levelplot              package:lattice              R Documentation

_L_e_v_e_l _P_l_o_t_s

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

     Draw Level Plots and Contour plots.

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

     levelplot(formula,
               at,
               col.regions = trellis.par.get("regions")$col,
               colorkey = region,
               contour = FALSE,
               cuts = 15,
               labels = format(at),
               pretty = FALSE,
               region = TRUE,
               ...)
     contourplot(formula, at,
                 contour = TRUE,
                 cuts = 7,
                 pretty = 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. See
          example below with log scales.

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

      at: numeric vector giving breaks along the range of `z'. Contours
          (if any) will be drawn at these heights, and the regions in
          between would be colored using `col.regions'. 

col.regions: color vector to be used if regions is TRUE

colorkey: logical specifying whether a color key is to be drawn
          alongside the plot, or a list describing the color key. The
          list may contain the following components:

          `space' location of the colorkey, can be one of ``left'',
          ``right'', ``top'' and ``bottom''. Defaults to ``right''.

          `x,y' location, unused

          `col' vector of colors

          `at' numeric vector specifying where the colors change. must
          be of length 1 more than the col vector.

          `labels' a character vector for labelling the `at' values, or
          more commonly, a list of components `labels, at, cex, col,
          font' describing label positions.

          `tick.number' approximate number of ticks.

          `corner' interacts with x, y; unimplemented

          `width' width of the key in terms of character widths

          `height' length of key w.r.t side of plot. 

 contour: logical, whether to draw contour lines. 

    cuts: number of levels the range of `z' would be divided into

  labels: character vector of labels for contour lines, not implemented
          yet.

  pretty: logical, whether to use pretty labels

  region: logical, whether regions between contour lines should be
          filled 

     ...: other arguments

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

     These 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', `Lattice', `panel.levelplot'

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

     x <- seq(pi/4, 5*pi, length = 100)
     y <- seq(pi/4, 5*pi, length = 100)
     r <- sqrt(outer(x^2, y^2, "+"))
     grid <- expand.grid(x=x, y=y)
     grid$z <- cos(r^2) * exp(-r/(pi^3))
     levelplot(z~x*y, grid, cuts = 50, xlab="", ylab="",
               main="Weird Function", colorkey = FALSE)
     levelplot(z~x*y, grid, cuts = 50, scales=list(log="e"), xlab="",
               ylab="", main="Weird Function", sub="with log scales",
               colorkey = FALSE, region = TRUE)
     #S+ example
     data(environmental)
     attach(environmental)
     ozo.m <- loess((ozone^(1/3)) ~ wind * temperature * radiation,
            parametric = c("radiation", "wind"), span = 1, degree = 2)
     w.marginal <- seq(min(wind), max(wind), length = 50)
     t.marginal <- seq(min(temperature), max(temperature), length = 50)
     r.marginal <- seq(min(radiation), max(radiation), length = 4)
     wtr.marginal <- list(wind = w.marginal, temperature = t.marginal,
             radiation = r.marginal)
     grid <- expand.grid(wtr.marginal)
     grid[, "fit"] <- c(predict(ozo.m, grid))
     contourplot(fit ~ wind * temperature | radiation, data = grid,
               cuts = 10, region = TRUE,
               xlab = "Wind Speed (mph)",
               ylab = "Temperature (F)",
               main = "Cube Root Ozone (cube root ppb)",
               col.regions = trellis.par.get("regions")$col)
     detach()

