Create a timeline of selected event metrics as 'lollipops'.

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: The name of a column from the event data.frame in the output of detect_event. Suggested choices are, but not limited to, of event_no, date_start or date_peak. Default is date_peak.
metric: The name of a column from the event data.frame in the output of detect_event.Suggested choices are, but not limited to, 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 column 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 does not need 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)