Title: New and Extended Plots, Methods, and Panel Functions for 'lattice'
Version: 0.2.1
Description: Extensions to 'lattice', providing new high-level functions, methods for existing functions, panel functions, and a theme.
Depends: R (≥ 3.4.0), lattice
Imports: grDevices, grid, gridExtra, latticeExtra, MASS, RColorBrewer, stats, utils
Suggests: covr, forecast, knitr, rmarkdown, spelling, testthat, zoo
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
URL: https://github.com/jolars/tactile
BugReports: https://github.com/jolars/tactile/issues
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2023-05-24 10:11:18 UTC; gerd-jln
Author: Johan Larsson ORCID iD [aut, cre], Deepayan Sarkar [ctb, cph] (lattice), Brian Ripley [ctb] (stats::plot.acf)
Maintainer: Johan Larsson <johanlarsson@outlook.com>
Repository: CRAN
Date/Publication: 2023-05-24 10:50:02 UTC

tactile: New and Extended Plots, Methods, and Panel Functions for 'lattice'

Description

Extensions to 'lattice', providing new high-level functions, methods for existing functions, panel functions, and a theme.

Author(s)

Maintainer: Johan Larsson johanlarsson@outlook.com (ORCID)

Other contributors:

See Also

Useful links:

Bubbleplots

Description

Draws bubbleblots – trivariate plots where the third dimension is mapped to the size of the points drawn on the screen.

Usage

bubbleplot(x, data = NULL, ...)

## S3 method for class 'formula'
bubbleplot(
  x,
  data = NULL,
  maxsize = 3,
  bubblekey = TRUE,
  panel = panel.bubbleplot,
  groups = NULL,
  subset = TRUE,
  drop.unused.levels = lattice.getOption("drop.unused.levels"),
  ...,
  outer,
  allow.multiple
)

Arguments

x

A formula of the form z ~ x * y, where x and y have the usual interpretation in trellis graphics (see lattice::xyplot()) and z is mapped to the size of bubbles.

data

A data.frame, list or environment wherein the formula and groups arguments can be evaluated.

...

Further arguments to pass to lattice::xyplot().

maxsize

Maximum size (in cex) for the bubbles.

bubblekey

Set to TRUE to draw an informative legend about the bubbles. Uses lattice::draw.key(). See the key section of the documentation in lattice::xyplot(). If both auto.key and bubblekey are given and their space arguments (positions) conflict, bubblekey will silently override the position of auto.key.

panel

See lattice::xyplot(). Here, we are passing an additional variable, z, which is then used in panel.bubbleplot().

groups

See lattice::xyplot()

subset

See lattice::xyplot()

drop.unused.levels

See lattice::xyplot()

outer

Ignored.

allow.multiple

Ignored.

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)

Johan Larsson

Examples

bubbleplot(disp ~ hp * wt, groups = cyl, data = mtcars, auto.key = TRUE)
bubbleplot(disp ~ hp * mpg | factor(cyl), groups = gear, data = mtcars,
           auto.key = TRUE)

An extended box and whiskers plot

Description

An extended version of lattice::bwplot(). The only modification is to group and stack box plots if groups is provided.

Usage

bwplot2(x, data = NULL, ...)

## S3 method for class 'formula'
bwplot2(
  x,
  data = NULL,
  allow.multiple = is.null(groups) || outer,
  outer = FALSE,
  auto.key = FALSE,
  groups = NULL,
  drop.unused.levels = lattice.getOption("drop.unused.levels"),
  ...,
  subset = TRUE
)

## S3 method for class 'numeric'
bwplot2(x, data = NULL, xlab = deparse(substitute(x)), ...)

Arguments

x

see lattice::bwplot()

data

see lattice::bwplot()

...

arguments passed down to lattice::bwplot()

allow.multiple

see lattice::bwplot()

outer

see lattice::bwplot()

auto.key

see lattice::bwplot()

groups

see lattice::bwplot()

drop.unused.levels

see lattice::bwplot()

subset

see lattice::bwplot()

xlab

see lattice::bwplot()

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.

