xyplot {lattice} | R Documentation

## Common Bivariate Trellis Plots

### Description

These are the most commonly used Trellis functions to look at 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. See details below.

Most of the arguments documented here are also applicable for many of the other Trellis functions. These are not described in any detail elsewhere, and this should be considered the canonical documentation for such arguments.

Note that 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.

### Usage

    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 = TRUE,
           par.settings,
           perm.cond,
           index.cond,
           ...,
           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)

### Arguments

`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. For S-PLUS compatibility, the formula can also be written as `y ~ x | g1 + g2 + ...`.
For all these functions other than `xyplot`, a formula of the form `~ x | g1 * g2 * ...` is also allowed. In that case, `y` defaults to `as.factor(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 conditioning plots). 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 order in which the panels are drawn depends on the order in which the conditioning variables are specified (`g1` varies 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 `order.cond` and `perm.cond` arguments, typically in the `update` method.
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 S-compatible.)
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` is 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. Inverse effect compared to S ?

`panel`

Once the subset of rows defined by each unique combination of the levels of the grouping variables are obtained (see above), the corresponding `x` and `y` variables (or some other variables, as appropriate, in the case of other 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. (The latter is preferred when possible, especially when the trellis object returned by the high level function is to be stored and plotted later.)
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 S-PLUS, 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 to get the old behaviour could simply coerce 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 grid-compatible replacements of base R graphics functions useful for this purpose, such as `llines`. (Note that the corresponding base R graphics functions like `lines` would not work.) These are usually sufficient to convert existing custom panel functions written for S-PLUS.
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). A very useful panel function predefined for use in such cases is `panel.superpose`, which can be combined with different `panel.groups` functions. See the examples section for an interaction plot constructed 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. (This becomes slightly more complicated when `allow.multiple` is in effect. Details are explained in the source code (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 non-null)

`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, and "xy", which tries to compute the aspect based on the 45 degree banking rule (see Visualizing Data by William S. Cleveland for details).
If a `prepanel` function is specified, the `dx, dy` components returned by it are used to compute the aspect, otherwise the default prepanel function is used. Currently, only the default prepanel function for `xyplot` produces sensible banking calculations.
The current implementation of banking is not very sophisticated, but is not totally vague either. See `banking` for details.

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

`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`

used typically with `panel=panel.superpose` to allow display controls (color, lty etc) to vary according to a grouping variable. Formally, if groups is specified, then `groups` along with `subscripts` is passed to the panel function, which is expected to handle these arguments.
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 non-null 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 re-`print`ed on another device, 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 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),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'' when appropriate) are `cex=1, col="black", lty=1, lwd=1, font=1, pch=8, adj=0, type="l", size=5, angle=0, density=-1`. `adj, angle, density` are 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:
`between`: numeric vector giving the amount of space (character widths) surrounding each column (split equally on both sides),
`title`: string or expression, title of the key,
`rep`: logical, defaults to TRUE. By default, it's assumed that all columns in the key (except the ``text''s) will have the same number of rows, and all components are replicated to be as long as the longest. This can be suppressed by specifying `rep = FALSE`, in which case the length of each column will be determined by components of that colunm alone.
`cex.title`: cex for the title
`background`: defaults to default background
`border`: color of border, black if TRUE, defaults to FALSE (no border drawn)
`transparent=FALSE`: logical, whether key area should be cleared
`columns`: the number of columns column-blocks the key is to be divided into, which are drawn side by side.
`betwen.columns`: Space between column blocks, in addition to `between`.
`divide` Number of point symbols to divide each line when `type` is `"b"' or `"o"' in `lines`.

`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 determined by the number of levels in the first given variable; the number of rows is the number of levels of the second given variable. If there is one given 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` | character string or expression or list describing 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, font`. The `label` tag can be omitted if it is the first element of the list. Expressions are treated as specification of LaTeX-like markup as in `plotmath`
`page` | a function of one argument (page number) to be called after drawing each page. The function must be `grid-compliant', 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, 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 containing four components `xlim, ylim, dx, dy`. If `xlim` and `ylim` 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, 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.
The prepanel function is responsible for providing a meaningful return value when the `x, y` (etc.) variables are zero-length vectors. When nothing is appropriate, values of NA should be returned for the `xlim` and `ylim` components.

