那些遇到过的问题

地图不会在带有传单和栅格的闪亮应用中呈现

Der*_*ran 6 r leaflet shiny

我正在一个闪亮的应用程序工作,让你知道你可以愉快地生活的地方,这是正确的工作应用程序知道:

闪亮的应用

到目前为止我喜欢它,但我真的宁愿有一个传单地图,你可以放大而不是静态地图,但到目前为止,我一直有很多问题,由传单包呈现或更新光栅.如果您需要文件存储库,那么github存储库就是这个存储库

这是现在应用程序的代码服务器:

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)
}
)
})
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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')
)
)
))
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到目前为止一切都那么好,但是当我尝试更改它以使用传单地图时它不能很好地工作,事实上传单地图没有出现,我试过这个:

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)
}
)
})
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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')
)
)
))
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这不会引发任何错误,但地图不会渲染,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
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Hub*_*rtL 2

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)
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归档时间：

查看次数：

330 次

最近记录：

9 年，4 月 前
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