xyplot {lattice}  R Documentation 
These are the most commonly used high level Trellis functions to plot
pairs of variables. By far the most common is xyplot
, designed
mainly for two continuous variates (though factors can be supplied as
well, in which case they will simply be coerced to numeric), which
produces Conditional Scatterplots. The others are useful when one of
the variates is a factor or a shingle. Most of these arguments are
also applicable for other high level functions in the lattice package,
but are only documented here.
xyplot(formula, data = parent.frame(), panel = if (is.null(groups)) "panel.xyplot" else "panel.superpose", allow.multiple, outer, aspect = "fill", as.table = FALSE, between, groups, key, auto.key = FALSE, legend, layout, main, page, par.strip.text, prepanel, scales, skip, strip = "strip.default", sub, xlab, xlim, ylab, ylim, drop.unused.levels, par.settings, perm.cond, index.cond, ..., default.scales, panel.groups = "panel.xyplot", subscripts, subset) dotplot(formula, data, panel = "panel.dotplot", groups = NULL, ..., subset = TRUE) barchart(formula, data, panel = "panel.barchart", box.ratio = 2, groups = NULL, ..., subset = TRUE) stripplot(formula, data, panel = "panel.stripplot", jitter = FALSE, factor = .5, box.ratio = if (jitter) 1 else 0, groups = NULL, ..., subset = TRUE) bwplot(formula, data, panel = "panel.bwplot", box.ratio = 1, ..., horizontal, subset = TRUE)
formula 
a formula describing the form of conditioning plot. The formula is
generally of the form y ~ x  g1 * g2 * ... , indicating
that plots of y (on the y axis) versus x (on the x
axis) should be produced conditional on the variables
g1, g2, ... . However, the conditioning variables
g1,g2,... may be omitted. The formula can also be supplied
as y ~ x  g1 + g2 + ... .
For all of these functions, with the exception of xyplot , a
formula of the form ~ x  g1 * g2 * ... is also
allowed. In that case, y defaults to names(x) if
x is named, and a factor with a single level otherwise.
Although it is not recommended, usage of the form dotplot(x)
(where the formula argument is not a formula at all) is also
allowed, and is equivalent to dotplot( ~ x) .
The conditioning variables g1, g2, ... must be either
factors or shingles. Shingles are a way of processing numeric
variables for use in conditioning. See documentation of
shingle for details. Like factors, they have a
`levels' attribute, which is used in producing the conditional
plots.
Numeric conditioning variables are converted to shingles by the function shingle (however, using equal.count
might be more appropriate in many cases) and character vectors are
coerced to factors.
The formula can involve expressions, e.g. sqrt() ,
log() .
A special case is when the left and/or right sides of the formula (before the conditioning variables) contain a `+' sign, e.g., y1+y2 ~ x  a*b . This formula would be taken to mean that the
user wants to plot both y1~x  a*b and y2~x  a*b , but
with the y1~x and y2~x superposed in each panel (this
is slightly more complicated in barchart ). The two parts
would be distinguished by different graphical parameters. This is
essentially what the groups argument would produce, if
y1 and y2 were concatenated to produce a longer
vector, with the groups argument being an indicator of which
rows come from which variable. In fact, this is exactly what is
done internally using the reshape function. This
feature cannot be used in conjunction with the groups
argument.
To interpret y1 + y2 as a sum, one can either set
allow.multiple=FALSE or use I(y1+y2) .
A variation on this feature is when the outer argument is set
to TRUE as well as allow.multiple . In that case, the
plots are not superposed in each panel, but instead separated into
different panels (as if a new conditioning variable had been added).
The x and y variables should both be numeric in
xyplot , and an attempt is made to coerce them if
not. However, if either is a factor, the levels of that factor are
used as axis labels. In the other four functions documented here,
exactly one of x and y should be numeric, and the
other a factor or shingle. Which of these will happen is determined
by the horizontal argument — if horizontal=TRUE ,
then y will be coerced to be a factor or shingle, otherwise
x . The default value of horizontal is FALSE if
x is a factor or shingle, TRUE otherwise. (The
functionality provided by horizontal=FALSE is not
Scompatible.)
All points with at least one of its values missing (NA) in any of the variates involved are omitted from the plot. 
data 
a data frame containing values for any variables in the
formula, as well as groups and subset if applicable.
By default the environment where the function was called from is
used.

