B_00_xyplot {lattice} | R Documentation

## Common Bivariate Trellis Plots

### Description

This help page documents several commonly used high-level Lattice functions. `xyplot` produces bivariate scatterplots or time-series plots, `bwplot` produces box-and-whisker plots, `dotplot` produces Cleveland dot plots, `barchart` produces bar plots, and `stripplot` produces one-dimensional scatterplots. All these functions, along with other high-level Lattice functions, respond to a common set of arguments that control conditioning, layout, aspect ratio, legends, axis annotation, and many other details in a consistent manner. These arguments are described extensively in this help page, and should be used as the reference for other high-level functions as well.

For control and customization of the actual display in each panel, the help page of the respective default panel function will often be more informative. In particular, these help pages describe many arguments commonly used when calling the corresponding high-level function but are specific to them.

### Usage

    xyplot(x, data, ...)
    dotplot(x, data, ...)
    barchart(x, data, ...)
    stripplot(x, data, ...)
    bwplot(x, data, ...)

    ## S3 method for class 'formula'
    xyplot(x,
           data,
           allow.multiple = is.null(groups) || outer,
           outer = !is.null(groups),
           auto.key = FALSE,
           aspect = "fill",
           panel = lattice.getOption("panel.xyplot"),
           prepanel = NULL,
           scales = list(),
           strip = TRUE,
           groups = NULL,
           xlab,
           xlim,
           ylab,
           ylim,
           drop.unused.levels = lattice.getOption("drop.unused.levels"),
           ...,
           lattice.options = NULL,
           default.scales,
           default.prepanel = lattice.getOption("prepanel.default.xyplot"),
           subscripts = !is.null(groups),
           subset = TRUE)

    ## S3 method for class 'formula'
    dotplot(x,
            data,
            panel = lattice.getOption("panel.dotplot"),
            default.prepanel = lattice.getOption("prepanel.default.dotplot"),
            ...)

    ## S3 method for class 'formula'
    barchart(x,
             data,
             panel = lattice.getOption("panel.barchart"),
             default.prepanel = lattice.getOption("prepanel.default.barchart"),
             box.ratio = 2,
             ...)

    ## S3 method for class 'formula'
    stripplot(x,
              data,
              panel = lattice.getOption("panel.stripplot"),
              default.prepanel = lattice.getOption("prepanel.default.stripplot"),
              ...)

    ## S3 method for class 'formula'
    bwplot(x,
           data,
           allow.multiple = is.null(groups) || outer,
           outer = FALSE,
           auto.key = FALSE,
           aspect = "fill",
           panel = lattice.getOption("panel.bwplot"),
           prepanel = NULL,
           scales = list(),
           strip = TRUE,
           groups = NULL,
           xlab,
           xlim,
           ylab,
           ylim,
           box.ratio = 1,
           horizontal = NULL,
           drop.unused.levels = lattice.getOption("drop.unused.levels"),
           ...,
           lattice.options = NULL,
           default.scales,
           default.prepanel = lattice.getOption("prepanel.default.bwplot"),
           subscripts = !is.null(groups),
           subset = TRUE)