Examples

bwplot2(variety ~ yield,
        groups = site,
        data = barley,
        par.settings = tactile.theme())

Diagonal Density Panels

Description

Plots univariate density estimates estimates to be used in a lattice::splom() call with the diag.panel argument.

Usage

diag.panel.splom.density(
  x,
  bw = "nrd0",
  adjust = 1,
  kernel = "gaussian",
  weights = NULL,
  n = 512,
  ...
)

Arguments

x

data vector corresponding to that row / column (which will be the same for diagonal 'panels').

bw

the smoothing bandwidth to be used. The kernels are scaled such that this is the standard deviation of the smoothing kernel. (Note this differs from the reference books cited below, and from S-PLUS.)

bw can also be a character string giving a rule to choose the bandwidth. See bw.nrd.
The default, "nrd0", has remained the default for historical and compatibility reasons, rather than as a general recommendation, where e.g., "SJ" would rather fit, see also Venables and Ripley (2002).

The specified (or computed) value of bw is multiplied by adjust.

adjust

the bandwidth used is actually adjust*bw. This makes it easy to specify values like ‘half the default’ bandwidth.

kernel

the smoothing kernel to be used. See stats::density() for options.

weights

numeric vector of non-negative observation weights, hence of same length as x. The default NULL is equivalent to weights = rep(1/nx, nx) where nx is the length of (the finite entries of) x[]. If na.rm = TRUE and there are NA's in x, they and the corresponding weights are removed before computations. In that case, when the original weights have summed to one, they are re-scaled to keep doing so.

Note that weights are not taken into account for automatic bandwidth rules, i.e., when bw is a string. When the weights are proportional to true counts cn, density(x = rep(x, cn)) may be used instead of weights.

n

the number of equally spaced points at which the density is to be estimated. When n > 512, it is rounded up to a power of 2 during the calculations (as fft is used) and the final result is interpolated by approx. So it almost always makes sense to specify n as a power of two.

...

Further arguments passed on to lattice::diag.panel.splom() and lattice::panel.lines().

See Also

lattice::diag.panel.splom(), lattice::splom(), stats::density().

Examples

splom(~ iris[1:4],
  data = iris,
  diag.panel = diag.panel.splom.density,
  pscales = 0
)

Suppress Plotting

Description

Suppress Plotting

Usage

dont_plot(x, ...)

Arguments

x

Object to call graphics::plot() on.

Value

Invisibly returns whatever plot(x) would normally returns, but does not plot anything (which is the point).

Ternary feldspar experiments and thermodynamic models

Description

A data set that has been manually transcribed from Table 5 of Elkins and Grove's Ternary feldspar experiments and thermodynamic models.

Usage

feldspar

Format

A data frame of 40 rows and 7 columns:

Experiment

The ID of the experiment

Feldspar

Coexisting feldspars, Alkali or Plagioclase

Or

Proportion of orthoclase

An

Proportion of anorthite

Ab

Proportion of albite

Temperature

Temperature of the reaction (degrees centigrade)

Pressure

Pressure of the reaction (bars)

Abstract

This paper reports the results of 20 experiments in which mixes of two or three feldspars were reacted to produce coexisting plagioclase feldspar (PF) and alkali feldspar (AF). Starting materials with similar bulk compositions were prepared using different combinations of two and three minerals, and experiments were designed to produce similar AF and PF minerals in the experimental products from different starting binary and ternary compositions. The coexisting AF and PF compositions produced as products define compositional fields that are elongate parallel to the ternary solvus. In 11 experiments reaction was sufficient to product fields of coexisting AF and PF, or AF, PF, and melt with a bulk composition close to that of the starting mixture. In six experiments significant reaction occurred in the form of reaction rim overgrowths on seeds of the starting materials. Three experiments produced AF, PF, and melt from a natural granite starting material. A two-feldspar thermometer is presented in which temperature is constrained by equilibria among all three components - Albite, Orthoclase, and Anorthite - in coexisting ternary feldspars.

Source

Elkins LT, Grove TL. Ternary feldspar experiments and thermodynamic models. American Mineralogist. 1990;75(5-6):544-59.

