The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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
<- sort(rnorm(1000))
x <- rnorm(1000)
y <- rnorm(1000) + atan2(x, y)
z
<- plot3js(x, y, z, col = rainbow(1000))
p 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’).
Several ways to add interactivity to plots are currently supported, namely labels, highlighting on mouse roll-over, and toggle buttons.
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:
<- plot3js(
p x = runif(100),
y = runif(100),
z = runif(100),
size = 3,
col = rainbow(100),
label = paste("Point", 1:100),
)
r3js(p)
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
:
<- plot3js(
p 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)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.