Visualise a timeline of several possible event metrics as 'lollipop' graphs.

lolli_plot(
  data,
  xaxis = "date_peak",
  metric = "intensity_max",
  event_count = 3
)

Arguments

data

Output from the detect_event function.

xaxis

One of event_no, date_start or date_peak. Default is date_start.

metric

One of intensity_mean, intensity_max, intensity_cumulative and duration. Default is intensity_max.

event_count

The number of top events to highlight, as determined by the value given to metric. Default is 3.

Value

The function will return a graph of the intensity of the selected metric along the y-axis and the chosen xaxis value. The number of top events as per event_count will be highlighted in a brighter colour. This function differs in use from geom_lolli in that it creates a stand-alone figure. The benefit of this being that one must not have any prior knowledge of ggplot2 to create the figure.

Author

Albertus J. Smit and Robert W. Schlegel

Examples

ts <- ts2clm(sst_WA, climatologyPeriod = c("1983-01-01", "2012-12-31")) res <- detect_event(ts) library(ggplot2) # The default output lolli_plot(res)