allow.multiple, outer 
logical flags to control what happens with formulas like y1 +
y2 ~ x . See the entry for formula for details.
allow.multiple defaults to TRUE whenever it makes
sense, and outer defaults to FALSE except when
groups is explicitly specified or grouping doesn't make sense
for the default panel function

box.ratio 
applicable to bwplot , barchart and
stripplot , specifies the ratio of the width of the rectangles
to the inter rectangle space.

horizontal 
logical, applicable to bwplot, dotplot,
barchart and stripplot . Determines which of x and
y is to be a factor or shingle (y if TRUE, x
otherwise). Defaults to FALSE if x is a factor or
shingle, TRUE otherwise. This argument is used to process the
arguments to these high level functions, but more importantly, it is
passed as an argument to the panel function, which is supposed to
use it as approporiate.
A potentially useful component of scales in this case might
be abbreviate = TRUE , in which case long labels which would
usually overlap will be abbreviated. scales could also
contain a minlength argument in this case, which would be
passed to the abbreviate function.

jitter 
logical specifying whether the values should be jittered by adding a random noise in stripplot. 
factor 
numeric controlling amount of jitter as in jitter .

panel 
Once the subset of rows defined by each unique combination of the
levels of the grouping variables are obtained (see details), the
corresponding x and y variables (or other variables,
as appropriate, in the case of other high level functions) are
passed on to be plotted in each panel. The actual plotting is done
by the function specified by the panel argument. Each high
level function has its own default panel function, which could
depend on whether the groups argument was supplied.
The panel function can be a function object or a character string giving the name of a predefined function. Much of the power of Trellis Graphics comes from the ability to define customized panel functions. A panel function appropriate for the functions described here would usually expect arguments named x and y , which would be provided by the
conditioning process. It can also have other arguments. It might be
useful to know in this context that all arguments passed to a high
level Trellis function (such as xyplot ) that are not
recognized by it are passed through to the panel function. It is
thus generally good practice when defining panel functions to allow
a ... argument. Such extra arguments typically control
graphical parameters, but other uses are also common. See
documentation for individual panel functions for specifics.
Note that unlike in SPLUS, it is not guaranteed that panel functions will be supplied only numeric vectors for the x and
y arguments; they can be factors as well (but not
shingles). Panel functions need to handle this case, which in most
cases can be done by simply coercing them to numeric.
Technically speaking, panel functions must be written using Grid graphics functions. However, knowledge of Grid is usually not necessary to construct new custom panel functions, there are several predefined panel functions which can help; for example, panel.grid , panel.loess , etc. There are also some
gridcompatible replacements of commonly used base R graphics
functions useful for this purpose. For example, lines can be
replaced by llines (or equivalently, panel.lines ).
Note that base R graphics functions like lines will not work
in a lattice panel function.
One case where a bit more is required of the panel function is when the groups argument is not null. In that case, the panel
function should also accept arguments named groups and
subscripts (see below for details). An useful panel function
predefined for use in such cases is panel.superpose , which
can be combined with different panel.groups functions
determining what is plotted for each group. See the examples
section for an interaction plot constructed in this way. Several
other panel functions can also handle the groups argument,
including the default ones for barchart , dotplot and
stripplot .
Even when groups is not present, the panel function can have
subscripts as a formal argument. In either case, the
subscripts argument passed to the panel function are the
indices of the x and y data for that panel in the
original data , BEFORE taking into account the effect of
the subset argument. Note that groups remains
unaffected by any subsetting operations, so
groups[subscripts] gives the values of groups that
correspond to the data in that panel. The value of
subscripts becomes slightly more complicated when
allow.multiple is in effect. Details can be found in the
source code of the function latticeParseFormula .
A panel function can have two other optional arguments for convenience, namely panel.number and
panel.counter . Both provide a simple integer index indicating
which panel is currently being drawn, but differ in how the count is
calculated. panel.counter is a simple incremental counter
that starts with 1 and is incremented each time a panel is
drawn. panel.number on the other hand depends only on the
combination of levels of the conditioning variables that is
represented by that panel. The two indices coincide unless the
order of conditioning variables is permuted and/or the plotting
order of levels within one or more conditioning variables is altered
(using perm.cond and index.cond respectively), in
which case panel.number gives the index corresponding to the
`natural' ordering of that combination of levels of the conditioning
variables.
panel.xyplot has an argument called type which is
worth mentioning here because it is quite frequently used (and as
mentioned above, can be passed to xyplot directly). panel
functions for bwplot and friends should have an argument
called horizontal to account for the cases when x is
the factor or shingle.

