542461.svg"
),
iconWidth = 45, iconHeight = 40,
iconAnchorX = 25, iconAnchorY = 12)
html_legend <- "<img src='https://image.flaticon.com/icons/svg/542/542461.svg'>"
# Map for all clusters:
m1<-leaflet(df1) %>% addTiles() %>%
addMarkers(~Longitude, ~Latitude, icon = leafIcons) %>%
addAwesomeMarkers(lat=~df$Latitude, lng = ~df$Longitude, icon=icons, label=~as.character(df$cluster)) %>%
addPolylines(lat=~df$Latitude, lng = ~df$Longitude,color="red") %>%
addLegend( position = "topright", title="Cluster", colors = ai_colors[1:max(df$cluster)],labels = unique(df$cluster))
plot1<-m1
# Map for specific cluster and propertie
if(nrow(df_spec_clust)>0){
clust_colors <- ai_colors[df_spec_clust$cluster]
icons <- awesomeIcons(
icon = 'ios-close',
iconColor = 'black',
library = 'ion',
markerColor = clust_colors)
m2<-leaflet(df_spec_clust) %>% addTiles() %>%
addAwesomeMarkers(lat=~Latitude, lng = ~Longitude, icon=icons, label=~cluster)
plot2<-m2} else plot2 <- NULL
return(list(
"Plot1" = plot1,
"Plot2" = plot2,
"Data" = data_table
))
}
ui <- bootstrapPage(
navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
"Cl",
tabPanel("Solution",
sidebarLayout(
sidebarPanel(
tags$b(h3("Choose the cluster number?")),
sliderInput("Slider", h5(""),
min = 2, max = 5, value = 3),
),
mainPanel(
tabsetPanel(
tabPanel("Solution", (leafletOutput("Leaf1",width = "95%", height = "600")))))
))),
tabPanel("",
sidebarLayout(
sidebarPanel(
selectInput("Filter1", label = h4("Select just one cluster to show"),""),
selectInput("Filter2",label=h4("Select the cluster property designated above"),""),
),
mainPanel(
tabsetPanel(
tabPanel("Map", (leafletOutput("Leaf2",width = "95%", height = "600")))))
)))
server <- function(input, output, session) {
Modelcl<-reactive({
function.cl(df,input$Slider,input$Filter1,input$Filter2)
})
output$Leaf1 <- renderLeaflet({
Modelcl()[[1]]
})
output$Leaf2 <- renderLeaflet({
Modelcl()[[2]]
})
observeEvent(input$Slider, {
abc <- req(Modelcl()$Data)
updateSelectInput(session,'Filter1',
choices=sort(unique(abc$cluster)))
})
observeEvent(input$Filter1,{
abc <- req(Modelcl()$Data) %>% filter(cluster == as.numeric(input$Filter1))
updateSelectInput(session,'Filter2',
choices=sort(unique(abc$Properties)))
})
}
shinyApp(ui = ui, server = server)
for(i in 1:nrow(df_spec_clust)){
df_line <- rbind(df_spec_prop[,c("Latitude","Longitude")],
df_spec_clust[i,c("Latitude","Longitude")])
m2 <- m2 %>%
addPolylines(data = df_line,
lat=~Latitude,
lng = ~Longitude,
color="red")
}
plot2<-m2
當我將第二個代碼插入第一個關於生成 map 2 的代碼時：
# Map for specific cluster and propertie
if(nrow(df_spec_clust)>0){
clust_colors <- ai_colors[df_spec_clust$cluster]
icons <- awesomeIcons(
icon = 'ios-close',
iconColor = 'black',
library = 'ion',
markerColor = clust_colors)
m2<-leaflet(df_spec_clust) %>% addTiles() %>%
addAwesomeMarkers(lat=~Latitude, lng = ~Longitude, icon=icons, label=~cluster)
plot2<-m2} else plot2 <- NULL
for(i in 1:nrow(df_spec_clust)){
df_line <- rbind(df_spec_prop[,c("Latitude","Longitude")],
df_spec_clust[i,c("Latitude","Longitude")])
m2 <- m2 %>%
addPolylines(data = df_line,
lat=~Latitude,
lng = ~Longitude,
color="red")
}
plot2<-m2
出現以下錯誤： 警告：評估錯誤：object 未找到“m2”。```
非常感謝你！
您必須在if語句中插入代碼：
# Map for specific cluster and propertie
if(nrow(df_spec_clust)>0){
clust_colors <- ai_colors[df_spec_clust$cluster]
icons <- awesomeIcons(
icon = 'ios-close',
iconColor = 'black',
library = 'ion',
markerColor = clust_colors)
m2<-leaflet(df_spec_clust) %>% addTiles() %>%
addAwesomeMarkers(lat=~Latitude, lng = ~Longitude, icon=icons, label=~cluster)
for(i in 1:nrow(df_spec_clust)){
df_line <- rbind(df_spec_prop[,c("Latitude","Longitude")],
df_spec_clust[i,c("Latitude","Longitude")])
m2 <- m2 %>%
addPolylines(data = df_line,
lat=~Latitude,
lng = ~Longitude,
color="red")
}
plot2<-m2} else plot2 <- NULL
@Jovani SouzA @Jose m2 將 object 傳遞到您的方法鏈中時不存在，您的意思是將 m1 傳遞到方法鏈中以添加折線以創建 m2。
library(shiny)
library(ggplot2)
