3d Scatter Plot

Draws 3d scatter plots and surfaces.

cloud(formula, data,
      aspect = c(1, 1),
      scales = list(distance = rep(1, 3), arrows = TRUE),
      zoom = 0.8,
wireframe(formula, data,
          at = pretty(z, cuts),
          drape = FALSE,
          shade = FALSE,
          pretty = FALSE,
          colorkey = any(drape),
          cuts = 70,
a formula of the form z ~ x * y | g1 * g2 * ..., where z is a numeric response, and x, y are numeric values. g1, g2, ..., if present, are conditioning variables used for conditioning, and mus
data frame in which variables are evaluated. Ignored is formula is not really a formula object.
vector of length 2, giving the relative aspects of the y-size/x-size and z-size/x-size of the enclosing cube.
a list describing the scales. As with other high level functions (see xyplot for details), this list can contain parameters in name=value form. It can also contain components with the special n
label describing the z variable. Similar to xlab and ylab in other high level functions
limits for the z-axis. Similar to xlim and ylim in other high level functions
factor by which to scale the picture. Useful to get the variable names into the plot. This is actually only used in the default prepanel function.
logical, whether the wireframe is to be draped in color. If TRUE, the height of a facet is used to determine its color in a manner similar to the coloring scheme used in levelplot
logical, whether the wireframe is to be rendered as being illuminated from a light source. See panel.3dwire for details
at, col.regions, alpha.regions
these arguments are analogous to those in levelplot. if drape=TRUE, at gives the vector of cutpoints where the colors change, and col.regions the vector
if at is unspecified, the approximate number of cutpoints if drape=TRUE
whether automatic choice of cutpoints should be prettfied
logical indicating whether a color key should be drawn alongside, or a list describing such a key. See levelplot for details.
other arguments, passed to the panel function. In particular, the arguments distance, perspective, screen and R.mat are very important in determining the 3-D display. These arguments are desc

These functions produce three dimensional plots in each panel (as long as the default panel functions are used). The orientation is obtained as follows: the data are scaled to fall within a bounding box that is contained in the [-0.5, 0.5] cube (even smaller for non-default values of aspect). The viewing direction is given by a sequence of rotations specified by the screen argument, starting from the positive Z-axis. The viewing point (camera) is located at a distance of 1/distance from the origin. If perspective=FALSE, distance is set to 0 (i.e., the viewing point is at an infinite distance).

cloud draws a 3-D Scatter Plot, while wireframe draws a 3-D surface (usually evaluated on a grid). Multiple surfaces can be drawn by wireframe using the groups argument (although this is of limited use because the display is incorrect when the surfaces intersect). Specifying groups with cloud results in a panel.superpose-like effect (via panel.3dscatter).

wireframe can optionally render the surface as being illuminated by a light source (no shadows though). Details can be found in the help page for panel.3dwire. Note that although arguments controlling these are actually arguments for the panel function, they can be supplied to cloud and wireframe directly.

For single panel plots, wireframe can also plot parametrized 3-D surfaces (i.e., functions of the form f(u,v) = (x(u,v), y(u,v), z(u,v)), where values of (u,v) lie on a rectangle. The simplest example of this sort of surface is a sphere parametrized by latitude and longitude. This can be achieved by calling wireframe with a formula of the form z~x*y, where x, y and z are all matrices of the same dimension, representing the values of x(u,v), y(u,v) and z(u,v) evaluated on a discrete rectangular grid (the actual values of (u,v) are irrelevant).

When this feature is used, the heights used to calculate drape colors or shading colors are no longer the z values, but the distances of (x,y,z) from the origin.

Note that this feature does not work with groups, subscripts, subset, etc. Conditioning variables are also not supported in this case.

The algorithm for identifying which edges of the bounding box are `behind' the points doesn't work in some extreme situations. Also, tries to figure out the optimal location of the arrows and axis labels automatically, but can fail on occasion (especially when the view is from ``below'' the data). This can be manually controlled by the scpos argument in

These and all other high level Trellis functions have several other arguments in common. These are extensively documented only in the help page for xyplot, which should be consulted to learn more detailed usage.


  • An object of class ``trellis''. The `update' method can be used to update components of the object and the `print' method (usually called by default) will plot it on an appropriate plotting device.


cloud(formula, data = parent.frame(), allow.multiple = is.null(groups) || outer, outer = FALSE, auto.key = FALSE, aspect = c(1,1), panel = "", prepanel = NULL, scales = list(), strip = TRUE, groups = NULL, xlab, xlim = if (is.factor(x)) levels(x) else range(x, na.rm = TRUE), ylab, ylim = if (is.factor(y)) levels(y) else range(y, na.rm = TRUE), zlab, zlim = if (is.factor(z)) levels(z) else range(z, na.rm = TRUE), at, drape = FALSE, pretty = FALSE, drop.unused.levels = lattice.getOption("drop.unused.levels"), ..., default.scales = list(distance = c(1, 1, 1), arrows = TRUE, axs = axs.default), colorkey = any(drape), col.regions, alpha.regions, cuts = 70, subset = TRUE, axs.default = "r") wireframe(formula, data = parent.frame(), panel = "panel.wireframe", prepanel = NULL, strip = TRUE, groups = NULL, cuts = 70, pretty = FALSE, drape = FALSE, ..., colorkey = any(drape), subset = TRUE)

See Also

xyplot, levelplot,, Lattice

  • cloud
  • wireframe
## volcano  ## 87 x 61 matrix
wireframe(volcano, shade = TRUE,
          aspect = c(61/87, 0.4),
          light.source = c(10,0,10))

g <- expand.grid(x = 1:10, y = 5:15, gr = 1:2)
g$z <- log((g$x^g$g + g$y^2) * g$gr)
wireframe(z ~ x * y, data = g, groups = gr,
          scales = list(arrows = FALSE),
          drape = TRUE, colorkey = TRUE,
          screen = list(z = 30, x = -60))

cloud(Sepal.Length ~ Petal.Length * Petal.Width | Species, data = iris,
      screen = list(x = -90, y = 70), distance = .4, zoom = .6)

par.set <-
    list(axis.line = list(col = "transparent"), clip = list(panel = FALSE))
print(cloud(Sepal.Length ~ Petal.Length * Petal.Width, 
            data = iris, cex = .8, 
            groups = Species, 
            main = "Stereo",
            screen = list(z = 20, x = -70, y = 3),
            par.settings = par.set),
      split = c(1,1,2,1), more = TRUE)
print(cloud(Sepal.Length ~ Petal.Length * Petal.Width,
            data = iris, cex = .8, 
            groups = Species,
            main = "Stereo",
            screen = list(z = 20, x = -70, y = 0),
            par.settings = par.set),
      split = c(2,1,2,1))
Documentation reproduced from package lattice, version 0.10-10, License: GPL version 2 or later

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