B_06_levelplot {lattice} | R Documentation

## Level plots and contour plots

### Description

Draws false color level plots and contour plots.

### Usage

    levelplot(x, data, ...)
    contourplot(x, data, ...)

    ## S3 method for class 'formula'
    levelplot(x,
              data,
              allow.multiple = is.null(groups) || outer,
              outer = TRUE,
              aspect = "fill",
              panel = if (useRaster) lattice.getOption("panel.levelplot.raster")
                      else lattice.getOption("panel.levelplot"),
              prepanel = NULL,
              scales = list(),
              strip = TRUE,
              groups = NULL,
              xlab,
              xlim,
              ylab,
              ylim,
              at,
              cuts = 15,
              pretty = FALSE,
              region = TRUE,
              drop.unused.levels =
                  lattice.getOption("drop.unused.levels"),
              ...,
              useRaster = FALSE,
              lattice.options = NULL,
              default.scales = list(),
              default.prepanel =
                  lattice.getOption("prepanel.default.levelplot"),
              colorkey = region,
              col.regions,
              alpha.regions,
              subset = TRUE)

    ## S3 method for class 'formula'
    contourplot(x,
                data,
                panel = lattice.getOption("panel.contourplot"),
                default.prepanel =
                    lattice.getOption("prepanel.default.contourplot"),
                cuts = 7,
                labels = TRUE,
                contour = TRUE,
                pretty = TRUE,
                region = FALSE,
                ...)

    ## S3 method for class 'table'
    levelplot(x, data = NULL, aspect = "iso", ..., xlim, ylim)

    ## S3 method for class 'table'
    contourplot(x, data = NULL, aspect = "iso", ..., xlim, ylim)

    ## S3 method for class 'matrix'
    levelplot(x, data = NULL, aspect = "iso",
              ..., xlim, ylim,
              row.values = seq_len(nrow(x)),
              column.values = seq_len(ncol(x)))

    ## S3 method for class 'matrix'
    contourplot(x, data = NULL, aspect = "iso",
                ..., xlim, ylim,
                row.values = seq_len(nrow(x)),
                column.values = seq_len(ncol(x)))

    ## S3 method for class 'array'
    levelplot(x, data = NULL, ...)

    ## S3 method for class 'array'
    contourplot(x, data = NULL, ...)

### Arguments

`x`

for the `formula` method, 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, ...` are optional conditional variables, and must be either factors or shingles if present.

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

Both `levelplot` and `wireframe` have methods for `matrix`, `array`, and `table` objects, in which case `x` provides the `z` vector described above, while its rows and columns are interpreted as the `x` and `y` vectors respectively. This is similar to the form used in `filled.contour` and `image`. For higher-dimensional arrays and tables, further dimensions are used as conditioning variables. Note that the dimnames may be duplicated; this is handled by calling `make.unique` to make the names unique (although the original labels are used for the x- and y-axes).

`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. Usually ignored with a warning in other cases.
`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 and column numbers.
`panel` | panel function used to create the display, as described in `xyplot`
`aspect` | For the `matrix` methods, the default aspect ratio is chosen to make each cell square. The usual default is `aspect="fill"`, as described in `xyplot`.

`at`

A numeric vector giving breakpoints 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`. In the latter case, values outside the range of `at` will not be drawn at all. This serves as a way to limit the range of the data shown, similar to what a `zlim` argument might have been used for. However, this also means that when supplying `at` explicitly, one has to be careful to include values outside the range of `z` to ensure that all the data are shown.

`col.regions`

color vector to be used if regions is TRUE. The general idea is that this should be a color vector of moderately large length (longer than the number of regions. By default this is 100). It is expected that this vector would be gradually varying in color (so that nearby colors would be similar). When the colors are actually chosen, they are chosen to be equally spaced along this vector. When there are more regions than colors in `col.regions`, the colors are recycled. The actual color assignment is performed by `level.colors`, which is documented separately.

`alpha.regions` | numeric, specifying alpha transparency (works only on some devices)

`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, currently unused

`col`:

  A color ramp specification, as in the `col.regions` argument in `level.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 describing characteristics of the labels. This list may include components `labels`, `at`, `cex`, `col`, `rot`, `font`, `fontface` and `fontfamily`.

`tick.number`:

  approximate number of ticks.

`corner`:

  interacts with x, y; unimplemented

`width`:

  width of the key

`height`:

  length of key w.r.t side of plot.

`raster`:

  Logical flag indicating whether the colorkey should be rendered as a raster image using `grid.raster`. See also `panel.levelplot.raster`.

`interpolate`:

  Logical flag, passed to `rasterGrob` when `raster=TRUE`.

`axis.line`:

  A list giving graphical parameters for the color key boundary and tick marks. Defaults to `trellis.par.get("axis.line")`.

`axis.text`:

  A list giving graphical parameters for the tick mark labels on the color key. Defaults to `trellis.par.get("axis.text")`.

`contour` | logical, whether to draw contour lines.
`cuts` | number of levels the range of `z` would be divided into
`labels` | typically a logical indicating whether contour lines should be labelled, but other possibilities for more sophisticated control exists. Details are documented in the help page for `panel.levelplot`, to which this argument is passed on unchanged. That help page also documents the `label.style` argument, which affects how the labels are rendered.
`pretty` | logical, whether to use pretty cut locations and labels
`region` | A logical flag, indicating whether regions between contour lines should be filled as in a level plot.
`allow.multiple, outer, prepanel, scales, strip, groups, xlab, xlim, ylab, ylim, drop.unused.levels, lattice.options, default.scales, subset` | these arguments are described in the help page for `xyplot`.
`default.prepanel` | Fallback prepanel function. See `xyplot`.
`...` | Further arguments may be supplied. Some are processed by `levelplot` or `contourplot`, and those that are unrecognized are passed on to the panel function.

`useRaster`

A logical flag indicating whether raster representations should be used, both for the false color image and the color key (if present). Effectively, setting this to `TRUE` changes the default panel function from `panel.levelplot` to `panel.levelplot.raster`, and sets the default value of `colorkey$raster` to `TRUE`.

Note that `panel.levelplot.raster` provides only a subset of the features of `panel.levelplot`, but setting `useRaster=TRUE` will not check whether any of the additional features have been requested.

Not all devices support raster images. For devices that appear to lack support, `useRaster=TRUE` will be ignored with a warning.

### Details

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.

Other useful arguments are mentioned in the help page for the default panel function `panel.levelplot` (these are formally arguments to the panel function, but can be specified in the high level calls directly).

### 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.

### Author(s)

Deepayan Sarkar Deepayan.Sarkar@R-project.org

### References

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

### See Also

`xyplot`, `Lattice`, `panel.levelplot`

### Examples

    x <- seq(pi/4, 5 * pi, length.out = 100)
    y <- seq(pi/4, 5 * pi, length.out = 100)
    r <- as.vector(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, scales=list(log="e"), xlab="",
              ylab="", main="Weird Function", sub="with log scales",
              colorkey = FALSE, region = TRUE)

    #S-PLUS example
    require(stats)
    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.out = 50)
    t.marginal <- seq(min(temperature), max(temperature), length.out = 50)
    r.marginal <- seq(min(radiation), max(radiation), length.out = 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)")
    detach()

[Package lattice version 0.20-6 Index]