我正在一个闪亮的应用程序中工作，让你知道你可以生活愉快的地方，这是正确的工作应用程序：
到目前为止我喜欢它，但我真的很想有一个传单地图，你可以放大而不是静态地图，但到目前为止，我一直在渲染或更新栅格时遇到很多问题通过传单包。如果您需要文件repository
，那么github存储库就是这个存储库这是应用程序的代码，现在服务器：
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)
}
)
})
UI：
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)
}
)
})
和
UI：
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
答案 0 :(得分：2)
问题是你的情节height不能相对。
只需将其替换为绝对值即可显示，例如：
leafletOutput("map", width = "100%", height = 400)