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I am working in a shiny app which lets you know places where it could be pleasant for you to live, this is the working app right know:
shiny app
I like it so far, but I really would rather have a leaflet map where you could zoom in instead of a static map, but so far I've been having a lot of problems with the raster being rendered or updated by the leaflet package. The github repository is this one if you need the files repository
This is the code of the app right now Server:
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')
)
)
))
So far so good, but when I try to change it to use the leaflet map it does not work very well, in fact the leaflet map does not appear, I have tried this:
Server:
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)
}
)
})
and
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')
)
)
))
This is not throwing any errors, but the map is not rendering, and I have the following warnings
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
773
The problem is the height of your plot that can't be relative.
Just replace it by an absolute value and it will be displayed, for example:
leafletOutput("map", width = "100%", height = 400)
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