Heatmap of data on a calendar — calendar

The package's single data-on-calendar renderer (the analogue of geoscales::geoscale_plot()): callers prepare a data.frame keyed by timeslice and hand it over. With no data, the calendar's own share is drawn — a quick structural view. Layout follows the calendar's hierarchy: finest timeframe on y, next-finest on x, anything coarser as facets (overridable via x_tf/y_tf/facet_tf).

Usage

calendar_plot(
  x,
  data = NULL,
  values = NULL,
  key = "timeslice",
  x_tf = NULL,
  y_tf = NULL,
  facet_tf = NULL,
  fun = mean,
  palette = NULL,
  ...
)

Arguments

x: A Calendar.
data: Optional data.frame with a key column of timeslice IDs plus one numeric value column (pick with values= if there are several). Default NULL plots leaves$share.
values: Name of the value column to plot. Default: the first numeric column other than key.
key: Name of the timeslice key column in data. Default "timeslice".
x_tf, y_tf, facet_tf: Timeframe names overriding the automatic layout.
fun: Aggregator applied when the chosen layout drops timeframes (e.g. plotting an hourly calendar by MONTH x HOUR averages over days). Default mean.
palette: NULL (default) keeps ggplot2's default continuous gradient; a viridis option letter/name opts in.
...: Ignored (future extension).

Value

A ggplot object.

Examples

if (requireNamespace("ggplot2", quietly = TRUE)) {
  calendar_plot(calendar("m12_h24"))   # structure: share heatmap

  cal <- calendar("m12")
  x <- data.frame(timeslice = sprintf("m%02d", 1:12), load = 1:12)
  calendar_plot(cal, x)
}