### Arguments

`x` | All high-level function in lattice are generic. `x` is the object on which method dispatch is carried out. For the `"formula"` methods, `x` must be a formula describing the primary variables (used for the per-panel display) and the optional conditioning variables (which define the subsets plotted in different panels) to be used in the plot. Conditioning is described in the “Details” section below. For the functions documented here, the formula is generally of the form `y ~ x | g1 * g2 * ...` (or equivalently, `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, ...`. Here `x` and `y` are the primary variables, and `g1, g2, ...` are the conditioning variables. The conditioning variables may be omitted to give a formula of the form `y ~ x`, in which case the plot will consist of a single panel with the full dataset. The formula can also involve expressions, e.g., `sqrt()`, `log()`, etc. See the `data` argument below for rules regarding evaluation of the terms in the formula. With the exception of `xyplot`, the functions documented here may also be supplied a formula of the form `~ x | g1 * g2 * ...`. In that case, `y` defaults to `names(x)` if `x` is named, and a factor with a single level otherwise. Cases where `x` is not a formula is handled by appropriate methods. The `numeric` methods are equivalent to a call with no left hand side and no conditioning variables in the formula. For `barchart` and `dotplot`, non-trivial methods exist for tables and arrays, documented at `barchart.table`. The conditioning variables `g1, g2, ...` must be either factors or shingles. Shingles provide a way of using numeric variables for conditioning; see the help page of `shingle` for details. Like factors, they have a `"levels"` attribute, which is used in producing the conditional plots. If necessary, numeric conditioning variables are converted to shingles using the `shingle` function; however, using `equal.count` may be more appropriate in many cases. Character variables are coerced to factors. Extended formula interface: As a useful extension of the interface described above, the primary variable terms (both the LHS `y` and RHS `x`) may consist of multiple terms separated by 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. The two groups will be distinguished by different graphical parameters. This is essentially what the `groups` argument (see below) 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`. 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). Primary variables: 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.) Note that the `x` argument used to be called `formula` in earlier versions (when the high-level functions were not generic and the formula method was essentially the only method). This is no longer allowed. It is recommended that this argument not be named in any case, but instead be the first (unnamed) argument.
`data` | For the `formula` methods, a data frame (or more precisely, anything that is a valid `envir` argument in `eval`, e.g., a list or an environment) containing values for any variables in the formula, as well as `groups` and `subset` if applicable. If not found in `data`, or if `data` is unspecified, the variables are looked for in the environment of the formula. For other methods (where `x` is not a formula), `data` is usually ignored, often with a warning if it is explicitly specified.
`allow.multiple` | Logical flag specifying whether the extended formula interface described above should be in effect. Defaults to `TRUE` whenever sensible.
`outer` | Logical flag controlling what happens with formulas using the extended interface described above (see the entry for `x` for details). Defaults to `FALSE`, except when `groups` is explicitly specified or grouping does not make sense for the default panel function.
`box.ratio` | Applicable to `barchart` and `bwplot`. Specifies the ratio of the width of the rectangles to the inter-rectangle space. See also the `box.width` argument in the respective default panel functions.
`horizontal` | Logical flag 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 expected to use it as appropriate. A potentially useful component of `scales` in this case may 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.

Common arguments: The following arguments are common to all the functions documented here, as well as most other high-level Trellis functions. These are not documented elsewhere, except to override the usage given here.

`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. The argument may be a function object or a character string giving the name of a predefined function. Each high-level function has its own default panel function, named as “`panel.`” followed by the name of the corresponding high-level function (e.g., `panel.xyplot`, `panel.barchart`, etc). 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 is useful to know in this context that all arguments passed to a high-level Lattice 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 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, as there are several predefined panel functions which can help; for example, `panel.grid`, `panel.loess`, etc. There are also some grid-compatible replacements of commonly used traditional graphics functions useful for this purpose. For example, `lines` can be replaced by `llines` (or equivalently, `panel.lines`). Note that traditional 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). A useful panel function predefined for use in such cases is `panel.superpose`, which can be combined with different `panel.groups` functions to determine 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 `xyplot`, `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 interpretation of `subscripts` does not hold when the extended formula interface is in use (i.e., when `allow.multiple` is in effect). A comprehensive description would be too complicated (details can be found in the source code of the function `latticeParseFormula`), but in short, the extended interface works by creating an artificial grouping variable that is longer than the original data frame, and consequently, `subscripts` needs to refer to rows beyond those in the original data. To further complicate matters, the artificial grouping variable is created after any effect of `subset`, in which case `subscripts` may have no relationship with corresponding rows in the original data frame. One can also use functions called `panel.number` and `packet.number`, representing panel order and packet order respectively, inside the panel function (as well as the strip function or while interacting with a lattice display using `trellis.focus` etc). Both provide a simple integer index indicating which panel is currently being drawn, but differ in how the count is calculated. The panel number is a simple incremental counter that starts with 1 and is incremented each time a panel is drawn. The packet number on the other hand indexes 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 `packet.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). In the event that a `groups` variable is used, `panel.xyplot` calls `panel.superpose`, arguments of which can also be passed directly to `xyplot`. Panel functions for `bwplot` and friends should have an argument called `horizontal` to account for the cases when `x` is the factor or shingle.

