lattice (version 0.7-1)

cloud: 3d Scatter Plot

Description

Draws 3d scatter plots and surfaces.

Usage

cloud(formula,
      data,
      aspect = c(1, 1),
      scales = list(cex = 0.5, lty = 1, lwd = 1,
                    col = "black", distance = rep(1, 3),
                    arrows = TRUE, draw = TRUE),
      zlab,
      zlim = range(z), 
      distance = 0.2,
      par.box,
      perspective = TRUE,
      R.mat = diag(4), 
      screen = list(z = 40, x = -60),
      zoom = .9,
      ...)
wireframe(formula, data,
          at = pretty(z, cuts),
          col.regions,
          drape = FALSE,
          pretty = FALSE,
          colorkey = any(drape),
          cuts = 70,
          distance = 0.2,
          par.box,
          screen = list(z = 40, x = -60),
          zoom = .9,
          scales = list(cex = 0.5, distance = rep(1, 3), arrows = TRUE),
          ...)

Arguments

formula

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, must be either factors or shingles. In the ca

data

data frame in which variables are evaluated

aspect

vector of length 2, giving the relative aspects of the y-size/x-size and z-size/x-size of the enclosing rectangle.

scales

describes scales. Can contain lists named x, y and z. Arrows are drawn if arrows=TRUE, otherwise tick marks with labels are drawn. Both can be suppressed by draw=FALSE. Several other components that work in the usual

zlab

z label

zlim

z limits

distance

between 0 and 1, controls amount of perspective. No connection with the physical concept of distance in this implementation (not clear what S+ does). individual values don't give the same results as S-Plus, but all instances should be achievab

par.box

graphical parameters for box, namely, col, lty and lwd. By default obtained from the parameter box.3d

perspective

logical, whether to plot a perspective view

R.mat

initial rotation matrix in homogeneous coordinates. Implemented but untested.

screen

A list determining the rotations to applied to the data before being plotted. The initial position starts with the viewing point somewhere in the positive z-axis, and the x and y axes in the usual position. Each component of the list should be

zoom

factor by which to scale the picture. Useful to get the variable names into the plot

drape

whether the wireframe is to be draped in color

at

these arguments are analogous to those in levelplot. if drape=TRUE, at gives the vector of values where the colors change

col.regions

the vector of colors to be used in that case

cuts

the default number of cutpoints if drape=TRUE

pretty

whether the cutpoints should be pretty

colorkey

whether a color key should be drawn alongside. See levelplot for details

...

other arguments, passed to the panel function

Value

• 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.

synopsis

cloud(formula, data = parent.frame(), allow.multiple, outer, auto.key, aspect = c(1,1), layout = NULL, panel = "panel.cloud", prepanel = NULL, scales = NULL, strip = TRUE, groups = NULL, xlab, xlim = range(x), ylab, ylim = range(y), zlab, zlim = range(z), distance = .2, perspective = TRUE, R.mat = diag(4), screen = list(z = 40, x = -60), zoom = .8, at, pretty = FALSE, drape = FALSE, ..., colorkey = any(drape), col.regions, cuts = 1, subscripts = TRUE, subset = TRUE) wireframe(formula, data = parent.frame(), panel = "panel.wireframe", prepanel = NULL, strip = TRUE, groups = NULL, cuts = 70, pretty = FALSE, drape = FALSE, ..., col.regions = trellis.par.get("regions")$col, colorkey = any(drape), subset = TRUE)

Details

cloud draws a 3d Scatter Plot, while wireframe draws a wireframe 3d surface evaluated on a grid. Multiple surfaces can be drawn by wireframe using the groups argument. 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.cloud. Note that although arguments controlling these are actually arguments for the panel function, they can be supplied to wireframe directly.

wireframe can be extremely slow in rendering; this should improve sometime in the future. (For some reason, postscript output is much faster than most other devices.)

The algorithm for identifying which edges of the bounding box should be drawn before the points are plotted fails in some cases.

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

See Also

xyplot, levelplot, panel.cloud, Lattice

Examples

x <- seq(-pi, pi, len = 20)
y <- seq(-pi, pi, len = 20)
g <- expand.grid(x = x, y = y)
g$z <- sin(sqrt(g$x^2 + g$y^2))
wireframe(z ~ x * y, g, drape = TRUE,
          perspective = FALSE,
          aspect = c(3,1), colorkey = FALSE)
g <- expand.grid(x = 1:10, y = 5:15, gr = 1:2)
g$z <- log((g$x^g$g + g$y^2) * g$gr)
wireframe(z ~ x * y, data = g, groups = gr,
          scales = list(arrows = FALSE),
          shade = TRUE,
          shade.colors = function(cosangle, height)
          palette.shade(cosangle, height = .15, saturation = .05),
          light.source = c(0, 0, 1),
          screen = list(z = 30, x = -60))
data(iris)
cloud(Sepal.Length ~ Petal.Length * Petal.Width, data = iris,
      groups = Species, screen = list(x = -90, y = 70),
      aspect = c(1, 1), distance = .4, zoom = .6,
      key = list(title = "Iris Data", x = .1, y=.9,
                 corner = c(0,1),
                 border = TRUE, 
                 points = Rows(trellis.par.get("superpose.symbol"), 1:3),
                 text = list(levels(iris$Species))))
print(cloud(Sepal.Length ~ Petal.Length * Petal.Width, 
            data = iris, cex = .8, 
            groups = Species, 
            subpanel = panel.superpose,
            main = "Stereo",
            screen = list(z = 20, x = -70, y = 3)),
      split = c(1,1,2,1), more = TRUE)
print(cloud(Sepal.Length ~ Petal.Length * Petal.Width,
            data = iris, cex = .8, 
            groups = Species,
            subpanel = panel.superpose,
            main = "Stereo",
            screen = list(z = 20, x = -70, y = 0)),
      split = c(2,1,2,1))