
image
plot. Colours maybe used to show the value of one mask covariate.## S3 method for class 'mask':
plot(x, border = 20, add = FALSE, covariate = NULL, axes = FALSE,
dots = TRUE, col = "grey", breaks = 10, meshcol = NA, ppoly = TRUE,
polycol = "red", legend = TRUE, \dots)
## S3 method for class 'Dsurface':
plot(x, covariate = "D", group = NULL, plottype =
"shaded", scale = 1, ...)
## S3 method for class 'Rsurface':
plot(x, covariate = "Resource", plottype =
"shaded", scale = 1, ...)
spotHeight (object, prefix = NULL, dec = 2, point = FALSE, text = TRUE,
sep = ", ", session = 1, scale = 1, ...)
cut
ppoly
= TRUE)eqscplot
(in the case
of plot.mask
), plot.mask
(in the case of
plot.Dsurface
and plot.Rsurface
), and points
or
text
(in the case Dsurface
)covariate
is specified and plottype = shaded
then
plot.mask
invisibly returns a character vector of the intervals
defined by `breaks' (useful for plotting a legend).
If `plottype = persp' then plot.mask
invisibly returns a the
perspective matrix that may be used to add to the plot with
trans3d
.
spotHeight
invisibly returns a dataframe of the extracted
values and their coordinates.dots
of plot.mask
selects between two
distinct types of plot (dots and shaded (coloured) pixels).
plot.Dsurface
and plot.Rsurface
offer contour and
perspective plots in addition to the options in plot.mask
. It may
take some experimentation to get what you want - see
contour
and persp
.
If using a covariate or Dsurface or Rsurface to colour dots or pixels, the
col
argument should be a colour vector of length equal to the
number of levels (the default palette from 2.9.0 is terrain.colors
, and this
palette will also be used whenever there are too few levels in the
palette provided; see Notes for more on palettes). Border lines around
pixels are drawn in `meshcol'. Set this to NA to eliminate pixel
borders.
If a covariate
is specified in a call to plot.Dsurface
then
that covariate will be plotted instead of density. This is a handy way
to contour a covariate (contouring is not available in plot.mask
).
If `breaks' is an integer then the range of the covariate is divided
into this number of equal intervals. Alternatively, `breaks' may be a
vector of break points (length one more than the number of
intervals). This gives more control and often `prettier'
spotHeight
may be used to interrogate a plot produced with
plot.Dsurface
or plot.Rsurface
, or by plot.mask
if
the mask has covariates. prefix
defaults to `density.' for
Dsurface objects and to `' (all covariates) for mask objects. The
predicted density or covariate at the nearest point is returned when the
user clicks on the plot. Multiple values may be displayed (e.g.,
prefix = c("lcl","ucl")
if Dsurface includes confidence
limits). Click outside the mask or hit the Esc key to
end. spotHeight
deals with one session at a time.
Legend plotting is enabled only when a covariate is specified. It uses
legend
when dots = TRUE
and
strip.legend
otherwise.colours
,
mask
,
Dsurface
,
rectangularMask
,
contour
persp
strip.legend
# simple
temptrap <- make.grid()
tempmask <- make.mask(temptrap)
plot (tempmask)
## restrict to points over an arbitrary detection threshold,
## add covariate, plot image and overlay traps
tempmask <- subset(tempmask, pdot(tempmask, temptrap,
noccasions = 5)>0.001)
covariates (tempmask) <- data.frame(circle =
exp(-(tempmask$x^2 + tempmask$y^2)/10000) )
plot (tempmask, covariate = "circle", dots = FALSE, axes = TRUE,
add = TRUE, breaks = 8, col = terrain.colors(8), mesh = NA)
plot (temptrap, add = TRUE)
## add a legend
par(cex = 0.9)
covrange <- range(covariates(tempmask)$circle)
step <- diff(covrange)/8
colourlev <- terrain.colors(9)
zlev <- format(round(seq(covrange[1],covrange[2],step),2))
legend (x = "topright", fill = colourlev, legend = zlev,
y.intersp = 0.8, title = "Covariate")
title("Colour mask points with p.(X) > 0.001")
mtext(side=3,line=-1, "g0 = 0.2, sigma = 20, nocc = 5")
## Waitarere possum density surface extrapolated across region
regionmask <- make.mask(traps(possumCH), buffer = 1000, spacing = 10,
poly = possumremovalarea)
dts <- distancetotrap(regionmask, possumarea)
covariates(regionmask) <- data.frame(d.to.shore = dts)
shorePossums <- predictDsurface(possum.model.Ds, regionmask)
## plot as coloured pixels with white lines
colourlev <- terrain.colors(7)
plot(shorePossums, breaks = seq(0,3.5,0.5), plottype = "shaded",
poly = FALSE, col = colourlev, mesh = NA)
plot(traps(possumCH), add = TRUE, detpar = list(col = "black"))
polygon(possumremovalarea)
## check some point densities
spotHeight(shorePossums, dec = 1, col = "black")
## add a legend
zlev <- format(seq(0,3,0.5), digits = 1)
legend (x = "topright", fill = colourlev, legend =
paste(zlev,"--"), y.intersp = 1, title = "Density / ha")
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