Plot Aoristic Analysis

Plot Aoristic Analysis

Usage

# S4 method for class 'AoristicSum,missing'
plot(
  x,
  calendar = getOption("kairos.calendar"),
  type = c("bar"),
  flip = FALSE,
  ncol = NULL,
  main = NULL,
  sub = NULL,
  ann = graphics::par("ann"),
  axes = TRUE,
  frame.plot = axes,
  panel.first = NULL,
  panel.last = NULL,
  ...
)

# S4 method for class 'AoristicSum'
image(x, calendar = getOption("kairos.calendar"), ...)

# S4 method for class 'RateOfChange,missing'
plot(
  x,
  calendar = getOption("kairos.calendar"),
  level = 0.95,
  flip = FALSE,
  ncol = NULL,
  main = NULL,
  sub = NULL,
  ann = graphics::par("ann"),
  axes = TRUE,
  frame.plot = axes,
  panel.first = NULL,
  panel.last = NULL,
  ...
)

Arguments

x

An AoristicSum object.

calendar

An aion::TimeScale object specifying the target calendar (see calendar()).

type

A character string specifying whether bar or density should be plotted? It must be one of "bar" or "density". Any unambiguous substring can be given.

flip

A logical scalar: should the y-axis (ticks and numbering) be flipped from side 2 (left) to 4 (right) from series to series when facet is "multiple"?

ncol

An integer specifying the number of columns to use when facet is "multiple". Defaults to 1 for up to 4 series, otherwise to 2.

main

A character string giving a main title for the plot.

sub

A character string giving a subtitle for the plot.

ann

A logical scalar: should the default annotation (title and x and y axis labels) appear on the plot?

axes

A logical scalar: should axes be drawn on the plot?

frame.plot

A logical scalar: should a box be drawn around the plot?

panel.first

An expression to be evaluated after the plot axes are set up but before any plotting takes place. This can be useful for drawing background grids.

panel.last

An expression to be evaluated after plotting has taken place but before the axes, title and box are added.

...

Further parameters to be passed to panel (e.g. graphical parameters).

level

A length-one numeric vector giving the confidence level.

Value

plot() is called it for its side-effects: it results in a graphic being displayed (invisibly returns x).

See also

aoristic(), roc()

Other plotting methods: plot_event, plot_fit, plot_mcd, plot_time()

Author

N. Frerebeau

Examples

## Data from Husi 2022
data("loire", package = "folio")

## Get time range
loire_range <- loire[, c("lower", "upper")]

## Calculate aoristic sum (normal)
aorist_raw <- aoristic(loire_range, step = 50, weight = FALSE)
plot(aorist_raw, col = "grey")


## Calculate aoristic sum (weights)
aorist_weighted <- aoristic(loire_range, step = 50, weight = TRUE)
plot(aorist_weighted, col = "grey")


## Calculate aoristic sum (weights) by group
aorist_groups <- aoristic(loire_range, step = 50, weight = TRUE,
                          groups = loire$area)
plot(aorist_groups, flip = TRUE, col = "grey")

image(aorist_groups)


## Rate of change
roc_weighted <- roc(aorist_weighted, n = 30)
plot(roc_weighted)


## Rate of change by group
roc_groups <- roc(aorist_groups, n = 30)
plot(roc_groups, flip = TRUE)