contour | R Documentation |
Display contours of the net probability of detection p.(X), or the
area within a specified distance of detectors. bufferContour
adds a conventional ‘boundary strip’ to a detector (trap) array, where
buffer
equals the strip width.
pdotContour(traps, border = NULL, nx = 64, detectfn = 0,
detectpar = list(g0 = 0.2, sigma = 25, z = 1), noccasions = NULL,
binomN = NULL, levels = seq(0.1, 0.9, 0.1), poly =
NULL, poly.habitat = TRUE, plt = TRUE, add = FALSE, fill = NULL, ...)
bufferContour(traps, buffer, nx = 64, convex = FALSE, ntheta = 100,
plt = TRUE, add = FALSE, poly = NULL, poly.habitat = TRUE,
fill = NULL, ...)
traps |
|
border |
width of blank margin around the outermost detectors |
nx |
dimension of interpolation grid in x-direction |
detectfn |
integer code or character string for shape of detection function 0 = halfnormal etc. – see detectfn |
detectpar |
list of values for named parameters of detection function |
noccasions |
number of sampling occasions |
binomN |
integer code for discrete distribution (see
|
levels |
vector of levels for p.(X) |
poly |
matrix of two columns, the x and y coordinates of a bounding polygon (optional) |
poly.habitat |
logical as in |
plt |
logical to plot contours |
add |
logical to add contour(s) to an existing plot |
fill |
vector of colours to fill contours (optional) |
... |
other arguments to pass to |
buffer |
vector of buffer widths |
convex |
logical, if TRUE the plotted contour(s) will be convex |
ntheta |
integer value for smoothness of convex contours |
pdotContour
constructs a rectangular mask and applies pdot
to
compute the p.(X) at each mask point.
If convex = FALSE
, bufferContour
constructs a mask and
contours the points on the basis of distance to the nearest detector at the
levels given in buffer
.
If convex = TRUE
, bufferContour
constructs a set of
potential vertices by adding points on a circle of radius =
buffer
to each detector location; the desired contour is the
convex hull of these points (this algorithm derives from Efford, 2012).
If traps
has a usage attribute then noccasions
is
set accordingly; otherwise it must be provided.
If traps
is for multiple sessions then detectpar should be a list
of the same length, one component per session, and noccasions may be a
numeric vector of the same length.
Increase nx
for smoother lines, at the expense of speed.
Coordinates of the plotted contours are returned as a list with one
component per polygon. The list is returned invisibly if plt =
TRUE
.
For multi-session input (traps
) the value is a list of such
lists, one per session.
The precision (smoothness) of the fitted line in bufferContour
is controlled by ntheta
rather than nx
when convex
= TRUE
.
To suppress contour labels, include the argument drawlabels =
FALSE
(this will be passed via ... to contour
). Other useful
arguments of contour
are col
(colour of contour lines)
and lwd
(line width).
You may wish to consider function st_buffer in package sf as an
alternative to bufferContour
.
bufferContour
failed with multi-session traps
before
secr 2.8.0.
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/.
pdot
, make.mask
possumtraps <- traps(possumCH)
## convex and concave buffers
plot(possumtraps, border = 270)
bufferContour(possumtraps, buffer = 100, add = TRUE, col = "blue")
bufferContour(possumtraps, buffer = 100, convex = TRUE, add = TRUE)
## areas
buff.concave <- bufferContour(possumtraps, buffer = 100,
plt = FALSE)
buff.convex <- bufferContour(possumtraps, buffer = 100,
plt = FALSE, convex = TRUE)
sum (sapply(buff.concave, polyarea)) ## sum over parts
sapply(buff.convex, polyarea)
## effect of nx on area
buff.concave2 <- bufferContour(possumtraps, buffer = 100,
nx = 128, plt = FALSE)
sum (sapply(buff.concave2, polyarea))
## Not run:
plot(possumtraps, border = 270)
pdotContour(possumtraps, detectfn = 0, nx = 128, detectpar =
detectpar(possum.model.0), levels = c(0.1, 0.01, 0.001),
noccasions = 5, add = TRUE)
## clipping to polygon
olddir <- setwd(system.file("extdata", package = "secr"))
possumtraps <- traps(possumCH)
possumarea <- read.table("possumarea.txt", header = TRUE)
par(xpd = TRUE, mar = c(1,6,6,6))
plot(possumtraps, border = 400, gridlines = FALSE)
pdotContour(possumtraps, detectfn = 0, nx = 256, detectpar =
detectpar(possum.model.0), levels = c(0.1, 0.01, 0.001),
noccasions = 5, add = TRUE, poly = possumarea, col = "blue")
lines(possumarea)
setwd(olddir)
par(xpd = FALSE, mar = c(5,4,4,2) + 0.1) ## reset to default
## End(Not run)
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