plot.bcpa: Plotting method for BCPA output

In bcpa: Behavioral Change Point Analysis of Animal Movement

Plotting method for BCPA output

Description

Plotting method for the output of a BCPA analysis with vertical break points, superimposed estimates of the partitioned mean and variance estimates and color-coded autocorrelation estimates.

Usage

## S3 method for class 'bcpa'
plot(
  x,
  type = c("smooth", "flat")[1],
  threshold = 3,
  clusterwidth = 1,
  col.cp = rgb(0.5, 0, 0.5, 0.5),
  pt.cex = 0.5,
  legend = TRUE,
  rho.where = "topleft",
  mu.where = "nowhere",
  col.sd = "red",
  col.mean = "black",
  ...
)

Arguments

x	a windowsweep object, i.e. the output of the WindowSweep function.
type	whether to plot smooth or flat bcpa output
threshold	for smooth BCPA, this is the minimum number of windows that must have identified a given changepoint to be illustrated.
clusterwidth	for flat BCPA, this is the temporal range within which change points are considered to be within the same cluster.
col.cp, col.mean, col.sd	color of the vertical change points, mean estimate, and prediction interval (mu +- sigma), respectively.
pt.cex	expansion coefficient for point sizes.
legend	logical - whether to draw a legend or not.
rho.where	where to place the legend for the time-scale / auto-correlation. Can be one of "nowhere", "top", "bottom", "left", "right", "topleft", "topright", "bottomright", "bottomleft"
mu.where	where (and whether) to place the legend box for the mean - same options as for rho.where
...	other arguments to pass to the plot base function.

Author(s)

Eliezer Gurarie

See Also

Plots output of the WindowSweep function.

Examples

if(!exists("Simp.ws"))
{
 data(Simp)
 Simp.ws <- WindowSweep(GetVT(Simp), "V*cos(Theta)", windowsize = 50, 
 windowstep = 1, progress=TRUE)
}

plot(Simp.ws)
# this actually provides basically the exact original changepoints
plot(Simp.ws, threshold=7)
# here's a flat analysis
plot(Simp.ws, type="flat", clusterwidth=3, legend=FALSE)

bcpa documentation built on May 30, 2022, 5:07 p.m.