Plot the per-date delay profiles

One translucent curve per date (see by) giving that date's share of reports at each delay, coloured by its mean delay. A batch is a lone right-shifted (long-delay) curve.

Usage

plot_delay_profiles(
  x,
  by = c("report", "event"),
  max_delay = NULL,
  plotly = FALSE,
  axis = c("report", "validation"),
  palette = .tbl_now_palette()
)

Arguments

x

A tbl_now() object.

by

One line per "report" date (default) or per "event" date.

max_delay

Largest delay to draw. NULL (default) caps at the delay covering 99% of reported mass.

plotly

If TRUE, return an interactive plotly widget instead of a static plot. Default FALSE.

axis

Which time axis the delay is measured to: "report" (default) or "validation". Both are measured from the event, so the two are directly comparable – run each in turn and the gap between them is the time the laboratory adds. (This is not the same quantity as the .validation_delay column, which is the laboratory's own turnaround, measured from the report.) Needs a validation process (see add_validation_date()); cases still "pending" are left out.

palette

A named colour palette. Defaults to the package palette.

Value

A ggplot2 object (or a plotly widget when plotly = TRUE).

See also

plot_delay_distribution() for the pooled delay distribution rather than one curve per date; plot_delay_drift() for whether those curves move over time; diagnose_batch_shape() for the test behind the eyeball; diagnostic_plot() for the whole gallery.

Examples

data(denguedat)
dn <- tbl_now(denguedat, onset_week, report_week, verbose = FALSE)
plot_delay_profiles(dn)