Retrieve a Function by Name or Definition

Description

Retrieve a Function by Name or Definition

Usage

get_fun(fun)

Arguments

fun

Character or function.

Wrapper for grid.arrange

Description

Wrapper for grid.arrange

Usage

grid_wrap(x, layout = NULL)

Arguments

x

List of trellis objects.

layout

A layout matrix or vector specifying rows and columns

Value

A list of trellis objects.

Make Bubbles

Description

Map z to the area of bubbles.

Usage

make_bubbles(x, maxsize)

Arguments

x

A numeric vector.

maxsize

The max size (in cex) of the bubbles.

Value

A list with the new bubbles as well as pretty breakpoints along with their respective cex values.

Panel Function for Bubble Plots

Description

Panel Function for Bubble Plots

Usage

panel.bubbleplot(x, y, z, groups = NULL, subscripts, cex = NULL, ...)

Arguments

x, y

variables to be plotted in the scatterplot

z

A numeric vector that areas of circles will be mapped to.

groups

Grouping variable (see lattice::xyplot()).

subscripts

A vector of indexes to specify which observation to plot. Normally does not need to be provided by the user.

cex

Is used internally and user settings will be ignored.

...

Further arguments to pass to lattice::panel.xyplot().

Value

Plots a layer inside a panel of a lattice plot.

Panel function for confidence interval

Description

Panel function for confidence interval

Usage

panel.ci(
  x,
  y,
  lower,
  upper,
  groups = NULL,
  subscripts,
  col,
  fill = if (is.null(groups)) plot.line$col else superpose.line$col,
  alpha = 0.15,
  lty = 0,
  lwd = if (is.null(groups)) plot.line$lwd else superpose.line$lwd,
  grid = FALSE,
  ...,
  col.line = if (is.null(groups)) plot.line$col else superpose.line$col
)

Arguments

x, y

variables to be plotted in the scatterplot

lower

lower confidence limits

upper

upper confidence limits

groups

an optional grouping variable. If present, panel.superpose will be used instead to display each subgroup

subscripts

see lattice::xyplot()

col

line color

fill

fill color

alpha

opacity for the fill

lty

line type

lwd

line width

grid

A logical flag, character string, or list specifying whether and how a background grid should be drawn. This provides the same functionality as type="g", but is the preferred alternative as the effect type="g" is conceptually different from that of other type values (which are all data-dependent). Using the grid argument also allows more flexibility.

Most generally, grid can be a list of arguments to be supplied to panel.grid, which is called with those arguments. Three shortcuts are available:

TRUE:

roughly equivalent to list(h = -1, v = -1)

"h":

roughly equivalent to list(h = -1, v = 0)

"v":

roughly equivalent to list(h = 0, v = -1)

No grid is drawn if grid = FALSE.

...

Extra arguments, if any, for panel.xyplot. Usually passed on as graphical parameters to low level plotting functions, or to the panel functions performing smoothing, if applicable.

col.line

line color. Supersedes col if both are specified.

Examples

mod <- lm(Petal.Width ~ Petal.Length * Species, data = iris)
newdat <- expand.grid(
  Petal.Length = seq(1, 7, by = 0.1),
  Species = c("setosa", "versicolor", "virginica")
)
pred <- predict(mod, newdat, interval = "confidence")
dd <- cbind(newdat, pred)

xyplot(
  fit ~ Petal.Length,
  groups = Species, data = dd,
  prepanel = prepanel.ci, auto.key = list(lines = TRUE, points = FALSE),
  ylab = "Petal Width",
  xlab = "Petal Length",
  lower = dd$lwr, upper = dd$upr, type = "l",
  panel = function(...) {
    panel.ci(..., alpha = 0.15, grid = TRUE)
    panel.xyplot(...)
  }
)

Q-Q Diagram Confidence Intervals Panels

Description

Panel function to go along with lattice::qqmath() and lattice::panel.qqmathline(). Adds filled confidence bands to the Q-Q-plot.