panel.groups 
useful mostly for xyplot and densityplot . Applies when
panel is panel.superpose (which happens by default in
these cases if groups is nonnull)

aspect 
controls physical aspect ratio of the panels (same for
all the panels). It can be specified as a ratio (vertical
size/horizontal size) or as a character string. Legitimate
values are "fill" (the default) which tries to make the panels as
big as possible to fill the available space; "xy", which
tries to compute the aspect based on the 45 degree banking
rule (see Visualizing Data by William S. Cleveland for
details); and "iso" for isometric scales, where the relation between
physical distance on the device and distance in the data scale are
forced to be the same for both axes.
If a prepanel function is specified and it returns components
dx and dy , these are used for banking calculations.
Otherwise, values from the default prepanel function are used.
Currently, only the default prepanel function for xyplot can
be expected to produce sensible banking calculations. See
banking for details on the implementation of banking .

as.table 
logical that controls the order in which panels
should be plotted: if FALSE (the default), panels are drawn
left to right, bottom to top (as in a graph); if TRUE , left
to right, top to bottom.

between 
a list with components x and y (both
usually 0 by default), numeric vectors specifying the space between
the panels (units are character heights). x and y are
repeated to account for all panels in a page and any extra
components are ignored. The result is used for all pages in a
multipage display. (In other words, it is not possible to use
different between values for different pages).

groups 
a variable or expression to be evaluated in the data
frame specified by data , expected to act as a grouping
variable within each panel, typically used to distinguish different
groups by varying graphical parameters like color and line type.
Formally, if groups is specified, then groups along
with subscripts is passed to the panel function, which is
expected to handle these arguments. Not all predefined panel
functions know how to, but for high level functions where grouping
is appropriate, the default panel functions are chosen so that they
do.
It is very common to use a key (legend) when a grouping variable is specified. See entries for key , auto.key
and simpleKey for how to draw a key.

auto.key 
A logical (indicating whether a key is to be drawn automatically when
a grouping variable is present in the plot), or a list of parameters
that would be valid arguments to simpleKey . If
auto.key is not FALSE , groups is nonnull and
there is no key or legend argument specified in the
call, a key is created with simpleKey with
levels(groups) as the first argument. (Note: this may not
work in all high level functions, but it does work for the ones
where grouping makes sense with the default panel function)
simpleKey uses the trellis settings to determine the
graphical parameters in the key, so this will be meaningful only if
the settings are used in the plot as well.
One disadvantage to using key (or even simpleKey )
directly is that the graphical parameters used in the key are
absolutely determined at the time when the ``trellis'' object is
created. Consequently, if a plot once created is reprint ed
with different settings, the parameter settings for the original
device will be used. However, with auto.key , the key is
actually created at printing time, so the key settings will match
the device settings.

