NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")), "true") knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = NOT_CRAN )
In this manual we will discuss an example of using starsTileServer
for serving map tiles in a shiny app. It shows the ability to visualize different layers and dynamically change layers. To do this we will use a sample dataset from the ERA5 weather model, that includes different variables and pressure levels.
library(starsTileServer)
The sample dataset can be retrieved with the following code using the ecmwfr
R package:
require(ecmwfr) request <- list( "dataset_short_name" = "reanalysis-era5-pressure-levels", "product_type" = "reanalysis", "variable" = c("temperature", "geopotential", "u_component_of_wind", "v_component_of_wind"), "pressure_level" = c("875", "900", "925"), "year" = "2000", "month" = "04", "day" = as.character(27:29), "time" = sprintf("%02i:00", 0:23), "area" = "64/-130/-64/144", "format" = "netcdf", "target" = "ecmwfData.nc" ) # make sure you use your own uid and key ( https://cds.climate.copernicus.eu/#!/home ) wf_set_key("uid_to_replace", "key_to_replace", service = "cds") ncfile <- wf_request( user = "uid_to_replace", request = request, transfer = TRUE, path = "~", verbose = FALSE )
if (!file.exists(tmpGridFile <- "~/ownCloudUva/test.nc")) { tmpGridFile <- tempfile(fileext = ".nc") download.file("https://surfdrive.surf.nl/files/index.php/s/Z6YoTyzyyAsmgGS/download", tmpGridFile, extra = "-q", method = "wget") }
To set up the tile server we need the grid file loaded. Additionally a color function can be added. This function needs to have the same format as the color as the color mapping functions in leaflet
.
weatherData <- stars::read_stars(tmpGridFile) sf::st_crs(weatherData) <- "+proj=longlat" colFun <- function(x, alpha = 1, max = 20, min = -20) { paste0( suppressWarnings(leaflet::colorNumeric( "RdYlBu", domain = c(as.numeric(min), as.numeric(max)) )(x)), as.character(as.raw(as.numeric(alpha) * 255)) ) } attr(colFun, "colorType") <- "numeric"
The tileserver needs to run in a separate process. On a personal computer this can easily be achieved by running two R processes at the same time. An alternative approach is to use callr
to start a separate process.
# note the process is ran in the background, do not forget to close it as it might use quite a bit of memory. # I have made the experience that callr seems to work poorly if the process is rather verbose require(callr) rp <- r_bg(args = list(grid = weatherData, colFun = colFun), function(grid, colFun) { starsTileServer::starsTileServer$new(grid, colFun)$run(port = 3746, docs = TRUE) })
Sys.sleep(3) stopifnot(rp$is_alive())
The process will print an url where documentation an testing for the server is available:
message(rp$read_error())
Now a small example of some interaction based on a shiny example. First we create UI, this consists of a few selection options to change the map features.
require(shiny) require(leaflet) require(stars) weather <- stars::read_stars(tmpGridFile, proxy = T) ui <- fluidPage( # Application title titlePanel("Web map"), sidebarLayout( # Sidebar with a slider input sidebarPanel( sliderInput("alpha", "Transparancy", 0, 1, .6, .01), selectInput("attr", "Attribute", choices = c("u", "v")), sliderInput( "time", "Time", value = min(st_get_dimension_values(weather, 4)), min = min(st_get_dimension_values(weather, 4)), max = max(st_get_dimension_values(weather, 4)), step = 3600, timezone = "+0000", animate = animationOptions(5000) ), selectInput("level", "level (mb)", choices = as.character(st_get_dimension_values(weather, 3))), sliderInput("colRange", "Range", -50, 50, c(-20, 20)) ), # Show a plot of the generated distribution mainPanel(leafletOutput("map")) ) )
We use the following shiny server function:
server <- function(input, output, session) { # This reactive creates the URL to the tileserver, it include the different input variables in requests to the server # The debounce ensures the URL does not get updated to frequent url <- reactive({ sprintf( "http://127.0.0.1:3746/map/%s/{z}/{x}/{y}?level=%s&alpha=%f&time=%s&min=%f&max=%f", input$attr, input$level, input$alpha, strftime(input$time, tz = "UTC", format = "%Y-%m-%d %H:%M:%S"), min(input$colRange), max(input$colRange) ) }) %>% debounce(100) # This reactive downloads the color function from the server and prepares it for adding as a legend to the leaflet map colorFunction <- reactive({ f <- readRDS(base::url(sprintf("http://127.0.0.1:3746/map/%s/colorfunctionnoalpha", input$attr))) at <- attributes(f) if (is.finite(max(colrange()))) { formals(f)$max <- max(colrange()) } if (is.finite(min(colrange()))) { formals(f)$min <- min(colrange()) } attributes(f) <- at f }) colrange <- reactive(range(input$colRange)) output$map <- renderLeaflet({ leaflet() %>% addTiles() %>% fitBounds(-50, -30, 50, 50) }) # This observer changes the tile layer as soon as the url is updated observe({ leafletProxy("map") %>% clearGroup("wind") %>% addTiles(url(), group = "wind", options = tileOptions(useCache = TRUE, crossOrigin = TRUE) ) }) # This observe changes the legend as soon as it is updated observe({ s <- seq(min(colrange()), max(colrange()), length.out = 20) leafletProxy("map") %>% clearControls() %>% addLegend( pal = colorFunction(), values = s, title = input$attr, position = "bottomleft" ) }) }
The app can be create using the regular shiny functionality
app <- shinyApp(ui, server)
The result of this shiny app looks as follows:
f <- tempfile(fileext = ".png") suppressMessages(webshot::appshot( app, file = f, delay = 45, vwidth = 1000, vheight = 600 )) magick::image_read(f)
To wrap up we close the tile server
rp$finalize()
Any scripts or data that you put into this service are public.
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