Getting Started

Generally, r3js works by generating an object containing the plotting data and then continuously updating it as new features are added to the plot (similar to plotly). For a simple 3D scatterplot however, the plot3js function handles all of the plotting setup for you. Plotting syntax is intended to be similar to the base plotting functions in R, and that used in the RGL package.

# Generate and view a simple 3D scatterplot
x <- sort(rnorm(1000))
y <- rnorm(1000)
z <- rnorm(1000) + atan2(x, y)
  
p <- plot3js(x, y, z, col = rainbow(1000))
r3js(p)

You can also build up a plot step by step using the lower level functions for initiating 3D plots (see vignettes ‘Creating a plot from scratch’).

Interactivity

Several ways to add interactivity to plots are currently supported, namely labels, highlighting on mouse roll-over, and toggle buttons.

Labels

Labels can be added, which will display when you hover the mouse over the plot element, simply by providing a string or string vector as input to the plotting function for the label argument:

p <- plot3js(
  x = runif(100),
  y = runif(100),
  z = runif(100),
  size = 3,
  col = rainbow(100),
  label = paste("Point", 1:100),
)

r3js(p)

Roll-over highlighting

Features of a plotted object can be programmed to change upon a mouse roll-over simply by passing the arguments you wish to update as a list to the highlight argument and set interactive = TRUE:

p <- plot3js(
  x = runif(100),
  y = runif(100),
  z = runif(100),
  size = 3,
  col = rainbow(100),
  highlight = list(
    size = 4,
    col = rev(rainbow(100)),
    mat = "basic"
  ),
  interactive = TRUE
)

r3js(p)

Toggle buttons

To associate an object with a toggle button simply pass the desired toggle label to the toggle argument:

x <- runif(100)
y <- runif(100)
z <- runif(100)

col <- c(
  rep("blue", 50),
  rep("red", 50)
)

toggle <- paste(col, "points")

p <- plot3js(
  x = x,
  y = y,
  z = z,
  size = 3,
  col = col,
  toggle = toggle
)

r3js(p)