| plot.capthist {secr} | R Documentation |
Display a plot of detection (capture) histories or telemetry data over a map of the detectors.
## S3 method for class 'capthist'
plot(x, rad = 5, hidetraps = FALSE, tracks = FALSE,
title = TRUE, subtitle = TRUE, add = FALSE, varycol = TRUE,
icolours = NULL, randcol = FALSE, lab1cap = FALSE, laboffset = 4, ncap = FALSE,
splitocc = NULL, col2 = "green", type = c("petal", "n.per.detector", "n.per.cluster",
"sightings", "centres", "telemetry", "nontarget"),
cappar = list(cex = 1.3, pch = 16, col = "blue"),
trkpar = list(col = "blue", lwd = 1),
labpar = list(cex = 0.7, col = "black"), ...)
plotMCP(x, add = FALSE, col = "black", fill = NA, lab1cap = FALSE, laboffset = 4,
ncap = FALSE, ...)
x |
an object of class |
rad |
radial displacement of dot indicating each capture event from the detector location (used to separate overlapping points) |
hidetraps |
logical indicating whether trap locations should be displayed |
tracks |
logical indicating whether consecutive locations of individual animals should be joined by a line |
title |
logical or character string for title |
subtitle |
logical or character string for subtitle |
add |
logical for whether to add to existing plot |
varycol |
logical for whether to distinguish individuals by colour |
icolours |
vector of individual colours (when |
randcol |
logical to use random colours ( |
lab1cap |
logical for whether to label the first capture of each animal |
laboffset |
distance by which to offset labels from points |
ncap |
logical to display the number of detections per trap per occasion |
splitocc |
optional occasion from which second colour is to be used |
col2 |
second colour (used with |
type |
character string ("petal", "n.per.detector" or "n.per.cluster") |
cappar |
list of named graphical parameters for detections (passed to |
trkpar |
list of named graphical parameters for tracks (passed to |
labpar |
list of named graphical parameters for labels (passed to |
... |
arguments to be passed to |
col |
vector of line colour numbers or names (plotMCP only) |
fill |
vector of fill colour numbers or names (plotMCP only) |
By default, a ‘petal’ plot is generated in the style of Density (Efford 2012)
using eqscplot from the MASS library.
If type =
"n.per.detector" or type = "n.per.cluster" the result is a
colour-coded plot of the number of individuals at each unit, pooled over
occasions.
If type = "sightings" the sightings of unmarked animals are
displayed on a petal-like plot (requires mark-resight data) (see also sightingPlot).
If type = "centres" then a single point is plotted for each animal, jittered on each axis by a random amount (limits +/- rad/2).
If type = "telemetry" and the ‘telemetryxy’ attribute is not NULL then the telemetry locations are plotted.
If type = "nontarget" and the ‘nontarget’ attribute is not NULL then the nontarget captures or interference events are plotted.
If title = FALSE no title is displayed; if title = TRUE,
the session identifer is used for the title.
If subtitle = FALSE no subtitle is displayed; if subtitle
= TRUE, the subtitle gives the numbers of occasions, detections and
individuals.
If x is a multi-session capthist object then a separate plot is
produced for each session. Use par(mfrow = c(nr, nc)) to allow a
grid of plots to be displayed simultaneously (nr rows x nc columns).
These arguments are used only for petal plots: rad,
tracks, varycol, randcol, lab1cap,
laboffset, ncap, splitocc, col2,
trkpar, and labpar. Call occasionKey
to add a key to the petals.
If icolours = NULL and varycol = TRUE then a vector of
colours is generated automatically as topo.colors((nrow(x)+1) * 1.5).
If there are too few values in icolours for the number of
individuals then colours will be re-used.
plotMCP plots minimum convex polygons of individual location
data over a base plot of detector locations. Usually the data are
telemetry locations in the xylist attribute of the capthist
object; if this is not present and x is a polygon search
capthist then the individual xy data are plotted.
For type = "petal", the number of detections in x.
For type = "sightings", the number of sightings of unmarked animals in x.
For type = "n.per.detector" or type = "n.per.cluster", a
dataframe with data for a legend (see Examples).
plotMCP invisibly returns a list in which each component is a
2-column (x,y) dataframe of boundary coordinates for one individual.
Efford, M. G. (2012) DENSITY 5.0: software for spatially explicit capture–recapture. Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand. https://www.otago.ac.nz/density/.
capthist,
occasionKey,
sightingPlot
demotrap <- make.grid()
tempcapt <- sim.capthist(demotrap,
popn = list(D = 5, buffer = 50),
detectpar = list(g0 = 0.15, sigma = 30))
plot(tempcapt, border = 10, rad = 3, tracks = TRUE,
lab1cap = TRUE, laboffset = 2.5)
## type = n.per.cluster
## generate some captures
testregion <- data.frame(x = c(0,2000,2000,0),
y = c(0,0,2000,2000))
popn <- sim.popn (D = 10, core = testregion, buffer = 0,
model2D = "hills", details = list(hills = c(-2,3)))
t1 <- make.grid(nx = 1, ny = 1)
t1.100 <- make.systematic (cluster = t1, spacing = 100,
region = testregion)
capt <- sim.capthist(t1.100, popn = popn, noccasions = 1)
## now plot captures ...
temp <- plot(capt, title = "Individuals per cluster",
type = "n.per.cluster", hidetraps = FALSE,
gridlines = FALSE, cappar = list(cex = 1.5))
if (interactive()) {
## add legend; click on map to place top left corner
legend (locator(1), pch = 21, pt.bg = temp$colour,
pt.cex = 1.3, legend = temp$legend, cex = 0.8)
}
## Not run:
## try varying individual colours - requires RColorBrewer
library(RColorBrewer)
plot(infraCH[[2]], icolours = brewer.pal(12, "Set3"), tracks = TRUE,
bg = "black", cappar = list(cex = 2), border = 10, rad = 2,
gridlines = FALSE)
## generate telemetry data
te <- make.telemetry()
tr <- make.grid(detector = "proximity")
totalpop <- sim.popn(tr, D = 20, buffer = 100)
tepop <- subset(totalpop, runif(nrow(totalpop)) < 0.05)
teCH <- sim.capthist(te, popn = tepop, renumber=FALSE, detectfn = "HHN",
detectpar = list(lambda0 = 3, sigma = 25))
plot(teCH, type = 'telemetry', tracks = TRUE)
## simple "centres" example
## polygon data require 'hazard' detection function 14:19
CH <- sim.capthist(make.poly(), nocc = 20, detectfn = 'HHN',
detectpar = list(lambda0 = 1, sigma = 10))
plot(CH, cappar = list(col = 'orange'), varycol = FALSE, border = 10)
plot(CH, type = 'centres', add = TRUE, rad = 0)
## End(Not run)