lattice (version 0.17-25)

cloud: 3d Scatter Plot and Wireframe Surface Plot

Description

Generic functions to draw 3d scatter plots and surfaces. The "formula" methods do most of the actual work.

Usage

cloud(x, data, ...)
wireframe(x, data, ...)
## S3 method for class 'formula':
cloud(x,
      data,
      allow.multiple = is.null(groups) || outer,
      outer = FALSE,
      auto.key = FALSE,
      aspect = c(1,1),
      panel.aspect = 1,
      panel = lattice.getOption("panel.cloud"),
      prepanel = NULL,
      scales = list(),
      strip = TRUE,
      groups = NULL,
      xlab,
      ylab,
      zlab,
      xlim = if (is.factor(x)) levels(x) else range(x, finite = TRUE),
      ylim = if (is.factor(y)) levels(y) else range(y, finite = TRUE),
      zlim = if (is.factor(z)) levels(z) else range(z, finite = TRUE),
      at,
      drape = FALSE,
      pretty = FALSE,
      drop.unused.levels,
      ...,
      lattice.options = NULL,
      default.scales =
      list(distance = c(1, 1, 1),
           arrows = TRUE,
           axs = axs.default),
      colorkey,
      col.regions,
      alpha.regions,
      cuts = 70,
      subset = TRUE,
      axs.default = "r")
## S3 method for class 'formula':
wireframe(x,
          data,
          panel = lattice.getOption("panel.wireframe"),
          ...)## S3 method for class 'matrix':
cloud(x, data = NULL, type = "h", 
      zlab = deparse(substitute(x)), aspect, ...,
      xlim, ylim, row.values, column.values)
## S3 method for class 'table':
cloud(x, data = NULL, groups = FALSE,
      zlab = deparse(substitute(x)),
      type = "h", ...)
## S3 method for class 'matrix':
wireframe(x, data = NULL,
          zlab = deparse(substitute(x)), aspect, ...,
          xlim, ylim, row.values, column.values)

Arguments

x

The object on which method dispatch is carried out.

For the "formula" methods, a formula of the form z ~ x * y | g1 * g2 * ..., where z is a numeric response, and x, y are num

data

for the "formula" methods, an optional data frame in which variables in the formula (as well as groups and subset, if any) are to be evaluated. data should not be specified except when using

row.values, column.values

Optional vectors of values that define the grid when x is a matrix. row.values and column.values must have the same lengths as nrow(x) and ncol(x) respectively. By default, row

allow.multiple, outer, auto.key, prepanel, strip, groups, xlab, xlim, ylab, ylim, drop.unused.levels, lattice.options, default.scales, subset

These arguments are documented in the help page for xyplot. For the cloud.table method, groups must be a logical indicating whether the last dimension should be used as

type

type of display in cloud (see panel.3dscatter for details). Defaults to "h" for the matrix method.

aspect, panel.aspect

unlike other high level functions, aspect is taken to be a numeric vector of length 2, giving the relative aspects of the y-size/x-size and z-size/x-size of the enclosing cube. The usual role of the aspect argument i

panel

panel function used to create the display. See panel.cloud for (non-trivial) details.

scales

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

axs.default

Unlike 2-D display functions, cloud does not expand the bounding box to slightly beyound the range of the data, even though it should. This is primarily because this is the natural behaviour in wireframe, which uses

zlab

Specifies a label describing the z variable in ways similar to xlab and ylab (i.e. grob, character string, expression or list) in other high level functions. Additionally, if zlab (and <

zlim

limits for the z-axis. Similar to xlim and ylim in other high level functions

drape

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

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

cuts

if at is unspecified, the approximate number of cutpoints if drape=TRUE

pretty

whether automatic choice of cutpoints should be prettfied

colorkey

logical indicating whether a color key should be drawn alongside, or a list describing such a key. See levelplot for details.

...

Any number of other arguments can be specified, and are passed to the panel function. In particular, the arguments distance, perspective, screen and R.mat are very important in determining t

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.

Details

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 x 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, panel.cloud 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 panel.cloud.

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.

References

Sarkar, Deepayan (2008) "Lattice: Multivariate Data Visualization with R", Springer. http://lmdvr.r-forge.r-project.org/

See Also

Lattice for an overview of the package, as well as xyplot, levelplot, panel.cloud

Examples

## 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)

## cloud.table

cloud(prop.table(Titanic, margin = 1:3),
      type = c("p", "h"), strip = strip.custom(strip.names = TRUE),
      scales = list(arrows = FALSE, distance = 2), panel.aspect = 0.7,
      zlab = "Proportion")[, 1]

## transparent axes

par.set <-
    list(axis.line = list(col = "transparent"),
         clip = list(panel = "off"))
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,
            scales = list(col = "black")),
      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,
            scales = list(col = "black")),
      split = c(2,1,2,1))