The r-deckgl package makes the open-source JavaScript library deck.gl available within R via the htmlwidgets package.
You can install the latest version of r-deckgl from github with:
Create a deckgl instance:
Add a basemap:
Add any kind of layers:
# Grid layer example
data("sf_bike_parking")
props <- list(
extruded = TRUE,
cellSize = 200,
elevationScale = 4,
getPosition = ~lng + lat,
tooltip = "Count: {{count}}"
)
deckgl(zoom = 11, pitch = 45) %>%
add_basemap() %>%
add_grid_layer(
data = sf_bike_parking,
properties = props
)deckgl InstanceThe deckgl function creates the widget / renderer to which you add layers and other configuration parameters:
rdeck <- deckgl(
latitude = 37.8,
longitude = -122.45,
zoom = 12
) %>%
add_grid_layer(
data = data,
properties = props
)Due to the generic function add_layer any kind of layer defined in the deck.gl Layer Catalog is supported. The layer type is chosen via the class_name parameter, e. g. ScatterplotLayer or GeoJsonLayer. Usually you will not use the generic function but one of the add_*_layer shortcuts instead:
# Generic function
deckgl() %>%
add_layer("ArcLayer", id, data, properties)
# Shortcut function
deckgl() %>%
add_arc_layer(id, data, properties)The data parameter can either be an url to fetch data from or a data object. In most cases you will pass an object of type data.frame to the layers. Use the formula syntax to define data accessors that deck.gl uses to access the properties of the data object:
sf Data ObjectsAn object of class sf is a data.frame with a geometry list-column. Set the layer prop that fetches the geometry to the geometry list-column of your sf object:
With add_source you can add a source to the widget that can be used accross layers:
data("bart_stations")
deckgl() %>%
add_source("bart-stations", bart_stations) %>%
add_scatterplot_layer(
source = "bart-stations",
getPosition = ~lng + lat,
# ...
) %>%
add_text_layer(
source = "bart-stations",
getPosition = ~lng + lat,
# ...
) %>%
add_basemap()Please note that you use the parameter source instead of data.
Layer properties are passed to the add_*_layer functions either as named list by the properties argument or as named parameters / keyword arguments via the ... parameter. The names correspond to the properties of the deck.gl counterparts. Therefore, please see the deck.gl Layer Catalog to determine the available parameters for the used layer. You can also pass a props list and keyword arguments together. Identical properties are overwritten by the latter ones.
Grid Layer example:
// JavaScript code
const layer = new GridLayer({
id: "grid-layer",
data: data,
extruded: true,
cellSize: 200,
elevationScale: 4,
getPosition: d => [d.lng, d.lat]
});# Corresponding R code
# using named arguments
deck <- deckgl() %>%
add_grid_layer(
id = "grid-layer",
data = data,
extruded = TRUE,
cellSize = 200,
elevationScale = 4,
getPosition = ~lng + lat
)
# ... using a named props list
props <- list(
cellSize = 200,
extruded = TRUE,
# ...
)
deckgl() %>%
add_grid_layer(
data = data,
properties = props
)According to the style conventions in R, camelCased parameters in deck.gl can also be passed as snake_cased parameters in R. For example, getPosition can be passed to deck.gl as get_position:
Use the formula syntax to define data accessors:
props <- list(
getPosition = ~lng + lat # js: d => [d.lng, d.lat]
getFillColor = ~color # js: d => d.color
# ...
)The example above assumes that your data contains the columns lng, lat and color.
It is also possible to pass JavaScript code by using the JS function in R:
In deck.gl colors are represented by [r, g, b, a] arrays. In R you can pass hex color codes or color names to all color props of the add_*_layer functions. They are automatically converted to the required format:
The tooltip for a layer can be set via the tooltip parameter. You can either pass a single template string or a list with the following properties (see also use_tooltip):
html: A template string that will be set as the innerHTML of the tooltip.style: A cssText string that will modefiy the default style of the tooltip.The tooltip string is a so called “mustache” template in which variable names are identified by the double curly brackets that surround them. The variable names available to the template are given by deck.gl’s pickingInfo.object and vary by layer.
Arc Layer example:
data("bart_segments")
props <- list(
getWidth = 12,
getSourcePosition = ~from_lng + from_lat,
getTargetPosition = ~to_lng + to_lat,
getSourceColor = "yellow",
getTargetColor = "orange",
tooltip = use_tooltip(
html = "{{from_name}} to {{to_name}}",
style = "background: steelBlue; border-radius: 5px;"
)
)
deckgl(zoom = 9.5, pitch = 35) %>%
add_arc_layer(data = bart_segments, properties = props) %>%
add_basemap()See mustache.js for a complete syntax overwiew.
Controls are displayed as overlays on top of the map / deck. Usually you can set the position and the style of the control. The most basic control is a simple text box:
deckgl() %>%
add_basemap() %>%
add_control(
html = "Plain Base Map",
pos = "top-right",
style = "background: steelblue; color: white"
)You can add an instance of the ace editor in JSON mode to the map by using add_json_editor:
This allows you to change your layer props on the fly. You can toggle the visibility of the editor by pressing “e”.
With add_legend you can add a custom legend to your widget:
deckgl() %>%
add_basemap() %>%
add_legend(
colors = c("yellow", "orange"),
labels = c("Cake", "Icecream"),
title = "Sweets"
)In most cases, you will create the legend automatically using a palette function:
data_column <- 1:10
pal <- scales::col_bin("Blues", data_column, bins = 5)
deckgl() %>%
add_basemap() %>%
add_legend_pal(pal, title = "Blues")By default, add_basemap adds a carto basemap to the widget.
To use basemaps from mapbox it is recommended that you store your API access token in an environment variable called MAPBOX_API_TOKEN:
# If not set globally
#Sys.setenv(MAPBOX_API_TOKEN = "xyz")
deckgl() %>%
add_mapbox_basemap("mapbox://styles/mapbox/light-v9")You can run the API examples from the add_*_layer functions with example(add_*_layer):
With the renderDeckgl and deckglOutput functions you can use r-deckgl in shiny applications:
library(shiny)
library(deckgl)
backend <- function(input, output) {
output$rdeck <- renderDeckgl({
deckgl() %>%
add_grid_layer(
data = sf_bike_parking,
getPosition = ~lng + lat,
cellSize = 400,
pickable = TRUE
) %>%
add_basemap()
})
}
frontend <- fluidPage(
deckglOutput("rdeck")
)
shinyApp(frontend, backend)To update a deckgl instance use deckgl_proxy in combination with update_deckgl.
Furthermore, the onclick event sends deck.gl’s picking info object to your shiny application and updates the corresponding input in the form of input$widget_id_onclick. For example, if the widget id is rdeck, you can access the pickingInfo object with input$rdeck_onclick:
backend < -function(input, output) {
# ...
observeEvent(input$rdeck_onclick, {
info <- input$rdeck_onclick
print(info$object)
})
}The JavaScript library of r-deckgl uses webpack as module bundler. Therefore, you need node.js to build the module. All JavaScript code is located in the javascript/src folder and test components go to javascript/src/test-components.
Install deps and build the library from inside the javascript folder with:
To spin up the webpack-dev-server run:
If the deckgl widget is not visible in the viewer pane of RStudio, just open it in your browser by clicking “Show in new window” and everything will be fine.