key 
A list of arguments that define a legend to be drawn on the plot.
This list is used as an argument to the draw.key
function, which produces a grid object eventually plotted by the
print method for ``trellis'' objects.
There is also a less flexible but usually sufficient shortcut function simpleKey that can generate such a list, as
well as the argument auto.key that can be convenient in the
most common situation where legends are used, namely when there is a
grouping variable. To use more than one legend, or to have arbitrary
legends not constrained by the structure imposed by key , use
the legend argument.
The position of the key can be controlled in either of two possible ways. If a component called space is present, the key is
positioned outside the plot region, in one of the four sides,
determined by the value of space , which can be one of
``top'', ``bottom'', ``left'' and ``right''. Alternatively, the key
can be positioned inside the plot region by specifying components
x , y and corner . x and y
determine the location of the corner of the key given by
corner , which can be one of c(0,0) , c(1,0) ,
c(1,1) and c(0,1) , which denote the corners of the
unit square. x and y must be numbers between 0 and 1,
giving coordinates with respect to the whole display area.
The key essentially consists of a number of columns, possibly divided into blocks, each containing some rows. The contents of the key are determined by (possibly repeated) components named ``rectangles'', ``lines'', ``points'' or ``text''. Each of these must be lists with relevant graphical parameters (see later) controlling their appearance. The key list itself can contain
graphical parameters, these would be used if relevant graphical
components are omitted from the other components.
The length (number of rows) of each such column (except ``text''s) is taken to be the largest of the lengths of the graphical components, including the ones specified outside (see the entry for rep below for details on this). The ``text'' component has to
have a character or expression vector as its first component, and
the length of this vector determines the number of rows.
The graphical components that can be included in key (and
also in the components named ``text'', ``lines'', ``points'' and
``rectangles'' as appropriate) are:
adj , angle and density are currently
unimplemented. size determines the width of columns of
rectangles and lines in character widths. type is relevant
for lines; "l" denotes a line, "p" denotes a point,
and "b" and "o" both denote both together.
Other possible components of key are:

legend 
the legend argument can be useful if one wants to place more than
one key. It also allows one to use arbitrary ``grob''s (grid
objects) as legends.
If used, legend must be a list, with an arbitrary number of
components. Each component must be named one of ``left'', ``right'',
``top'', ``bottom'' or ``inside''. The name ``inside'' can be
repeated, but not the others. This name will be used to determine
the location for that component, and is similar to the space
component of key . If key (or colorkey for
levelplot and wireframe ) is specified,
their space component must not conflict with the name of any
component of legend .
Each component of legend must have a component called
fun . This can be a ``grob'', or a function or the name of a
function that produces a ``grob'' when called. If this function
expects any arguments, they must be supplied as a list in another
component called args . For components named ``inside'', there
can be additional components called x , y and
corner , which work in the same way as it does for key .

layout 
In general, a Trellis conditioning plot consists of several panels
arranged in a rectangular array, possibly spanning multiple
pages. layout determines this arrangement.
layout is a numeric vector giving the number of columns, rows
and pages in a multipanel display. By default, the number of
columns is the number of levels of the first conditioning variable
and the number of rows is the number of levels of the second
conditioning variable. If there is only one conditioning variable,
the default layout vector is c(0,n) , where n is the
number of levels of the given vector. Any time the first value in
the layout vector is 0, the second value is used as the desired
number of panels per page and the actual layout is computed from
this, taking into account the aspect ratio of the panels and the
device dimensions (via par("din") ). The number of pages is
by default set to as many as is required to plot all the panels. In
general, giving a high value of layout[3] is not wasteful
because blank pages are never created.

main 
typically a character string or expression or list
describing the main title to be placed on top of each page. Defaults
to NULL . Can be a character string or expression, or a list
with components label , cex , col and
font . The label tag can be omitted if it is the first
element of the list. Expressions are treated as specification of
LaTeXlike markup as in plotmath .
main can also be an arbitrary ``grob'' (grid graphical
object).

page 
a function of one argument (page number) to be called after drawing each page. The function must be `gridcompliant', and is called with the whole display area as the default viewport. 
par.strip.text 
list of graphical parameters to control the
strip text, possible components are col , cex ,
font and lines . The first three control graphical
parameters while the last is a means of altering the height of the
strips. This can be useful, for example, if the strip labels
(derived from factor levels, say) are double height (i.e., contains
``\n''s) or if the default height seems too small or too large.

