layer: Add layers to a Trellis plot, optionally using a new data source

Description

A mechanism to add new layers to a trellis object, optionally using a new data source. This is an alternative to modifying the panel function. Note the non-standard evaluation in layer().

Usage

layer(..., data, magicdots, exclude,
      packets, rows, columns, groups,
      style, force, theme, under, superpose, 
      eval, etc) ## these 2 deprecated

layer_(...)
glayer(...)
glayer_(...)

## S3 method for class 'trellis':
+(object, lay)

drawLayer(lay)

flattenPanel(object)

Arguments

...

expressions as they would appear in a panel function. These can refer to the panel function arguments (such as x, y and subscripts), and also to any named objects passed in through the data

data

optional. A named list containing objects needed when evaluating (drawing) the layer.

magicdots, exclude

if magicdots = TRUE, the default, any reference to ... in the layer expressions will only pass on those arguments from the panel function which are not named in the call (thus avoiding dupli

packets, rows, columns, groups

restricts the layer to draw only in specified packets (which refer to individual panels, but are independent of their layout), or rows or columns of the trellis layout (trellis.currentLayout

style

style index of the layer, used only to set lattice graphical parameters (same effect as in grouped displays). Note that this will use the theme settings in effect in the existing plot, which may or may not be what is desired. It may be nece

force

force = TRUE is just a shorthand for theme = trellis.par.get(), which is useful for over-riding the theme settings in effect in an existing plot. For instance, if the original plot specified par.settings = si

theme

a style specification to be passed to trellis.par.set which has effect only while drawing the layer. One can pass a whole theme specification list, such as theme = custom.theme()

under

whether the layer should be drawn before the existing panel function. This defaults to TRUE in the convenience functions layer_() and glayer_().

superpose

if TRUE, the layer will be drawn once for each level of any groups in the plot, using panel.superpose. This defaults to TRUE in the convenience

eval, etc

These two arguments are now Deprecated and should not be used in new code. Rather than using eval, use data. It is not necessary to use etc because that happens automatically with magicdots

object

a trellis object.

lay

a layer object.

Details

The layer mechanism is a method for augmenting a panel function. It allows expressions to be added to the panel function without knowing what the original panel function was. In this way it can be useful for convenient augmentation of trellis plots. Note that the evaluation used in layer is non-standard, and can be confusing at first: you typically refer to variables as if inside the panel function (x, y, etc); you can usually refer to objects which exist in the global environment (workspace), but it is safer to pass them in by name in the data argument to layer. (And this should not to be confused with the data argument to the original xyplot.) A simple example is adding a reference line to each panel: layer(panel.refline(h = 0)). Note that the expressions are quoted, so if you have local variables they will need to be either accessible globally, or passed in via the data argument. For example:

layer(panel.refline(h = myVal)) ## if myVal is global}

  layer(panel.refline(h = h), data = list(h = myVal))

  Another non-standard aspect is that the special argument
  ... will, by default, only pass through those
  argument not already named. For example, this will over-ride the
  x argument and pass on the remaining arguments:

  layer(panel.xyplot(x = jitter(x), ...))

  The first un-named argument is assumed to be "x", so that is the same as

  layer(panel.xyplot(jitter(x), ...))

  The layer mechanism should probably still be considered experimental.

  drawLayer() actually draws the given layer object, applying the
  panel specification, style settings and so on. It should only be
  called while a panel is in focus.

  The flattenPanel function will construct a human-readable
  function incorporating code from all layers (and the original panel
  function). Note that this does not return a usable function, as it
  lacks the correct argument list and ignores any extra data sources
  that layers might use. It is intended be edited manually.

a layer object is defined as a list of expression objects, each of which may have a set of attributes. The result of "adding" a layer to a trellis object (+.trellis) is the updated trellis object. [object Object] update.trellis, as.layer for overlaying entire plots foo <- xyplot(ozone ~ wind, environmental) foo ## overlay reference lines foo <- foo + layer(panel.abline(h = 0)) + layer(panel.lmline(x, y, lty = 2)) ## underlay a flat color foo <- foo + layer(panel.fill(grey(.98)), under = TRUE) foo ## layers can access the panel function arguments foo <- foo + layer({ ok <- (y>100); panel.text(x[ok], y[ok], y[ok], pos = 1) }) foo ## over-ride arguments by name foo <- foo + layer(panel.xyplot(y = ave(y, x, FUN = max), type = "a", ...)) foo ## see a sketch of the complete panel function flattenPanel(foo) ## group layers, drawn for each group in each panel dotplot(VADeaths, type = "o") + glayer(ltext(x[5], y[5], group.value, srt = 40)) ## a quick way to print out the panel.groups arguments: dotplot(VADeaths, type = "o") + glayer(str(list(...))) ## layers with superposed styles zoip <- xyplot(ozone ~ wind | equal.count(temperature, 2), data = environmental) + layer(panel.loess(x, y, span = 0.5), style = 1) + layer(panel.loess(x, y, span = 1.0), style = 2) update(zoip, auto.key = list(text = c("span = 0.5", "span = 1.0"), title = "loess smooth", lines = TRUE, points = FALSE)) ## note that styles come from the settings in effect in the plot, ## which is not always what you want: xyplot(1:10 ~ 1:10, type = "b", par.settings = simpleTheme(col = "red")) + layer(panel.lines(x = jitter(x, 2), ...)) + ## drawn in red layer(panel.lines(x = jitter(x, 2), ...), force = TRUE) ## reset theme ## using other variables from the original `data` object ## NOTE: need subscripts = TRUE in original call! zoip <- xyplot(wind ~ temperature | equal.count(radiation, 2), data = environmental, subscripts = TRUE) zoip + layer(panel.points(..., pch = 19, col = grey(1 - ozone[subscripts] / max(ozone))), data = environmental) ## restrict drawing to specified panels barchart(yield ~ variety | site, data = barley, groups = year, layout = c(1,6), as.table = TRUE, scales = list(x = list(rot = 45))) + layer(ltext(tapply(y, x, max), lab = abbreviate(levels(x)), pos = 3), rows = 1) ## example of a new data source qua <- xyplot(lat ~ long | cut(depth, 2), quakes, aspect = "iso", pch = ".", cex = 2) qua .featured_example <- TRUE ## add layer showing distance from Auckland newdat <- with(quakes, expand.grid( gridlat = seq(min(lat), max(lat), length = 60), gridlon = seq(min(long), max(long), length = 60))) newdat$dist <- with(newdat, sqrt((gridlat - -36.87)^2 + (gridlon - 174.75)^2)) qua + layer_(panel.contourplot(x = gridlon, y = gridlat, z = dist, contour = TRUE, subscripts = TRUE), data = newdat) aplot