`aspect` | This argument controls the physical aspect ratio of the panels, which is usually the same for all the panels. It can be specified as a ratio (vertical size/horizontal size) or as a character string. In the latter case, legitimate values are `"fill"` (the default) which tries to make the panels as big as possible to fill the available space; `"xy"`, which computes the aspect ratio based on the 45 degree banking rule (see `banking`); 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. Not all default prepanel functions produce sensible banking calculations.
`groups` | A variable or expression to be evaluated in `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. For high level functions where grouping is appropriate, the default panel functions can handle grouping. 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, or a list containing components to be used as arguments to `simpleKey`. `auto.key=TRUE` is equivalent to `auto.key=list()`, in which case `simpleKey` is called with a set of default arguments (which may depend on the relevant high-level function). Most valid components to the `key` argument can be specified in this manner, as `simpleKey` will simply add unrecognized arguments to the list it produces. `auto.key` is typically used to automatically produce a suitable legend in conjunction with a grouping variable. If `auto.key=TRUE`, a suitable legend will be drawn if a `groups` argument is also provided, and not otherwise. In list form, `auto.key` will modify the default legend thus produced. For example, `auto.key=list(columns = 2)` will create a legend split into two columns (`columns` is documented in the entry for `key`). More precisely, 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 (`text`) 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). If `auto.key` is provided as a list and includes a `text` component, then that is used instead as the text labels in the key, and the key is drawn even if `groups` is not specified. Note that `simpleKey` uses the default settings (see `trellis.par.get`) to determine the graphical parameters in the key, so the resulting legend will be meaningful only if the same settings are used in the plot as well. The `par.settings` argument may be useful to temporarily modify the default settings for this purpose. 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-`plot`-ted with different settings, the original parameter settings will be used for the key even though the new settings are used for the actual display. However, with `auto.key`, the key is actually created at plotting time, so the settings will match.
`prepanel` | A 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 return value of a user-supplied prepanel function need not contain all these components; in case some are missing, they are replaced by the component-wise defaults. 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, or a character vector representing levels of a factor). If the `xlim` and `ylim` arguments are not explicitly specified (possibly as components in `scales`) in the high-level call, 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 per-panel basis otherwise. The `dx` and `dy` components are used for banking computations in case `aspect` is specified as `"xy"`. See documentation of `banking` for details. 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 zero-length vectors. When nothing else is appropriate, values of NA should be returned for the `xlim` and `ylim` components.
`strip` | A 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. This description also applies to the `strip.left` argument (see `...` below), which can be used to draw strips on the left of each panel (useful for wide short panels, e.g., in time-series plots).
`xlab` | Character or expression (or a `"grob"`) giving label(s) for the x-axis. Generally defaults to the expression for `x` in the formula defining the plot. Can be specified as `NULL` to omit the label altogether. Finer control is possible, as described in the entry for `main`, with the modification that if the `label` component is omitted from the list, it is replaced by the default `xlab`.
`ylab` | Character or expression (or `"grob"`) giving label for the y-axis. Generally defaults to the expression for `y` in the formula defining the plot. Finer control is possible, see entries for `main` and `xlab`.
`scales` | Generally a 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. Note that certain high-level functions have defaults that are specific to a particular axis (e.g., `bwplot` has `alternating=FALSE` for the categorical axis only); these can only be overridden by an entry in the corresponding component of `scales`. As a special exception, `scales` (or its `x` and `y` components) can also be a character string, in which case it is interpreted as the `relation` component. The possible components are : `relation` A character string that determines how axis limits are calculated for each panel. Possible values are `"same"` (default), `"free"` and `"sliced"`. For `relation="same"`, the same limits, usually large enough to encompass all the data, are used for all the panels. For `relation="free"`, limits for each panel is determined by just the points in that panel. Behavior for `relation="sliced"` is similar, except that the length (max - min) of the scales are constrained to remain the same across panels. The determination of what axis limits are suitable for each panel can be controlled by the `prepanel` function, which can be overridden by `xlim`, `ylim` or `scales$limits` (except when `relation="sliced"`, in which case explicitly specified limits are ignored with a warning). When `relation` is `"free"`, `xlim` or `ylim` can be a list, in which case it is treated as if its components were the limit values obtained from the prepanel calculations for each panel (after being replicated if necessary). `tick.number` An integer, giving the suggested number of intervals between ticks. This is ignored for a factor, shingle, or