An R package for fast web gl rendering of features on leaflet maps. It's an R port of https://github.com/robertleeplummerjr/Leaflet.glify where more detailed information/documentation can be found. Also, if you like what you get here, make sure to star the original repo!
Currently not on CRAN, github only:
devtools::install_github("r-spatial/leafgl")It allows rendering of a large amount of features on a leaflet map. What exactly a "large amount" is, depends
- on the types of features and
- on the hardware/software of the rendering machine.
Regarding 1. millions of points should be no problem, but millions of polygons might, depending on their complexity - i.e. the number of vertices.
With regard to 2., obviously the amount of RAM will matter most but there are other, more suptle, problems that can occur.
Given it's name, leafgl is intended to fully integrate with the
leaflet package, though it is very likely that it won't be a 1:1
replacement for the respective leaflet::add* functions. For example,
given the intention to render/visualise as many features as possible we
need to make a compromise on what additional information we allow to be
part of the rendering. So far, we allow coloring of features and popups
based on one column of the feature attributes, hence you cannot provide
your own popup content. This may seem drastic, but all this information
is costly both in terms of performance/speed and memory. In the end, who
wants to wait for a map that the browser isn't able to render anyway...
For starters, it doesn't guarantee to be working tomorrow. At this stage
lealet.glify is pre-alpha and under heavy development so things are
likely to change frequently. For example, we are thinking about shorter
funtion names (e.g. addGlPolygons instead of the current
addGlifyPolygons). Additionally, we are still figuring out which
pathway is best to use in order to pass data from R to the browser. As
a result, rendering environments other than the browser (or RStudio
viewer) may not work properly or at all until we approach a more stable
implementation.
Depending on your operating system and browser, you may
see some weird colors that do not correspond to the ones that you
specified. The only known work-around at this stage is to set opacity = 1.
For more details the inclined reader is referred to this issue
A lot! First and foremost you can use it as often as possible and report issues/bugreports and/or feature request (see end of page for details). If you have ideas on how to enhance functionality without impacting performance too much and feel confident enough to provide pull request, please don't hesitate. Finally, if you have proficient knowledge of JavaScript and want/know how to improve the package in any way, we would very much love to hear from you!
This will render 1 Mio. points on a standard leaflet map.
library(mapview)
library(leaflet)
library(leafgl)
library(sf)
n = 1e6
df1 = data.frame(id = 1:n,
x = rnorm(n, 10, 3),
y = rnorm(n, 49, 1.8))
pts = st_as_sf(df1, coords = c("x", "y"), crs = 4326)
options(viewer = NULL) # view in browser
system.time({
m = leaflet() %>%
addProviderTiles(provider = providers$CartoDB.DarkMatter) %>%
addGlPoints(data = pts, group = "pts") %>%
addMouseCoordinates() %>%
setView(lng = 10.5, lat = 49.5, zoom = 6) %>%
addLayersControl(overlayGroups = "pts")
})
m
For this we use library(colourvalues) because it can create color
voctors in the blink of an eye!
library(mapview)
library(leaflet)
library(leafgl)
library(sf)
library(colourvalues)
n = 1e6
df1 = data.frame(id = 1:n,
x = rnorm(n, 10, 3),
y = rnorm(n, 49, 1.8))
pts = st_as_sf(df1, coords = c("x", "y"), crs = 4326)
cols = colour_values_rgb(pts$id, include_alpha = FALSE) / 255
options(viewer = NULL)
system.time({
m = leaflet() %>%
addProviderTiles(provider = providers$CartoDB.DarkMatter) %>%
addGlPoints(data = pts, color = cols, group = "pts") %>%
addMouseCoordinates() %>%
setView(lng = 10.5, lat = 49.5, zoom = 6) %>%
addLayersControl(overlayGroups = "pts")
})
m
In reality, it only 97112 polygons... But who wants to be pedantic here?
This data was downloaded from https://download.geofabrik.de/europe/switzerland.html
library(mapview)
library(leaflet)
library(leafgl)
library(sf)
library(colourvalues)
ch_lu = st_read("/media/timpanse/d8346522-ef28-4d63-9bf3-19fec6e13aab/bu_lenovo/software/testing/mapview/switzerland/landuse.shp")
ch_lu = ch_lu[, c(1, 3, 4)] # don't handle NAs so far
options(viewer = NULL)
cols = colour_values_rgb(ch_lu$type, include_alpha = FALSE) / 255
system.time({
m = leaflet() %>%
addProviderTiles(provider = providers$CartoDB.DarkMatter) %>%
addGlPolygons(data = ch_lu,
color = cols,
popup = "type",
group = "pols") %>%
addMouseCoordinates() %>%
setView(lng = 8.3, lat = 46.85, zoom = 9) %>%
addLayersControl(overlayGroups = "pols")
})
m
Thanks to @ColinFay leafgl has dedicated shiny functions. Given that what leafgl produces is a leaflet map, we only need to
use leafglOutput in our ui call. In the server call we can simply use renderLeaflet. Here an example:
library(mapview)
library(leaflet)
library(leafgl)
library(sf)
library(shiny)
n = 1e6
df1 = data.frame(id = 1:n,
x = rnorm(n, 10, 3),
y = rnorm(n, 49, 1.8))
pts = st_as_sf(df1, coords = c("x", "y"), crs = 4326)
options(viewer = NULL) # view in browser
m = leaflet() %>%
addProviderTiles(provider = providers$CartoDB.DarkMatter) %>%
addGlPoints(data = pts, group = "pts") %>%
addMouseCoordinates() %>%
setView(lng = 10.5, lat = 49.5, zoom = 4) %>%
addLayersControl(overlayGroups = "pts")
ui <- fluidPage(
leafglOutput("mymap")
)
server <- function(input, output, session) {
output$mymap <- renderLeaflet(m)
}
shinyApp(ui, server)Please file Pull requests, bug reports and feature requests at https://github.com/r-spatial/leafgl/issues