prepanel 
function that takes the same arguments as the panel function
and returns a list, possibly containing components named
xlim , ylim , dx and dy (and less
frequently, xat and yat ).
The xlim and ylim components are similar to the high
level xlim and ylim arguments (i.e., they are usually
a numeric vector of length 2 defining a range of values, or a
character vector representing levels of a factor). If the
xlim and ylim arguments are not explicitly specified
(possibly as components in scales ), then the actual limits of
the panels are guaranteed to include the limits returned by the
prepanel function. This happens globally if the relation
component of scales is "same" , and on a panel by panel
basis otherwise. See xlim to see what forms of the components
xlim and ylim are allowed.
The dx and dy components are used for banking
computations in case aspect is specified as "xy" . See
documentation for the function banking for details regarding
how this is done.
The return value of the prepanel function need not have all the components named above; in case some are missing, they are replaced by the usual componentwise defaults. If xlim or ylim is a character vector (which is
appropriate when the corresponding variable is a factor), this
implicitly indicates that the scale should include the first
n integers, where n is the length of xlim or
ylim , as the case may be. The elements of the character
vector are used as the default labels for these n integers.
Thus, to make this information consistent between panels, the
xlim or ylim values should represent all the levels of
the corresponding factor, even if some are not used within that
particular panel.
In such cases, an additional component xat or yat may
be returned by the prepanel function, which should be a
subset of 1:n , indicating which of the n values
(levels) are actually represented in the panel. This is useful when
calculating the limits with relation="free" or
relation="sliced" in scales .
The prepanel function is responsible for providing a meaningful return value when the x , y (etc.) variables are
zerolength vectors. When nothing is appropriate, values of NA
should be returned for the xlim and ylim components.

scales 
list determining how the x and yaxes (tick marks and
labels) are drawn. The list contains parameters in
name=value form, and may also contain two other lists called
x and y of the same form (described below).
Components of x and y affect the respective axes only,
while those in scales affect both. When parameters are
specified in both lists, the values in x or y are
used. The possible components are :
Note that much of the function of scales is accomplished by
pscales in splom .

skip 
logical vector (default FALSE ), replicated to be as long as
the number of panels (spanning all pages). For elements that are
TRUE , the corresponding panel position is skipped; i.e.,
nothing is plotted in that position. The panel that was supposed to
be drawn there is now drawn in the next available panel position,
and the positions of all the subsequent panels are bumped up
accordingly. This is often useful for arranging plots in an
informative manner.

strip 
logical flag or function. If FALSE , strips are not drawn.
Otherwise, strips are drawn using the strip function, which
defaults to strip.default . See documentation of
strip.default to see the arguments that are available to the
strip function.

sub 
character string or expression (or a ``grob'') for a subtitle to be
placed at the bottom of each page. See entry for main for
finer control options.

subscripts 
logical specifying whether or not a vector named subscripts
should be passed to the panel function. Defaults to FALSE ,
unless groups is specified, or if the panel function accepts
an argument named subscripts . (One should be careful when
defining the panel function onthefly.)

subset 
logical or integer indexing vector (can be specified in terms of
variables in data ). Only these rows of data will be
used for the plot. If subscripts is TRUE , the
subscripts will provide indices to the rows of data before the
subsetting is done. Whether levels of factors in the data frame
that are unused after the subsetting will be dropped depends on the
drop.unused.levels argument.

xlab 
character string or expression (or a ``grob'') giving
label for the xaxis. Defaults to the expression for x in
formula . Can be specified as NULL to omit the label
altogether. Finer control is possible, as described in the entry
for main , with the additional feature that if the
label component is omitted from the list, it is replaced by
the default xlab .

xlim 
Normally a numeric vector of length 2 (possibly a
DateTime object) giving minimum and maximum for the xaxis, or, a
character vector, expected to denote the levels of x . The
latter form is interpreted as a range containing c(1, length(xlim)),
with the character vector determining labels at tick positions
1:length(xlim)
xlim could also be a list, with as many components as the
number of panels (recycled if necessary), with each component as
described above. This is meaningful only when
scales$x$relation is "free" or "sliced", in which case these
are treated as if they were the corresponding limit components
returned by prepanel calculations.

ylab 
character string or expression (or ``grob'') giving label
for the yaxis. Defaults to the expression for y in
formula . Fine control is possible, see entry for
xlab .