character vector, for in these cases there is no natural rule for leaving out some of the labels. But see `xlim`. `draw` A logical flag, defaulting to `TRUE`, that determines whether to draw the axis (i.e., tick marks and labels) at all. `alternating` Usually a logical flag specifying whether axis labels should alternate from one side of the group of panels to the other. For finer control, `alternating` can also be a vector (replicated to be as long as the number of rows or columns per page) consisting of the following numbers 0: do not draw tick labels 1: bottom/left 2: top/right 3: both. `alternating` applies only when `relation="same"`. The default is `TRUE`, or equivalently, `c(1, 2)` `limits` Same as `xlim` and `ylim`. `at` The 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` Vector of labels (characters or expressions) to go along with `at`. Can also be a list like `at`. `cex` A numeric multiplier to control character sizes for axis labels. Can be a vector of length 2, to control left/bottom and right/top labels separately. `font`, `fontface`, `fontfamily` Specifies the font to be used for axis labels. `lineheight` Specifies the line height parameter (height of line as a multiple of the size of text); relevant for multi-line labels. (This is currently ignored for `cloud`.) `tck` Usually a numeric scalar controlling the length of tick marks. Can also be a vector of length 2, to control the length of left/bottom and right/top tick marks separately. `col` Color of tick marks and labels. `rot` Angle (in degrees) by which the axis labels are to be rotated. Can be a vector of length 2, to control left/bottom and right/top axes separately. `abbreviate` A logical flag, indicating whether to abbreviate the labels using the `abbreviate` function. Can be useful for long labels (e.g., in factors), especially on the x-axis. `minlength` Argument passed to `abbreviate` if `abbreviate=TRUE`. `log` Controls whether the corresponding variable (`x` or `y`) will be log transformed before being passed to the panel function. Defaults to `FALSE`, in which case the data are not transformed. Other possible values are any number that works as a base for taking logarithm, `TRUE` (which is equivalent to 10), and `"e"` (for the natural logarithm). As a side effect, the corresponding axis is labeled differently. Note that this is in reality a transformation of the data, not the axes. Other than the axis labeling, using this feature is no different than transforming the data in the formula; e.g., `scales=list(x = list(log = 2))` is equivalent to `y ~ log2(x)`. See entry for `equispaced.log` below for details on how to control axis labeling. `equispaced.log` A logical flag indicating whether tick mark locations should be equispaced when ‘log scales’ are in use. Defaults to `TRUE`. Tick marks are always labeled in the original (untransformed) scale, but this makes the choice of tick mark locations nontrivial. If `equispaced.log` is `FALSE`, the choice made is similar to how log scales are annotated in traditional graphics. If `TRUE`, tick mark locations are chosen as ‘pretty’ equispaced values in the transformed scale, and labeled in the form `"base^loc"`, where `base` is the base of the logarithm transformation, and `loc` are the locations in the transformed scale. See also `xscale.components.logpower` in the latticeExtra package. `format` The `format` to use for POSIXct variables. See `strptime` for description of valid values. `axs` A character string, `"r"` (default) 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 that much of the function of `scales` is accomplished by `pscales` in `splom`.
`subscripts` | A logical flag 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`. This argument is useful if one wants the subscripts to be passed on even if these conditions do not hold; a typical example is when one wishes to augment a Lattice plot after it has been drawn, e.g., using `panel.identify`.
`subset` | An expression that evaluates to a logical or integer indexing vector. Like `groups`, it is evaluated in `data`. Only the resulting rows of `data` are used for the plot. If `subscripts` is `TRUE`, the subscripts provided to the panel function will be indices referring to the rows of `data` prior to the subsetting. Whether levels of factors in the data frame that are unused after the subsetting will be dropped depends on the `drop.unused.levels` argument.
`xlim` | Normally a numeric vector (or a DateTime object) of length 2 giving left and right limits 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"`, in which case these are treated as if they were the corresponding limit components returned by prepanel calculations.
`ylim` | Similar to `xlim`, applied to the y-axis.
`drop.unused.levels` | A logical flag indicating whether the unused levels of factors will be dropped, usually relevant with a subsetting operation is performed or an `interaction` is created. Unused levels are usually dropped, but it is sometimes appropriate to suppress dropping to preserve a useful layout. For finer control, this argument could also be list containing components `cond` and `data`, both logical, indicating desired behavior for conditioning variables and primary variables respectively. The default is given by `lattice.getOption("drop.unused.levels")`, which is initially set to `TRUE` for both components. Note that this argument does not control dropping of levels of the `groups` argument.
`default.scales` | A list giving the default values of `scales` for a particular high-level function. This is rarely of interest to the end-user, but may be helpful when defining other functions that act as a wrapper to one of the high-level Lattice functions.
`default.prepanel` | A function or character string giving the name of a function that serves as the (component-wise) fallback prepanel function when the `prepanel` argument is not specified, or does not return all necessary components. The main purpose of this argument is to enable the defaults to be overridden through the use of `lattice.options`.