Usage

panel.qqmathci(
  x,
  y = x,
  distribution = qnorm,
  probs = c(0.25, 0.75),
  qtype = 7,
  groups = NULL,
  ci = 0.95,
  alpha = 0.25,
  col = trellis.par.get("plot.line")$col,
  ...,
  col.line
)

Arguments

x

The original sample, possibly reduced to a fewer number of quantiles, as determined by the f.value argument to qqmath

y

an alias for x for backwards compatibility

distribution

quantile function for reference theoretical distribution.

probs

numeric vector of length two, representing probabilities. Corresponding quantile pairs define the line drawn.

qtype

the type of quantile computation used in quantile

groups

optional grouping variable. If non-null, a line will be drawn for each group.

ci

Confidence level

alpha

Alpha level for the color fill

col

Color fill for the confidence bands.

...

Arguments passed to lattice::panel.superpose() and lattice::panel.polygon()

col.line

Color fill for the confidence bands. Is used internally by lattice::panel.superpose() and should generally not be changed.

Details

The function tries to figure out the density function counterpart to that provided in the argument distribution by regular expressions.

Value

Augments a trellis plot panel, such as that created by lattice::qqmath(), with confidence levels.

Author(s)

Johan Larsson.

See Also

lattice::panel.qqmathline(), lattice::qqmath(), and lattice::panel.qqmath().

Examples

qqmath(~ height | voice.part, aspect = "xy", data = singer,
       prepanel = prepanel.qqmathline,
       panel = function(x, ...) {
         panel.qqmathci(x, ...)
         panel.qqmathline(x, ...)
         panel.qqmath(x, ...)
       })

Panel Function for Ternary Plots

Description

Panel Function for Ternary Plots

Usage

panel.ternaryplot(
  x,
  y,
  z,
  subscripts,
  response = NULL,
  density = FALSE,
  region = density || !is.null(response),
  contour = density || !is.null(response),
  labels = !is.null(response),
  points = TRUE,
  grid = TRUE,
  density_breaks = NULL,
  xlab,
  ylab,
  zlab,
  xlab.default,
  ylab.default,
  zlab.default,
  ...
)

Arguments

x

Numeric vector

y

Numeric vector

z

Numeric vector

subscripts

See lattice::panel.xyplot().

response

An optional response variable

density

Compute two-dimensional density estimates via MASS::kde2d().

region

Fill density or response estimates with a color gradient.

contour

Draw contour lines for density and response estimates.

labels

Label contour lines.

points

Draw points (via panel.ternaryplot.xyplot()).

grid

Draw a reference grid.

density_breaks

Breaks for the density plot if used (see panel.ternaryplot.density()).

xlab

X axis label (the left dimension)

ylab

Y axis label (the right dimension)

zlab

Z axis label (the top dimension)

xlab.default

Internal argument

ylab.default

Internal argument

zlab.default

Internal argument

...

Arguments passed down to subsequent panel functions.

Value

Plots a layer inside a panel of a lattice plot.

See Also

The building blocks of this function are available as the separate panel functions panel.ternaryplot.xyplot(), panel.ternaryplot.grid(), panel.ternaryplot.scales(), panel.ternaryplot.clip(), panel.ternaryplot.response(), and panel.ternaryplot.density() in case the user would like to get complete control of the customization.

Plot Region Clipping for Ternary Plots

Description

Plot Region Clipping for Ternary Plots

Usage

panel.ternaryplot.clip(
  xl = current.panel.limits()$x,
  yl = current.panel.limits()$y,
  border = "transparent",
  col = if (background$col == "transparent") "#FFFFFF" else background$col
)

Arguments

xl

X axis limits

yl

Y axis limits

border

Border color

col

Polygon fill

Value

Plots a layer inside a panel of a lattice plot.

Two-Dimensional Density Estimation for Ternary Plots

Description

Two-Dimensional Density Estimation for Ternary Plots

Usage

panel.ternaryplot.density(
  x,
  y,
  z,
  subscripts,
  n = 100,
  region = TRUE,
  contour = FALSE,
  labels = isTRUE(contour),
  density_breaks = NULL,
  ...
)

Arguments

x

Numeric vector

y

Numeric vector

z

Numeric vector

subscripts

See lattice::panel.xyplot().

n

Number of grid points in each direction. Can be scalar or a length-2 integer vector.

region

Fill density or response estimates with a color gradient.

contour

Draw contour lines for density and response estimates.

labels

Label contour lines.

density_breaks

Breaks for the density plot if used (see panel.ternaryplot.density()).