ylim 
similar to xlim , applied to the yaxis. 
drop.unused.levels 
logical indicating whether the unused levels of factors will be
dropped. Unused levels are usually dropped, but it is sometimes
appropriate to suppress dropping to preserve an useful layout. For
finer control, this argument could also be list containing
components cond and data , both logical, indicating
desired behaviour for conditioning variables and data variables
respectively. The default is given by
lattice.getOption("drop.unused.levels") , which is initially
set to TRUE for both components.

par.settings 
a list that could be supplied to trellis.par.set .
This enables the user to attach some display settings to the trellis
object itself rather than change the settings globally. When the
object is printed, these settings are temporarily in effect for the
duration of the plot, after which the settings revert back to
whatever it was before.

perm.cond 
numeric vector, a permutation of 1:n , where n is the
number of conditioning variables. By default, the order in which
panels are drawn depends on the order of the conditioning variables
specified in the formula . perm.cond can modify this
order. If the trellis display is thought of as an
n dimensional array, then during printing, its dimensions are
permuted using perm.cond as the perm argument to
aperm .

index.cond 
While perm.cond permutes the dimensions of the
multidimensional array of panels, index.cond can be used to
subset (or reorder) margins of that array. index.cond can be
a list or a function, with behaviour in each case described
below.
The panel display order within each conditioning variable depends on the order of their levels. index.cond can be used to choose
a `subset' (in the R sense) of these levels, which is then used as
the display order for that variable. If index.cond is a
list, it has to be as long as the number of conditioning variables,
and the i th component has to be a valid indexing vector for
the integer vector 1:nlevels(g_i) (which can, among other
things, repeat some of the levels or drop some altogether). The
result of this indexing determines the order of panels within that
conditioning variable. To keep the order of a particular variable
unchanged, the corresponding component must be set to TRUE .
Note that the components of index.cond are in the order of
the conditioning variables in the original call, and is not affected
by perm.cond .
Another possibility is to specify index.cond as a function.
In this case, this function is called once for each panel,
potentially with all arguments that are passed to the panel function
for that panel. (More specifically, if this function has a
... argument, then all panel arguments are passed,
otherwise, only named arguments that match are passed.) For a single
conditioning variable, the levels of that variable are then sorted
so that these values are in ascending order. For multiple
conditioning variables, the order for each variable is determined by
first taking the average over all other conditioning variables.
Although they can be supplied in high level function calls directly, it is more typical to use perm.cond and index.cond to
update an existing ``trellis'' object, thus allowing it to be
displayed in a different arrangement without recalculating the data
subsets that go into each panel. In the update method, both
can be set to NULL , which reverts these back to their
defaults.

default.scales 
list giving the default values of scales for a particular
high level function. This should not be of any interest to the
normal user, but may be helpful when defining other functions that
act as a wrapper to one of the high level lattice functions.

... 
other arguments, passed to the panel function.
The arguments horizontal and panel.groups are
documented here to avoid confusion, but they are actually not
recognised by these high level functions. Instead, they are passed
along to the panel function, as are any other unrecognized
arguments.