`lattice.options` | A list that could be supplied to `lattice.options`. These options are applied temporarily for the duration of the call, after which the settings revert back to what they were before. The options are retained along with the object and reused during plotting. This enables the user to attach options settings to the trellis object itself rather than change the settings globally. See also the `par.settings` argument described below for a similar treatment of graphical settings.
`...` | Further arguments, usually not directly processed by the high-level functions documented here, but instead passed on to other functions. Such arguments can be broadly categorized into two types: those that affect all high-level Lattice functions in a similar manner, and those that are meant for the specific panel function being used. The first group of arguments are processed by a common, unexported function called `trellis.skeleton`. These arguments affect all high-level functions, but are only documented here (except to override the behaviour described here). All other arguments specified in a high-level call, specifically those neither described here nor in the help page of the relevant high-level function, are passed unchanged to the panel function used. By convention, the default panel function used for any high-level function is named as “`panel.`” followed by the name of the high-level function; for example, the default panel function for `bwplot` is `panel.bwplot`. In practical terms, this means that in addition to the help page of the high-level function being used, the user should also consult the help page of the corresponding panel function for arguments that may be specified in the high-level call. The effect of the first group of common arguments are as follows: `as.table`: A logical flag that controls the order in which panels should be displayed: 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 (as in a table). `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 multi page display. In other words, it is not possible to use different `between` values for different pages. `key`: A list that defines a legend to be drawn on the plot. This list is used as an argument to the `draw.key` function, which produces a `"grob"` (grid object) eventually plotted by the print method for `"trellis"` objects. The structure of the legend is constrained in the ways described below. Although such a list can be and often is created explicitly, it is also possible to generate such a list using the `simpleKey` function; the latter is more convenient but less flexible. The `auto.key` argument can be even more convenient for the most common situation where legends are used, namely, in conjunction with 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 is usually one of `c(0,0)`, `c(1,0)`, `c(1,1)` and `c(0,1)`, which denote the corners of the unit square. Fractional values are also allowed, in which case `x` and `y` determine the position of an arbitrary point inside (or outside for values outside the unit interval) the key. `x` and `y` should be numbers between 0 and 1, giving coordinates with respect to the “display area”. Depending on the value of the `"legend.bbox"` option (see `lattice.getOption`), this can be either the full figure region (`"full"`), or just the region that bounds the panels and strips (`"panel"`). 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 must have a character or expression vector as its first component, to be used as labels. 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: `cex=1` (text, lines, points) `col="black"` (text, rectangles, lines, points) `alpha=1` (text, rectangles, lines, points) `fill="transparent"` (lines, points) `lty=1` (lines) `lwd=1` (lines, points) `font=1` (text, points) `fontface` (text, points) `fontfamily` (text, points) `pch=8` (lines, points) `adj=0` (text) `type="l"` (lines) `size=5` (rectangles, lines) `height=1` (rectangles) `lineheight=1` (text) `angle=0` (rectangles, but ignored) `density=-1` (rectangles, but ignored) In addition, the component `border` can be included inside the `"rect"` component to control the border color of the rectangles; when specified at the top level, `border` controls the border of the entire key (see below). `angle` and `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. `height` gives heights of rectangles as a fraction of the default. Other possible components of `key` are: `reverse.rows` Logical flag, defaulting to `FALSE`. If `TRUE`, all components are reversed after being replicated (the details of which may depend on the value of `rep`). This is useful in certain situations, e.g., with a grouped `barchart` with `stack = TRUE` with the categorical variable on the vertical axis, where the bars in the plot will usually be ordered from bottom to top, but the corresponding legend will have the levels from top to bottom unless `reverse.rows = TRUE`. Note that in this case, unless all columns have the same number or rows, they will no longer be aligned. `between` Numeric vector giving the amount of space (character widths) surrounding each column (split equally on both sides). `title` String or expression giving a title for the key. `rep` Logical flag, defaults to `TRUE`. By default, it is 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 column alone. `cex.title` Zoom factor for the title. `lines.title` The amount of vertical space to be occupied by the title in lines (in multiples of itself). Defaults to 2. `padding.text` The amount of space (padding) to be used above and below each row containing text, in multiples of the default, which is currently `0.2 * "lines"`. This padding is in addition to the normal height of any row that contains text, which is the minimum amount necessary to contain all the text entries. `background` Background color for the legend. Defaults to the global background color. `alpha.background` An alpha transparency value between 0 and 1 for the background. `border` Either a color for the border, or a logical flag. In the latter case, the border color is black if `border` is `TRUE`, and no border is drawn if it is `FALSE` (the default). `transparent=FALSE` Logical flag, whether legend should have a transparent background. `just` A character or numeric vector of length one or two giving horizontal and vertical justification for the placement of the legend. See `grid.layout` for more precise details. `columns` The number of column-blocks (drawn side by side) the legend is to be divided into. `between.