r - map 不会在带有传单和光栅的 Shiny 应用程序中呈现-6ren

r - map 不会在带有传单和光栅的 Shiny 应用程序中呈现

转载作者：行者123 更新时间：2023-12-04 06:42:03

我正在一个 Shiny 的应用程序中工作，它可以让您知道哪些地方适合您居住，这是正确知道的工作应用程序:

shiny app

到目前为止我喜欢它，但我真的更喜欢有一个传单 map ，你可以在其中放大而不是静态 map ，但到目前为止，我在传单包渲染或更新光栅时遇到了很多问题。如果你需要文件，github 仓库就是这个仓库 repository

这是应用程序现在服务器的代码:

library(shiny)
library(raster)
library(rworldmap)
library(rgdal)
library(dplyr)
data("countriesCoarse")
uno <- readRDS("uno.rds")
World <- getData('worldclim', var='bio', res=10)
cities <- readRDS("cities.rds")
shinyServer(function(input, output) {

  output$distPlot <- renderPlot({
    uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
    uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
    uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
    plot(uno, col ="red", legend = FALSE)
    plot(countriesCoarse, add = TRUE)
})
  output$downloadPlot <- downloadHandler(
    filename = function() { paste("WhereToLive", '.png', sep='') },
content = function(file) {
    png(file)
    uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
    uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
    uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
    plot(uno, col ="red", legend = FALSE)
    plot(countriesCoarse, add = TRUE)
    dev.off()
})
  output$visFun <- renderDataTable({
    uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
    uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
    uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
    cities$exists <- extract(uno, cities[,2:3])
    cities <- filter(cities, exists == 1)
    cities <- cities[,c(1,4,5,6)]
    cities <- filter(cities, pop > min(as.numeric(as.character(input$Population))))
    cities <- filter(cities, pop < max(as.numeric(as.character(input$Population))))
    cities
})
  output$downloadData <- downloadHandler(
    filename = function() { paste("cities", '.csv', sep='') },
    content = function(file) {
      uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
      uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
      uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
      uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
      uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
      uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
      cities$exists <- extract(uno, cities[,2:3])
      cities <- filter(cities, exists == 1)
      cities <- filter(cities$pop > min(input$Population))
      cities <- filter(cities$pop < max(input$Population))
      cities <- cities[,c(1,4,5,6)]
      write.csv(cities, file)
}
)
})

用户界面:

library(shiny)
library(raster)
library(rworldmap)
library(rgdal)
data("countriesCoarse")


shinyUI(fluidPage(

  titlePanel("Where should you live according to your climate preferences?"),


  sidebarLayout(
    sidebarPanel(
      h3("Select your climate preferences"),
      p("Using worldclim database, and knowing your climate prefeneces, you can now using this tool get an idea of where in the world you should live."),
      p("Just use the sliders to anwer the simple questions we ask and you will get a map together with a downloadable table of where the climate suits you."),
      selectInput(inputId = "degrees", label = "Temp units:", choices = 
                c("Celcius"= "Celcius",
                  "Fahrenheit" = "Fahrenheit")),
      submitButton("Update View", icon("refresh")),
      conditionalPanel(condition = "input.degrees == 'Celcius'",
                   sliderInput(inputId = "MaxTempC",
                               label = "What's the average maximum temperature you want to endure during the summer?",
                               min = 0,
                               max = 50,
                               value = 30),
                   sliderInput(inputId = "MinTempC",
                               label = "What's the average minimum temperature you want to endure during the winter?",
                               min = -40,
                               max = 60,
                               value = 0),
                   sliderInput(inputId = "RangeTempC",
                               label = "What's your prefered temperature range?",
                               min = -10,
                               max = 30,
                               value = c(0, 20)),
                   sliderInput(inputId = "RangePPC",
                               label = "What's your prefered precipitation range?",
                               min = 0,
                               max = 5000,
                               value = c(0, 5000))),