...

Arguments that will be passed on to lattice::panel.lines(), lattice::panel.polygon(), and lattice::panel.text().

Value

Plots a layer inside a panel of a lattice plot.

Reference Grid for Ternary Plot

Description

Reference Grid for Ternary Plot

Usage

panel.ternaryplot.grid(
  at = seq.int(0, 1, by = 0.2),
  alpha = reference.line$alpha,
  col = reference.line$col,
  lty = reference.line$lty,
  lwd = reference.line$lwd
)

Arguments

at

Where to draw the reference lines

alpha

Alpha

col

Color

lty

Line type

lwd

Line weight

Value

Plots a layer inside a panel of a lattice plot.

Response Panels for Ternary Plots

Description

Response Panels for Ternary Plots

Usage

panel.ternaryplot.response(
  x,
  y,
  z,
  subscripts,
  response,
  region = TRUE,
  contour = TRUE,
  labels = isTRUE(contour),
  fun = c("glm", "lm"),
  formula = response ~ poly(x, y),
  ...
)

Arguments

x

Numeric vector

y

Numeric vector

z

Numeric vector

subscripts

See lattice::panel.xyplot().

response

An optional response variable

region

Fill density or response estimates with a color gradient.

contour

Draw contour lines for density and response estimates.

labels

Label contour lines.

fun

Function to apply to the response variable.

formula

Formula for the function.

...

Arguments passed on to lattice::panel.lines(), lattice::panel.polygon(), lattice::panel.text().

Value

Plots a layer inside a panel of a lattice plot.

Axes and Labels for Ternary Plots

Description

Axes and Labels for Ternary Plots

Usage

panel.ternaryplot.scales(
  xlab,
  ylab,
  zlab,
  xlab.default,
  ylab.default,
  zlab.default,
  at = seq.int(0, 1, by = 0.2),
  ...
)

Arguments

xlab, ylab, zlab

Labels, have to be lists. Typically the user will not manipulate these, but instead control this via arguments to cloud directly.

xlab.default

for internal use

ylab.default

for internal use

zlab.default

for internal use

at

Where to draw tick marks.

...

Currently ignored.

Value

Plots a layer inside a panel of a lattice plot.

Ternary Plot Wrapper for lattice::xyplot

Description

This mainly exists to enable users to string together their own ternary plot functions.

Usage

panel.ternaryplot.xyplot(x, y, z, subscripts, ...)

Arguments

x

Numeric vector of values in the original space

y

Numeric vector of values in the original space

z

Numeric vector of values in the original space

subscripts

see lattice::xyplot().

...

Arguments that are passed on to lattice::panel.xyplot().

Value

Plots a layer inside a panel of a lattice plot.

Prepanel for ciplot

Description

Prepanel for ciplot

Usage

prepanel.ci(x, y, lower, upper, subscripts, groups = NULL, ...)

Arguments

x, y

x and y values, numeric or factor

lower

lower confidence limits

upper

upper confidence limits

groups, subscripts

See xyplot. Whenever appropriate, calculations are done separately for each group and then combined.

...

other arguments, usually ignored

Examples

mod <- lm(Petal.Width ~ Petal.Length * Species, data = iris)
newdat <- expand.grid(
  Petal.Length = seq(1, 7, by = 0.1),
  Species = c("setosa", "versicolor", "virginica")
)
pred <- predict(mod, newdat, interval = "confidence")
dd <- cbind(newdat, pred)

xyplot(
  fit ~ Petal.Length,
  groups = Species, data = dd,
  prepanel = prepanel.ci,
  ylab = "Petal Width",
  xlab = "Petal Length",
  lower = dd$lwr, upper = dd$upr, alpha = 0.3,
  panel = function(...) {
    panel.ci(..., grid = TRUE)
    panel.xyplot(type = "l", ...)
  }
)

Q-Q Plots for Zoo Objects

Description

Draw quantile-Quantile plots of a sample against a theoretical distribution, possibly conditioned on other variables.

