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plot. Colours maybe used to show the value of one mask covariate.# S3 method for 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, …)# S3 method for Dsurface
plot(x, covariate, group = NULL, plottype =
"shaded", scale = 1, ...)
# S3 method for 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 of spotHeight) Dsurface)If 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.
The argument 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.
For plot.Dsurface the default value of `covariate' is `D' unless the Dsurface has a `parameter' attribute of `noneuc',
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")
## Not run: ------------------------------------
#
# ## 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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