locations: Plotting estimated locations
In b-steve/admbsecr: SECR models with supplementary location information

Plots estimated densities of animal locations, which are latent variables in SECR models.

locations(fit, id, infotypes = NULL, combine = FALSE, xlim = range(mask[,
  1]), ylim = range(mask[, 2]), mask = get.mask(fit), levels = NULL,
  nlevels = 10, density = FALSE, cols = list(combined = "black", capt =
  "purple", ss = "orange", bearing = "green", dist = "brown", toa = "blue"),
  ltys = list(combined = "solid", capt = "solid", ss = "solid", bearing =
  "solid", dist = "solid", toa = "solid"), trap.col = "red",
  circle.traps = TRUE, show.labels = TRUE, plot.contours = TRUE,
  plot.estlocs = FALSE, keep.estlocs = FALSE, plot.arrows = "bearing"
  %in% fit$infotypes, plot.circles = "dist" %in% fit$infotypes,
  arrow.length = NULL, show.legend = FALSE, show.axes = TRUE,
  add = FALSE)

`fit`	A fitted model from admbsecr.
`id`	A numeric vector with row numbers from `fit$args$capt`, indicating which individuals' locations are to be plotted.
`infotypes`	A character vector indicating the type(s) of information to be used when plotting the estimated density of location. Elements can be a subset of `"capt"`, `"bearing"`, `"dist"`, `"ss"`, `"toa"`, `"combined"`, and `"all"`, where `"capt"` shows estimated location only using detection locations, `"combined"` combines all information types together, and `"all"` plots all possible contour types. When signal strength information is used in the model fit, `"capt"` and `"ss"` are equivalent as the signal strength information is built into the detection function. By default, only the most informative contour is plotted, i.e., `"capt"` if the model was fitted with no additional information, and `"combined"` otherwise.
`combine`	Logical, if `TRUE` then the information types specified in `infotypes` are combined into a single contour. If `FALSE` then separate contours are plotted for each information type.
`xlim`	A numeric vector of length 2, giving the x coordinate range.
`ylim`	A numeric vector of length 2, giving the y coordinate range.
`mask`	A matrix with two columns. Each row provides Cartesian coordinates for the location of a mask point. The function create.mask will return a suitable object. The mask used to fit the model `fit` will be used by default; this argument is usually used when estimated location contours need to be plotted to a higher resolution than this.
`levels`	A numeric vector giving the values to be associated with the plotted contours.
`nlevels`	The number of contour levels desired. Ignored if `levels` is provided.
`density`	Logical, if `TRUE`, the labels on contours (and the levels specified by `levels`) refer to the density of the estimated distribution of the individual's location. If `FALSE`, the labels on contours (and the levels specified by `levels`) refer to the probability of the individual being located within the associated contour under the estimated distribution of the individual's location.
`cols`	A list with named components corresponding to each contour type (i.e., a subset of `"capt"`, `"bearing"`, `"dist"`, `"toa"`, and `"combined"`). Each component provides the colour of the associated contour type (e.g., using a character string such as `"red"`, or a call to the function rgb). By default, if only one contour is to be plotted, it will be plotted in black. Alternatively, a vector with a single element, specifying the colour for all contours.
`ltys`	The line type of the contours, with the same required syntax as `cols`; see par.
`trap.col`	The colour of the points representing detector locations.
`circle.traps`	Logical, if `TRUE` circles are plotted around traps that made a detection of the individual in question.
`show.labels`	Logical, if `TRUE`, contours are labelled with the appropriate probability density (if `density` is `TRUE`), or the corresponding probability of the individual being within the associated contour, under the estimated density (if `density` is `FALSE`).
`plot.contours`	Logical, if `TRUE`, contours are plotted. Note that, if `FALSE`, nothing corresponding to the density of the individuals' locations is plotted unless `plot.estlocs` is `TRUE`.
`plot.estlocs`	Logical, if `TRUE`, dots are plotted at the mode of the combined densities. If a density has more than a single mode (and the modes have the same density value) then a dot will be plotted for each.
`keep.estlocs`	Logical, if `TRUE`, the locations of the estimated locations are returned.
`plot.arrows`	Logical, if `TRUE`, arrows indicating the estimated bearing to the individual are plotted from detectors at which detections were made.
`plot.circles`	Logical, if `TRUE`, circles indicating the estimated distance to the individual are plotted around detectors at which detections were made.
`arrow.length`	Numeric, providing the length of the arrows (only used if `plot.arrows` is `TRUE`).
`show.legend`	Logical, if `TRUE`, a legend will be added to the plot.
`show.axes`	Logical, if `TRUE`, axes will be added to the plot.
`add`	Logical, if `TRUE`, contours will be added to an existing plot.

locations(example$fits$simple.hn, 1)
locations(example$fits$simple.hn, 1, levels = c(0.50, 0.90, 0.95))
## Not run: 
fine.mask <- create.mask(example$traps, 20, spacing = 0.2)
locations(example$fits$bearing.hn, 1, infotypes = "all", mask = fine.mask)

## End(Not run)