| levelplot {lattice} | R Documentation |
Draw Level Plots and Contour plots.
levelplot(x, ...)
contourplot(x, ...)
## S3 method for class 'formula':
levelplot(x, data,
panel = "panel.levelplot",
at,
contour = FALSE,
cuts = 15,
pretty = FALSE,
region = TRUE,
...,
col.regions = trellis.par.get("regions")$col,
colorkey = region)
## S3 method for class 'formula':
contourplot(x,
data = parent.frame(),
panel = "panel.contourplot",
cuts = 7,
labels = TRUE,
contour = TRUE,
pretty = TRUE,
region = FALSE,
...)
## S3 method for class 'matrix':
levelplot(x, data, aspect = "iso", ...)
## S3 method for class 'matrix':
contourplot(x, data, aspect = "iso", ...)
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 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.
|
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. By default, the
environment where the function was called from is used. Ignored
with a warning in other cases.
|
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 |
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. 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 col.regions, the colors are recycled. |
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:
|
contour |
logical, whether to draw contour lines. |
cuts |
number of levels the range of z would be divided into
|
labels |
logical specifying whether contour lines should be labelled, or
character vector of labels for contour lines. The type of labelling
can be controlled by the label.style argument, which is
passed on to panel.levelplot
|
pretty |
logical, whether to use pretty cut locations and labels |
region |
logical, whether regions between contour lines should be filled |
... |
other arguments |
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).
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.
Deepayan Sarkar Deepayan.Sarkar@R-project.org
xyplot, Lattice,
panel.levelplot
x <- seq(pi/4, 5 * pi, length = 100)
y <- seq(pi/4, 5 * pi, length = 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 = 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)")
detach()