Usage

## S3 method for class 'zoo'
qqmath(
  x,
  data = NULL,
  xlab = "Theoretical quantiles",
  ylab = "Sample quantiles",
  ref = TRUE,
  ci = TRUE,
  ...
)

Arguments

x

A zoo object

data

Ignored

xlab

X axis label

ylab

Y axis label

ref

Plot a reference line via lattice::panel.qqmathline().

ci

Plot confidence levels via panel.qqmathci().

...

Parameters to pass on to lattice::qqmath().

Value

Plots and returns a trellis object.

Author(s)

Original by Deepayan Sarkar.

See Also

lattice::qqmath(), zoo::zoo(), lattice::panel.qqmathline().

Examples

if (require(zoo))
  qqmath(zoo(lh))

Throw An Error if A Required Package Is Unavailable

Description

Throw An Error if A Required Package Is Unavailable

Usage

require_pkg(pkg)

Arguments

pkg

The required package

Value

An error if the package namespace is not available.

Uniform Rescaling

Description

Uniform Rescaling

Usage

rescale(
  x,
  new_min = 0,
  new_max = 1,
  old_min = min(x, na.rm = TRUE),
  old_max = max(x, na.rm = TRUE)
)

Arguments

x

A numeric vector to rescale

new_min

New min

new_max

New max

old_min

Old min

old_max

Old max

Value

A rescaled version of x.

Sequential palette helper.

Description

Divides the regions palette from lattice in half when it does not make sense to have a diverging palette.

Usage

seq_pal(n, bias = 1, space = "Lab", ...)

Arguments

n

Number of colors to generate

...

Stuff to pass on to grDevices::colorRampPalette()

Key Setup

Description

Try to setup a key while also dodging existing keys

Usage

setup_key(
  legend,
  key,
  default_key,
  fun,
  pos = c("right", "top", "bottom", "left")
)

Arguments

legend

a list of legends, usually the ⁠$legend⁠ slot of a trellis object.

key

A key specification, usually the user input.

default_key

The default key specifications that may be overridden by the user.

fun

The function to draw the key, such as lattice::draw.colorkey().

pos

Preferences for the position of the new key.

Value

The original legend object with the addition of the key defined by key, default_key, and fun.

Tactile Theme

Description

A custom theme for lattice that tries to make away with some of the (in this author's opinion) excessive margins that result from the default settings. It also provides a different color theme based partly on latticeExtra::custom.theme().

Usage

tactile.theme(fontsize = c(12, 8), color = TRUE, ...)

Arguments

fontsize

A vector of two numeric scalars for text and symbols respectively.

color

Colorized theme.

...

Additional named options.

Details

The theme currently modifies the default lattice theme so that

Value

A list of graphical parameters that for instance could be supplied inside a call to lattice::xyplot() or set via lattice::lattice.options().

Examples

xyplot(speed ~ dist, data = cars, par.settings = tactile.theme())
opars <- trellis.par.get()
trellis.par.set(tactile.theme())
show.settings()
trellis.par.set(opars)

Ternary Plot

Description

A ternary plot is a triangular diagram that displays proportions of three variables. It can be used to map three-dimensional data to a two-dimensional surface with the caveat that the data's original scales are lost (unless it was proportional data to begin with).#'

Usage

ternaryplot(x, data, ...)

## S3 method for class 'formula'
ternaryplot(
  x,
  data = NULL,
  response = NULL,
  groups = NULL,
  density = FALSE,
  region = density || !is.null(response),
  contour = density || !is.null(response),
  labels = !is.null(response),
  colorkey = region,
  xlab,
  ylab,
  zlab,
  xlim = c(-0.15, 1.15),
  ylim = c(-0.3, 1),
  panel = panel.ternaryplot,
  default.prepanel = lattice.getOption("prepanel.default.xyplot"),
  drop.unused.levels = lattice.getOption("drop.unused.levels"),
  subset = TRUE,
  ...
)

## S3 method for class 'data.frame'
ternaryplot(x, data = NULL, ...)

## S3 method for class 'matrix'
ternaryplot(x, data = NULL, ...)

Arguments

x

See Methods (by class).

data

A data frame in which the formula, groups, and conditioning variables are evaluated.