  conditionalPanel(condition = "input.degrees == 'Fahrenheit'",
                   sliderInput(inputId = "MaxTempF",
                               label = "What's the average maximum temperature you want to endure during the summer?",
                               min = 0,
                               max = 120,
                               value = 90),
                   sliderInput(inputId = "MinTempF",
                               label = "What's the average minimum temperature you want to endure during the winter?",
                               min = -40,
                               max = 60,
                               value = 32),
                   sliderInput(inputId = "RangeTempF",
                               label = "What's your prefered temperature range?",
                               min = -40,
                               max = 90,
                               value = c(32, 70)),                       
                   sliderInput(inputId = "RangePPF",
                               label = "What's your prefered precipitation range?",
                               min = 0,
                               max = 200,
                               value = c(0, 200))),
                  sliderInput(inputId = "Population",
                               label = "how big of a town do you want to live in (Population)?",
                               min = 0,
                               max = 20000000,
                               value = c(0, 20000000, by = 1)))
,

# Show a plot of the generated distribution
mainPanel(
  plotOutput("distPlot"),
  downloadButton('downloadPlot', 'Download Plot'),
  dataTableOutput("visFun"),
  downloadButton('downloadData', 'Download Table')
)
)
))

到目前为止一切顺利，但是当我尝试将其更改为使用传单 map 时效果不佳，实际上传单 map 没有出现，我尝试过:

服务器:

library(shiny)
library(raster)
library(rworldmap)
library(rgdal)
library(dplyr)
library(leaflet)
library(sp)
data("countriesCoarse")
uno <- readRDS("uno.rds")
World <- getData('worldclim', var='bio', res=10)
cities <- readRDS("cities.rds")
shinyServer(function(input, output) {

  output$map <- renderLeaflet({
    uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
    uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
    uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
    l <- leaflet() %>% setView(0, 0, zoom = 1)    
    l <- l %>% addRasterImage(uno)
    l
})
  output$downloadPlot <- downloadHandler(
    filename = function() { paste("WhereToLive", '.png', sep='') },
content = function(file) {
    png(file)
    uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
    uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
    uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
    plot(uno, col ="red", legend = FALSE)
    plot(countriesCoarse, add = TRUE)
    dev.off()
})
  output$visFun <- renderDataTable({
    uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
    uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
    uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
    uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
    cities$exists <- extract(uno, cities[,2:3])
    cities <- filter(cities, exists == 1)
    cities <- cities[,c(1,4,5,6)]
    cities <- filter(cities, pop > min(as.numeric(as.character(input$Population))))
    cities <- filter(cities, pop < max(as.numeric(as.character(input$Population))))
    cities
})
  output$downloadData <- downloadHandler(
    filename = function() { paste("cities", '.csv', sep='') },
    content = function(file) {
      uno[World[[10]] > ifelse(input$degrees == "Celcius", (input$MaxTempC*10), (((input$MaxTempF-32)*5/9)*10))] <- NA
      uno[World[[11]] < ifelse(input$degrees == "Celcius", (input$MinTempC*10), (((input$MinTempF-32)*5/9)*10))] <- NA
      uno[World[[1]] < ifelse(input$degrees == "Celcius", min(input$RangeTempC*10), min(((input$RangeTempF-32)*5/9)*10))] <- NA
      uno[World[[1]] > ifelse(input$degrees == "Celcius", max(input$RangeTempC*10), max(((input$RangeTempF-32)*5/9)*10))] <- NA
      uno[World[[12]] < ifelse(input$degrees == "Celcius", min(input$RangePPC), min(input$RangePPF*25.4))] <- NA
      uno[World[[12]] > ifelse(input$degrees == "Celcius", max(input$RangePPC), max(input$RangePPF*25.4))] <- NA
      cities$exists <- extract(uno, cities[,2:3])
      cities <- filter(cities, exists == 1)
      cities <- filter(cities$pop > min(input$Population))
      cities <- filter(cities$pop < max(input$Population))
      cities <- cities[,c(1,4,5,6)]
      write.csv(cities, file)
}
)
})

