cloud                package:lattice                R Documentation

_3_d _S_c_a_t_t_e_r _P_l_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     Draws 3d scatter plots and surfaces.

_U_s_a_g_e:

     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),
               ...)

_A_r_g_u_m_e_n_t_s:

 formula: a formula of the form `z ~ x * y | g1 * g2 * ...', where `z'
          is a numeric response, and `x, y' are numeric values
          evaluated on a rectangular grid. 

          `g1,g2,...', if present, must be either factors or shingles.

          Calculations are based on the assumption that all x and y
          values are evaluated on a grid (defined by `(unique(x))' and
          `(unique(y))'. The function will not return an error if this
          is not true, but the display might be nonsense.

          However, the x and y values need not be equally spaced. 

          As an extension to partially support the form used in
          `filled.contour' and `image', `formula' can be a matrix. 

    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 `scales' argument
          also work here (see `xyplot'). 

    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 achievable.

 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 named one of `x, y, z' (repititions allowed), with
          their values indicating the amount of rotation about that
          axis in degrees.  

    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

_D_e_t_a_i_l_s:

     `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
     (namely when perspective = TRUE and the projection of the rear
     surface is totally contained in that of the front surface).

     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.

_A_u_t_h_o_r(_s):

     Deepayan Sarkar deepayan@stat.wisc.edu

_S_e_e _A_l_s_o:

     `xyplot', `levelplot', `panel.cloud', `Lattice'

_E_x_a_m_p_l_e_s:

     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))