...

Arguments that are passed on to other methods, particularly panel.ternaryplot().

response

An optional response variable

groups

A variable or expression to be evaluated in data and used to distinguish groups by varying graphical parameters.

density

Compute two-dimensional density estimates via MASS::kde2d().

region

Fill density or response estimates with a color gradient.

contour

Draw contour lines for density and response estimates.

labels

Label contour lines.

colorkey

if TRUE automatically computes a colorkey for density or response estimates. Can also be a list (see lattice::levelplot() for details on this).

xlab

X axis label (the left dimension)

ylab

Y axis label (the right dimension)

zlab

Z axis label (the top dimension)

xlim

X limits for the plot region.

ylim

Y limits for the plot region.

panel

The panel function.

default.prepanel

The default prepanel function.

drop.unused.levels

Drop unused conditioning or groups levels.

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.

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.

Methods (by class)

Examples

ternaryplot(Fertility ~ Agriculture * Catholic, data = swiss)
ternaryplot(Catholic ~ Examination * Education, response = Infant.Mortality,
            data = swiss, contour = FALSE)

ternaryplot(Or ~ An * Ab | Feldspar, data = feldspar)

ternaryplot(Or ~ An * Ab, groups = Feldspar, data = feldspar, density = TRUE)

Update a List with User Input

Description

Wrapper for utils::modifyList().

Usage

updateList(x, val)

Arguments

x

A list to be updated.

val

Stuff to update x with.

Value

Returns an updated list.

See Also

utils::modifyList()

Diagnostic Plots for ARIMA Models

Description

Diagnostic plots modelled after stats::tsdiag() with some modifications and corrections of p-values in the Box–Ljung test.

Usage

## S3 method for class 'Arima'
xyplot(
  x,
  data = NULL,
  which = 1:4,
  lag.max = NULL,
  gof.lag = NULL,
  qq.aspect = "iso",
  na.action = na.pass,
  main = NULL,
  layout = NULL,
  ...
)

Arguments

x

A fitted time-series model of class Arima.

data

Ignored

which

A sequence of integers between 1 and 4, identifying the plots to be shown.

lag.max

Number of lags to compute ACF for.

gof.lag

The maximum number of lags for the Ljung–Box test.

qq.aspect

Aspect of Q-Q plot (see lattice::qqmath()).

na.action

Treatment of NAs.

main

Optional titles for the plots. Can also be TRUE, in which case a default list of titles will be added.

layout

Either a numeric vector with (columns, rows) to use in the call to gridExtra::grid.arrange(), or a layout matrix which will then be passed as the layout_matrix in grid.arrange().

...

Parameters to pass to xyplot().

Value

Plots a lattice plot and returns a trellis object.

See Also

stats::tsdiag(), stats::arima(), lattice::xyplot(), gridExtra::grid.arrange(), stats::Box.test().

Examples

fit <- arima(lh, order = c(1, 1, 0))
xyplot(fit, layout = c(2, 2))
xyplot(fit, which = c(1:2, 4), layout = rbind(c(1, 1), c(2, 3)))

Plot Autocovariance and Autocorrelation Functions

Description

This is a version of stats::plot.acf().

Usage

## S3 method for class 'acf'
xyplot(
  x,
  data = NULL,
  ci = 0.95,
  ci_type = c("white", "ma"),
  ci_col = trellis.par.get("add.line")$col,
  ci_lty = 2,
  ...
)

Arguments

x

An 'acf' object.

data

Ignored

ci

Confidence level.

ci_type

Type of confidence level.

ci_col

Line color for the confidence levels.

ci_lty

Line type for the confidence levels.

...

Arguments passed on to lattice::xyplot().

Value

Returns and plots a trellis object.

Author(s)

Original by Brian Ripley.

See Also

lattice::xyplot(), stats::plot.acf(), stats::acf().