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 the use of 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 for `key`. `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. `xlab.top`, `ylab.right`: Labels for the x-axis on top, and y-axis on the right. Similar to `xlab` and `ylab`, but less commonly used. `main`: Typically a character string or expression describing the main title to be placed on top of each page. Defaults to `NULL`. `main` (as well as `xlab`, `ylab` and `sub`) is usually a character string or an expression that gets used as the label, but can also be a list that controls further details. Expressions are treated as specification of LaTeX-like markup as described in `plotmath`. The label can be a vector, in which case the components will be spaced out horizontally (or vertically for `ylab`). This feature can be used to provide column or row labels rather than a single axis label. When `main` (etc.) is a list, the actual label should be specified as the `label` component (which may be unnamed if it is the first component). The label can be missing, in which case the default will be used (`xlab` and `ylab` usually have defaults, but `main` and `sub` do not). Further named arguments are passed on to `textGrob`; this can include arguments controlling positioning like `just` and `rot` as well as graphical parameters such as `col` and `font` (see `gpar` for a full list). `main`, `sub`, `xlab`, `ylab`, `xlab.top`, and `ylab.right` can also be arbitrary `"grob"`s (grid graphical objects). `sub`: Character string or expression (or a list or `"grob"`) for a subtitle to be placed at the bottom of each page. See entry for `main` for finer control options. `par.strip.text`: A list of parameters to control the appearance of strip text. Notable 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. Additionally, the `lineheight` component can control the space between multiple lines. The labels can be abbreviated when shown by specifying `abbreviate = TRUE`, in which case the components `minlength` and `dot` (passed along to the `abbreviate` function) can be specified to control the details of how this is done. `layout`: In general, a conditioning plot in Lattice consists of several panels arranged in a rectangular array, possibly spanning multiple pages. `layout` determines this arrangement. `layout` is a numeric vector of length 2 or 3 giving the number of columns, rows, and pages (optional) 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")`). If `NA` is specified for the number of rows or columns (but not both), that dimension will be filled out according to the number of panels. The number of pages is by default set to as many as is required to plot all the panels, and so rarely needs to be specified. However, in certain situations the default calculation may be incorrect, and in that case the number of pages needs to be specified explicitly. `skip`: A 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 may be useful for arranging plots in an informative manner. `strip.left`: `strip.left` can be used to draw strips on the left of each panel, which can be useful for wide short panels, as in time-series (or similar) plots. See the entry for `strip` for detailed usage. `xlab.default`, `ylab.default`: Fallback default for `xlab` and `ylab` when they are not specified. If `NULL`, the defaults are parsed from the Trellis formula. This is rarely useful for the end-user, but can be helpful when developing new Lattice functions. `xscale.components`, `yscale.components`: Functions that determine axis annotation for the x and y axes respectively. See documentation for `xscale.components.default`, the default values of these arguments, to learn more. `axis`: Function responsible for drawing axis annotation. See documentation for `axis.default`, the default value of this argument, to learn more. `perm.cond`: An integer 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 does in `aperm`. `index.cond`: Whereas `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 behavior 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 `levels(g_i)`, where `g_i` is the `i`-th conditioning variable in the plot (note that these levels may not contain all levels of the original variable, depending on the effects of the `subset` and `drop.unused.levels` arguments). In particular, this indexing may repeat 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 interpreted 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.) If there is only one 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 re-calculating the data subsets that go into each panel. In the `update.trellis` method, both can be set to `NULL`, which reverts these back to their defaults. `par.settings`: A list that could be supplied to `trellis.par.set`. When the resulting object is plotted, these options are applied temporarily for the duration of the plotting, after which the settings revert back to what they were before. This enables the user to attach some display settings to the trellis object itself rather than change the settings globally. See also the `lattice.options` argument described above for a similar treatment of non-graphical options. `plot.args`: A list containing possible arguments to `plot.trellis`, which will be used by the `plot` or `print` methods when drawing the object, unless overridden explicitly. This enables the user to attach such arguments to the trellis object itself. Partial matching is not performed.

