Draws false color level plots and contour plots.
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, …)
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).
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.
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 function used to create the display, as described in
xyplot
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.
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.
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.
Numeric, specifying alpha transparency (works only on some devices)
A logical flag specifying whether a colorkey is to be drawn alongside the plot, or a list describing the colorkey. 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:A 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.
title:Usually a character vector or expression providing a title for
the colorkey, or a list controlling the title in further detail,
or an arbitrary "grob". For details of how the list form
is interpreted, see the entry for main in
xyplot; generally speaking, the actual label
should be specified as the label component (which may be
unnamed if it is the first component), and the remaining
arguments are used as appropriate in a call to
textGrob.
Further control of the placement of the title is possible
through the component title.control. In particular, if a
rot component is not specified, its default depends on
the value of title.control$side (0 for top or bottom, and
90 for left or right).
title defaults to NULL, which means no title is drawn.
title:A list providing control over the placement of a title, if
specified. Currently two components are honoured: side
can take values "top", "bottom", "left",
and "right", and specifies the side of the colorkey on
which the title is to be placed. Defaults to the value of the
"space" component. padding is a multiplier for the
default amount of padding between the title and the colorkey.
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").
A logical flag, indicating whether to draw contour lines.
The number of levels the range of z would be divided into.
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.
A logical flag, indicating whether to use pretty cut locations and labels.
A logical flag, indicating whether regions between contour lines should be filled as in a level plot.
These arguments are described in the help page for
xyplot.
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.
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.
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.
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).
Sarkar, Deepayan (2008) Lattice: Multivariate Data Visualization with R, Springer. http://lmdvr.r-forge.r-project.org/
# 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, with a title
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()
# }
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