`scales`

list determining how the x- and y-axes (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 components are :
relation : determines limits of the axis. Possible values are "same" (default), "free" and "sliced". For relation="same", the same limits (determined by `xlim, ylim, scales$limits` etc) are used for all the panels. For relation="free", limits for each panel is determined by the points in that panel (via the `prepanel` function). Behaviour for relation = "sliced" is similar, except that the length (max - min) of the scales are constrained to remain the same across panels (limits specified as character vectors, if any, are ignored in these computations). If relation is not "same", the value of `xlim/ ylim/ scales$limits` is normally ignored, except when the latter is a list, when it is treated as if its components were the limit values obtained from the prepanel calculations for each panel.
tick.number: Suggested number of ticks (ignored for a factor, shingle or character vector, in which case there's no natural rule for leaving out some of the labels. But see xlim).
draw = TRUE: logical, whether to draw the axis at all.
alternating = TRUE/c(1,2): logical specifying whether axes alternate from one side of the group of panels to the other. For more accurate control, alternating can be a vector (replicated to be as long as the number of rows or columns per page) consisting of the possible numbers 0=do not draw, 1=bottom/left, 2=top/right and 3=both. alternating applies only when relation="same".
limits: same as xlim and ylim.
at: location of tick marks along the axis (in native coordinates), or a list as long as the number of panels describing tick locations for each panel.
labels: Labels (strings or expressions) to go along with `at`. Can be a list like `at` as well.
cex: factor to control character sizes for axis labels. Can be a vector of length 2, to control left/bottom and right/top separately.
font: font face for axis labels (integer 1-4).
tck: factor to control length of tick marks. Can be a vector of length 2, to control left/bottom and right/top separately.
col: color of ticks and labels.
rot: Angle by which the axis labels are to be rotated. Can be a vector of length 2, to control left/bottom and right/top separately.
abbreviate: logical, whether to abbreviate the labels using `abbreviate`. Can be useful for long labels (e.g., in factors), especially on the x-axis.
minlength: argument to `abbreviate` if `abbreviate=TRUE`.
log: Use a log scale. Defaults to `FALSE`, other possible values are any number that works as a base for taking logarithm, `TRUE`, equivalent to 10, and `"e"` (for natural logarithm). Note that in this case the values passed to the panel function are already transformed, so all computations done inside the panel funtion will be affected accordingly. For example, `panel.lmline` will fit a line to the transformed values.
format: the `format` to use for POSIXct variables. See `strptime` for description of valid strings.
axs: character, ``r'' or ``i''. In the latter case, the axis limits are calculated as the exact data range, instead of being padded on either side. (May not always work as expected.)
Note: 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). If `TRUE`, nothing is plotted in the corresponding panel. 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 form of a strip function.
`sub` | character string or expression 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 on-the-fly.)
`subset` | logical or integer indexing vector (can be specified in terms of variables in `data`). Everything will be done on the data points indexed by `subset`. In case `subscripts` is TRUE, the subscripts will provide indices to the rows of data AFTER the subsetting is done (unlike S-PLUS).
`xlab` | character string or expression giving label for the x-axis. Defaults to the expression for `x` in `formula`. Specify as `NULL` to omit the label altogether. Fine control is possible, see entry for `sub`.

`xlim`

Normally a numeric vector of length 2 (possibly a DateTime object) giving minimum and maximum for the x-axis, 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 giving label for the y-axis. Defaults to the expression for `y` in `formula`. Fine control possible, see entry for `xlab`.
`ylim` | same as `xlim`, applied to the y-axis.
`drop.unused.levels` | logical indicating whether the unused levels of factors will be dropped. Defaults to `TRUE`, but it is sometimes useful 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.
`par.settings` | a list that could be supplied to `lset`. 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 `1:n`, where `n` is the number of conditioning variables. 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 that array.
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 each of these levels. `index.cond` has to be a list 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 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, one can simply set the corresponding component 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`.
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 re-calculating the data subsets that go into each panel.

`...` | 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. Rather, they are passed along to the panel function, as are any other unrecognized arguments.

### Details

These are for the most part decriptions generally applicable to all high level Lattice functions, with special emphasis on `xyplot, bwplot` etc. For other functions, their individual documentation should be studied in addition to this.

### 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@stat.wisc.edu

### See Also

`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` `lset`

### Examples

    require(stats)
    ## Tonga Trench Earthquakes
    data(quakes)
    Depth <- equal.count(quakes$depth, number=8, overlap=.1)
    xyplot(lat ~ long | Depth, data = quakes)

    ## Examples with data from `Visualizing Data' (Cleveland)
    ## (obtained from Bill Cleveland's Homepage :
    ## http://cm.bell-labs.com/cm/ms/departments/sia/wsc/, also
    ## available at statlib)
    data(ethanol)
    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

    data(sunspots)
    spots <- by(sunspots, gl(235, 12, lab = 1749:1983), mean)
    plot <- xyplot(spots ~ 1749:1983, xlab = "", type = "l",
                   scales = list(x = list(alternating = 2)),
                   main = "Average 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

    data(iris)
    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

    data(state)
    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 = "HersheyPlain"))

    data(barley)
    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)))

    data(singer)
    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
    data(OrchardSprays)
    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"))

[Package Contents]