和

用户界面:

library(shiny)
library(raster)
library(rworldmap)
library(rgdal)
library(leaflet)
data("countriesCoarse")


shinyUI(fluidPage(

  titlePanel("Where should you live according to your climate preferences?"),


  sidebarLayout(
    sidebarPanel(
      h3("Select your climate preferences"),
      p("Using worldclim database, and knowing your climate prefeneces, you can now using this tool get an idea of where in the world you should live."),
      p("Just use the sliders to anwer the simple questions we ask and you will get a map together with a downloadable table of where the climate suits you."),
      selectInput(inputId = "degrees", label = "Temp units:", choices = 
                c("Celcius"= "Celcius",
                  "Fahrenheit" = "Fahrenheit")),
      submitButton("Update View", icon("refresh")),
      conditionalPanel(condition = "input.degrees == 'Celcius'",
                   sliderInput(inputId = "MaxTempC",
                               label = "What's the average maximum temperature you want to endure during the summer?",
                               min = 0,
                               max = 50,
                               value = 30),
                   sliderInput(inputId = "MinTempC",
                               label = "What's the average minimum temperature you want to endure during the winter?",
                               min = -40,
                               max = 60,
                               value = 0),
                   sliderInput(inputId = "RangeTempC",
                               label = "What's your prefered temperature range?",
                               min = -10,
                               max = 30,
                               value = c(0, 20)),
                   sliderInput(inputId = "RangePPC",
                               label = "What's your prefered precipitation range?",
                               min = 0,
                               max = 5000,
                               value = c(0, 5000))),

  conditionalPanel(condition = "input.degrees == 'Fahrenheit'",
                   sliderInput(inputId = "MaxTempF",
                               label = "What's the average maximum temperature you want to endure during the summer?",
                               min = 0,
                               max = 120,
                               value = 90),
                   sliderInput(inputId = "MinTempF",
                               label = "What's the average minimum temperature you want to endure during the winter?",
                               min = -40,
                               max = 60,
                               value = 32),
                   sliderInput(inputId = "RangeTempF",
                               label = "What's your prefered temperature range?",
                               min = -40,
                               max = 90,
                               value = c(32, 70)),                       
                   sliderInput(inputId = "RangePPF",
                               label = "What's your prefered precipitation range?",
                               min = 0,
                               max = 200,
                               value = c(0, 200))),
                  sliderInput(inputId = "Population",
                               label = "how big of a town do you want to live in (Population)?",
                               min = 0,
                               max = 20000000,
                               value = c(0, 20000000, by = 1)))
,

# Show a plot of the generated distribution
mainPanel(
  leafletOutput("map", width = "100%", height = "100%"),
  downloadButton('downloadPlot', 'Download Plot'),
  dataTableOutput("visFun"),
  downloadButton('downloadData', 'Download Table')
)
)
))

这没有抛出任何错误，但 map 没有渲染，我有以下警告

Listening on http://127.0.0.1:7231
Warning in rgdal::rawTransform(projfrom, projto, nrow(xy), xy[, 1], xy[,  :
54 projected point(s) not finite
Warning in rgdal::rawTransform(projfrom, projto, nrow(xy), xy[, 1], xy[,  :
54 projected point(s) not finite
Warning in rgdal::rawTransform(projfrom, projto, nrow(xy), xy[, 1], xy[,  :
54 projected point(s) not finite

最佳答案

问题是 height你的情节不能是相对的。

只需将其替换为绝对值即可显示，例如:

leafletOutput("map", width = "100%", height = 400)

关于r - map 不会在带有传单和光栅的 Shiny 应用程序中呈现，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/39337259/

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r - map 不会在带有传单和光栅的 Shiny 应用程序中呈现