library(rdist)
library(geosphere)
library(shinythemes)
library(leaflet)
function.cl<-function(df,k,Filter1,Filter2){
#database df
df<-structure(list(Properties = c(1,2,3,4,5,6,7),
Latitude = c(-23.8, -23.8, -23.9, -23.9, -23.9,-23.4,-23.5),
Longitude = c(-49.6, -49.3, -49.4, -49.8, -49.6,-49.4,-49.2),
Waste = c(526, 350, 526, 469, 285, 433, 456)), class = "data.frame", row.names = c(NA, -7L))
#clusters
coordinates<-df[c("Latitude","Longitude")]
d<-as.dist(distm(coordinates[,2:1]))
fit.average<-hclust(d,method="average")
clusters<-cutree(fit.average, k)
nclusters<-matrix(table(clusters))
df$cluster <- clusters
#specific cluster and specific propertie
df1<-df[c("Latitude","Longitude")]
df1$cluster<-as.factor(clusters)
df_spec_clust <- df1[df1$cluster == Filter1,]
df_spec_prop<-df[df$Properties==Filter2,]
#Table to join df and df1
data_table <- Reduce(merge, list(df, df1))
#Color and Icon for map
ai_colors <-c("red","gray","blue","orange","green","beige","darkgreen","lightgreen", "lightred", "darkblue","lightblue",
"purple","darkpurple","pink", "cadetblue","white","darkred", "lightgray","black")
clust_colors <- ai_colors[df$cluster]
icons <- awesomeIcons(
icon = 'ios-close',
iconColor = 'black',
library = 'ion',
markerColor = clust_colors)
leafIcons <- icons(
iconUrl = ifelse(df1$Properties,
"https://image.flaticon.com/icons/svg/542/542461.svg"
),
iconWidth = 45, iconHeight = 40,
iconAnchorX = 25, iconAnchorY = 12)
html_legend <- "<img src='https://image.flaticon.com/icons/svg/542/542461.svg'>"
# Map for all clusters:
m1<-leaflet(df1) %>% addTiles() %>%
addMarkers(~Longitude, ~Latitude, icon = leafIcons) %>%
addAwesomeMarkers(lat=~df$Latitude, lng = ~df$Longitude, icon=icons, label=~as.character(df$cluster)) %>%
addPolylines(lat=~df$Latitude, lng = ~df$Longitude,color="red") %>%
addLegend( position = "topright", title="Cluster", colors = ai_colors[1:max(df$cluster)],labels = unique(df$cluster))
plot1<-m1
# Map for specific cluster and propertie
if(nrow(df_spec_clust)>0){
clust_colors <- ai_colors[df_spec_clust$cluster]
icons <- awesomeIcons(
icon = 'ios-close',
iconColor = 'black',
library = 'ion',
markerColor = clust_colors)
m2<-leaflet(df_spec_clust) %>% addTiles() %>%
addAwesomeMarkers(lat=~Latitude, lng = ~Longitude, icon=icons, label=~cluster)
plot2<-m2} else plot2 <- NULL
for(i in 1:nrow(df_spec_clust)){
df_line <- rbind(df_spec_prop[,c("Latitude","Longitude")],
df_spec_clust[i,c("Latitude","Longitude")])
m2 <- m1 %>%
addPolylines(data = df_line,
lat=~Latitude,
lng = ~Longitude,
color="red")
}
plot2<-m2
return(list(
"Plot1" = plot1,
"Plot2" = plot2,
"Data" = data_table
))
}
ui <- bootstrapPage(
navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
"Cl",
tabPanel("Solution",
sidebarLayout(
sidebarPanel(
tags$b(h3("Choose the cluster number?")),
sliderInput("Slider", h5(""),
min = 2, max = 5, value = 3),
),
mainPanel(
tabsetPanel(
tabPanel("Solution", (leafletOutput("Leaf1",width = "95%", height = "600")))))
))),
tabPanel("",
sidebarLayout(
sidebarPanel(
selectInput("Filter1", label = h4("Select just one cluster to show"),""),
selectInput("Filter2",label=h4("Select the cluster property designated above"),""),
),
mainPanel(
tabsetPanel(
tabPanel("Map", (leafletOutput("Leaf2",width = "95%", height = "600")))))
)))
server <- function(input, output, session) {
Modelcl<-reactive({
function.cl(df,input$Slider,input$Filter1,input$Filter2)
})
output$Leaf1 <- renderLeaflet({
Modelcl()[[1]]
})
output$Leaf2 <- renderLeaflet({
Modelcl()[[2]]
})
observeEvent(input$Slider, {
abc <- req(Modelcl()$Data)
updateSelectInput(session,'Filter1',
choices=sort(unique(abc$cluster)))
})
observeEvent(input$Filter1,{
abc <- req(Modelcl()$Data) %>% filter(cluster == as.numeric(input$Filter1))
updateSelectInput(session,'Filter2',
choices=sort(unique(abc$Properties)))
})
}
shinyApp(ui = ui, server = server)
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