Examples

z <- ts(matrix(rnorm(400), 100, 4), start = c(1961, 1), frequency = 12)
xyplot(acf(z))

Plot Forecasts with Trellis Graphics

Description

Plot forecasts from forecast::forecast(). It is built mostly to resemble the forecast::autoplot.forecast() and forecast::plot.forecast() functions, but in addition tries to plot the predictions on the original scale.

Usage

## S3 method for class 'forecast'
xyplot(
  x,
  data = NULL,
  ci = TRUE,
  ci_levels = x$level,
  ci_key = ci,
  ci_pal = hcl(0, 0, 45:100),
  ci_alpha = trellis.par.get("regions")$alpha,
  ...
)

Arguments

x

An object of class forecast.

data

Data of observations left out of the model fit, usually "future" observations.

ci

Plot confidence intervals for the predictions.

ci_levels

The prediction levels to plot as a subset of those forecasted in x.

ci_key

Set to TRUE to draw a key automatically or provide a list (if length(ci_levels) > 5 should work with lattice::draw.colorkey() and otherwise with lattice::draw.key())

ci_pal

Color palette for the confidence bands.

ci_alpha

Fill alpha for the confidence interval.

...

Arguments passed on to lattice::panel.xyplot().

Details

This function requires the zoo package.

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.

See Also

lattice::panel.xyplot(), forecast::forecast(), lattice::xyplot.ts().

Examples

if (require(forecast)) {
  train <- window(USAccDeaths, c(1973, 1), c(1977, 12))
  test <- window(USAccDeaths, c(1978, 1), c(1978, 12))
  fit <- arima(train, order = c(0, 1, 1),
               seasonal = list(order = c(0, 1, 1)))
  fcast1 <- forecast(fit, 12)
  xyplot(fcast1, test, grid = TRUE, auto.key = list(corner = c(0, 0.99)),
         ci_key = list(title = "PI Level"))

  # A fan plot
  fcast2 <- forecast(fit, 12, level = seq(0, 95, 10))
  xyplot(fcast2, test, ci_pal = heat.colors(100))
}

Lattice plot diagnostics for lm objects

Description

Lattice plot diagnostics for lm objects, mostly mimicking the behavior of stats::plot.lm() but based on lattice::xyplot() instead.

Usage

## S3 method for class 'lm'
xyplot(
  x,
  data = NULL,
  which = c(1:3, 5),
  main = FALSE,
  id.n = 3,
  labels.id = names(residuals(x)),
  cex.id = 0.75,
  cook.levels = c(0.5, 1),
  label.pos = c(4, 2),
  layout = NULL,
  ...
)

Arguments

x

lm object, typically result of lm or glm.

data

Only provided for method consistency and is ignored.

which

if a subset of the plots is required, specify a subset of the numbers 1:6

main

if TRUE plots default titles. Can also be a list or character vector of length 6.

id.n

number of points to be labelled in each plot, starting with the most extreme.

labels.id

vector of labels, from which the labels for extreme points will be chosen. NULL uses observation numbers.

cex.id

magnification of point labels.

cook.levels

levels of Cook's distance at which to draw contours.

label.pos

positioning of labels, for the left half and right half of the graph respectively, for plots 1-3, 5, 6.

layout

a numeric vector with ⁠[columns, rows]⁠ to use in the call to gridExtra::grid.arrange(), or a layout matrix which will then be passed as the layout_matrix in grid.arrange().

...

arguments to be passed to lattice::xyplot().

Value

A list of trellis objects or a single trellis object.

Author(s)

Original by John Maindonald and Martin Maechler. Adaptation to lattice by Johan Larsson.

See Also

stats::lm(), stats::plot.lm(), lattice::xyplot()

Examples

fit <- lm(Sepal.Length ~ Sepal.Width, data = iris)
xyplot(fit)
xyplot(fit, which = 5)

Convert a formula from z ~ x * y to y ~ x

Description

Convert a formula from z ~ x * y to y ~ x

Usage

xyz_to_xy(form)

Arguments

form

Three-dimensional lattice formula.

Value

A two-dimensional lattice formula.

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