### Details

The high-level functions documented here, as well as other high-level Lattice functions, are generic, with the `formula` method usually doing the most substantial work. The structure of the plot that is produced is mostly controlled by the formula (implicitly in the case of the non-formula methods). For each unique combination of the levels of the conditioning variables `g1, g2, ...`, a separate “packet” is produced, consisting of the points `(x,y)` for the subset of the data defined by that combination. The display can be thought of as a three-dimensional array of panels, consisting of one two-dimensional matrix per page. The dimensions of this array are determined by the `layout` argument. If there are no conditioning variables, the plot produced consists of a single packet. Each packet usually corresponds to one panel, but this is not strictly necessary (see the entry for `index.cond` above).

The coordinate system used by lattice by default is like a graph, with the origin at the bottom left, with axes increasing to the right and top. 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. It is possible to set a global preference for the table-like arrangement by changing the default to `as.table=TRUE`; this can be done by setting `lattice.options(default.args = list(as.table = TRUE))`. 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, followed by `g2`, and so on. 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` (and other related) method(s).

### Value

The high-level functions documented here, as well as other high-level Lattice functions, return an object of class `"trellis"`. The `update` method can be used to subsequently update components of the object, and the `print` method (usually called by default) will plot it on an appropriate plotting device.

### Note

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.

### Author(s)

Deepayan Sarkar Deepayan.Sarkar@R-project.org

### References

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

### See Also

`Lattice` for an overview of the package, as well as `barchart.table`, `print.trellis`, `shingle`, `banking`, `reshape`, `panel.xyplot`, `panel.bwplot`, `panel.barchart`, `panel.dotplot`, `panel.stripplot`, `panel.superpose`, `panel.loess`, `panel.average`, `strip.default`, `simpleKey` `trellis.par.set`

### Examples

    require(stats)

    ## Tonga Trench Earthquakes

    Depth <- equal.count(quakes$depth, number=8, overlap=.1)
    xyplot(lat ~ long | Depth, data = quakes)
    update(trellis.last.object(),
           strip = strip.custom(strip.names = TRUE, strip.levels = TRUE),
           par.strip.text = list(cex = 0.75),
           aspect = "iso")

    ## Examples with data from `Visualizing Data' (Cleveland, 1993) obtained
    ## from http://cm.bell-labs.com/cm/ms/departments/sia/wsc/

    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")

    ## Extended formula interface

    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, labels = groups[subscripts], cex=1,
                     fontfamily = "HersheySans")
           })

    ## Stacked bar chart

    barchart(yield ~ variety | site, data = barley,
             groups = year, layout = c(1,6), stack = TRUE,
             auto.key = list(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)

    ## Grouped dot plot showing anomaly at Morris

    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.data = TRUE, xlab = "Height (inches)")

    ## Interaction Plot

    xyplot(decrease ~ treatment, OrchardSprays, groups = rowpos,
           type = "a",
           auto.key =
           list(space = "right", points = FALSE, lines = TRUE))

    ## longer version with no x-ticks

    ## Not run:
    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"))

    ## End(Not run)

[Package lattice version 0.20-6 Index]