# B_06_levelplot

##### Level plots and contour plots

Draws false color level plots and contour plots.

- Keywords
- hplot

##### Usage

```
levelplot(x, data, …)
contourplot(x, data, …)
```# S3 method for 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 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 table
levelplot(x, data = NULL, aspect = "iso", …, xlim, ylim)

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

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

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

# S3 method for array
levelplot(x, data = NULL, …)

# S3 method for 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.`at`

can have length one only if`region=FALSE`

.- 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.

`tri.lower`

,`tri.upper`

:Logical or numeric controlling whether the first and last intervals should be triangular instead of rectangular. With the default value (

`NA`

), this happens only if the corresponding extreme`at`

values are`-Inf`

or`Inf`

respectively, and the triangles occupy 5% of the total length of the color key. If numeric and between 0 and 0.25, these give the corresponding fraction, which is again 5% when specified as`TRUE`

.`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`

:The approximate number of ticks desired.

`tck`

:A (scalar) multipler for tick lengths.

`corner`

:Interacts with x, y; currently unimplemented

`width`

:The width of the key

`height`

:The length of key as a fraction of the appropriate side of plot.

`raster`

:A 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
A logical flag, indicating whether to draw contour lines.

- cuts
The 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
A logical flag, indicating 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.

##### References

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

##### See Also

##### Examples

```
# NOT RUN {
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)
## triangular end-points in color key
levelplot(z ~ x * y, grid, col.regions = topo.colors(10),
at = c(-Inf, seq(-0.8, 0.8, by = 0.2), Inf))
#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()
# }
```

*Documentation reproduced from package lattice, version 0.20-40, License: GPL (>= 2)*