The structure of the plot that is produced is mostly controlled by the
formula
argument. For each unique combination of the levels of
the conditioning variables g1, g2, ...
, a separate panel is
produced using the points (x,y)
for the subset of the data
(also called packet) defined by that combination. The panels can be
though of as a 3dimensional array, consisting of one 2dimensional
matrix per page. The dimesions of this array are determined by the
layout
argument.
If there are no conditioning variables, the plot produced consists of a single panel.
The coordinate system used by lattice by default is like a graph,
with the origin at the bottom left, with axes increasing to left and
up. In particular, panels are by default drawn starting from the
bottom left corner, going right and then up; unless as.table =
TRUE
, in which case panels are drawn from the top left corner,
going right and then down. One might wish to set a global preference
for a tablelike arrangement by changing the default to
as.table=TRUE
; this can be done by setting
lattice.options(default.args = list(as.table = TRUE))
. In
fact, default values can be set in this manner for the following
arguments: as.table
, aspect
, between
,
page
, main
, sub
, par.strip.text
,
layout
, skip
and strip
. Note that these global
defaults are sometimes overridden by individual functions.
The order of the panels depends on the order in which the conditioning
variables are specified, with g1
varying fastest. Within a
conditioning variable, the order depends on the order of the levels
(which for factors is usually in alphabetical order). Both of these
orders can be modified using the index.cond
and
perm.cond
arguments, possibly using the update
method.
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.
Most of the arguments documented here are also applicable for the other high level functions in the lattice package. These are not described in any detail elsewhere unless relevant, and this should be considered the canonical documentation for such arguments.
Any arguments passed to these functions and not recognized by them will be passed to the panel function. Most predefined panel functions have arguments that customize its output. These arguments are described only in the help pages for these panel functions, but can usually be supplied as arguments to the high level plot.
Deepayan Sarkar Deepayan.Sarkar@Rproject.org
Lattice
,
print.trellis
,
shingle
,
banking
,
reshape
,
panel.xyplot
,
panel.bwplot
,
panel.barchart
,
panel.dotplot
,
panel.stripplot
,
panel.superpose
,
panel.loess
,
panel.linejoin
,
strip.default
,
simpleKey
trellis.par.set
require(stats) ## Tonga Trench Earthquakes Depth < equal.count(quakes$depth, number=8, overlap=.1) xyplot(lat ~ long  Depth, data = quakes) update(trellis.last.object(), aspect = "iso") ## Examples with data from `Visualizing Data' (Cleveland) ## (obtained from Bill Cleveland's Homepage : ## http://cm.belllabs.com/cm/ms/departments/sia/wsc/, also ## available at statlib) EE < equal.count(ethanol$E, number=9, overlap=1/4) ## Constructing panel functions on the fly; prepanel xyplot(NOx ~ C  EE, data = ethanol, prepanel = function(x, y) prepanel.loess(x, y, span = 1), xlab = "Compression Ratio", ylab = "NOx (micrograms/J)", panel = function(x, y) { panel.grid(h=1, v= 2) panel.xyplot(x, y) panel.loess(x,y, span=1) }, aspect = "xy") ## with and without banking plot < xyplot(sunspot.year ~ 1700:1988, xlab = "", type = "l", scales = list(x = list(alternating = 2)), main = "Yearly Sunspots") print(plot, position = c(0, .3, 1, .9), more = TRUE) print(update(plot, aspect = "xy", main = "", xlab = "Year"), position = c(0, 0, 1, .3)) ## Multiple variables in formula for grouped displays xyplot(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width  Species, data = iris, scales = "free", layout = c(2, 2), auto.key = list(x = .6, y = .7, corner = c(0, 0))) ## user defined panel functions states < data.frame(state.x77, state.name = dimnames(state.x77)[[1]], state.region = state.region) xyplot(Murder ~ Population  state.region, data = states, groups = state.name, panel = function(x, y, subscripts, groups) ltext(x = x, y = y, label = groups[subscripts], cex=1, fontfamily = "HersheySans")) barchart(yield ~ variety  site, data = barley, groups = year, layout = c(1,6), ylab = "Barley Yield (bushels/acre)", scales = list(x = list(abbreviate = TRUE, minlength = 5))) barchart(yield ~ variety  site, data = barley, groups = year, layout = c(1,6), stack = TRUE, auto.key = list(points = FALSE, rectangles = TRUE, space = "right"), ylab = "Barley Yield (bushels/acre)", scales = list(x = list(rot = 45))) bwplot(voice.part ~ height, data=singer, xlab="Height (inches)") dotplot(variety ~ yield  year * site, data=barley) dotplot(variety ~ yield  site, data = barley, groups = year, key = simpleKey(levels(barley$year), space = "right"), xlab = "Barley Yield (bushels/acre) ", aspect=0.5, layout = c(1,6), ylab=NULL) stripplot(voice.part ~ jitter(height), data = singer, aspect = 1, jitter = TRUE, xlab = "Height (inches)") ## Interaction Plot bwplot(decrease ~ treatment, OrchardSprays, groups = rowpos, panel = "panel.superpose", panel.groups = "panel.linejoin", xlab = "treatment", key = list(lines = Rows(trellis.par.get("superpose.line"), c(1:7, 1)), text = list(lab = as.character(unique(OrchardSprays$rowpos))), columns = 4, title = "Row position"))