| make.traps {secr} | R Documentation |
Construct a rectangular array of detectors (trapping grid) or a circle of detectors.
make.grid(nx = 6, ny = 6, spacing = 20, detector = "multi", binomN = 0,
originxy = c(0,0), hollow = F, ID = 'alphay')
make.circle (n = 20, radius = 100, spacing = NULL,
detector = "multi", originxy = c(0,0), IDclockwise = T)
nx |
number of columns of detectors |
ny |
number of rows of detectors |
spacing |
distance between adjacent detectors (nominally in metres) |
detector |
character value for detector type 'single', 'multi' or 'proximity' |
binomN |
maximum value when detector == 'count' |
originxy |
vector origin for x-y coordinates |
hollow |
logical for hollow grid |
ID |
character string to control row names |
n |
number of detectors |
radius |
radius of circle (nominally in metres) |
IDclockwise |
logical for numbering of detectors |
make.grid generates coordinates for nx.ny traps at
separation spacing. The bottom-left (southwest) corner is at
originxy. For a hollow grid, only detectors on the perimeter are
retained. By default, identifiers are constructed from a letter code for
grid rows and an integer value for grid columns ('A1', 'A2',...).
'Hollow' grids are always numbered clockwise in sequence from the
bottom-left corner. Other values of ID have the following
effects:
| ID | Effect |
| numx | column-dominant numeric sequence |
| numy | row-dominant numeric sequence |
| numxb | column-dominant boustrophedonical numeric sequence (try it!) |
| numyb | row-dominant boustrophedonical numeric sequence |
| alphax | column-dominant alphanumeric |
| alphay | row-dominant alphanumeric |
make.circle generates coordinates for n traps in a circle centred on originxy. If spacing is specified then it overrides the radius setting; the radius is adjusted to provide the requested straightline distance between adjacent detectors.
Traps are numbered from the trap due east of the origin, either clockwise or anticlockwise as set by IDclockwise.
An object of class traps comprising a data frame of x- and y-coordinates, the detector type ('single', 'multi', or 'proximity'), and possibly other attributes.
Several methods are provided for manipulating detector arrays - see traps.
Murray Efford murray.efford@otago.ac.nz
Efford, M.G. (2007) Density 4.1: software for spatially explicit capture–recapture. Department of Zoology, University of Otago, Dunedin, New Zealand. http://www.otago.ac.nz/density
Efford, M. G., Borchers D. L. and Byrom, A. E. (2009) Density estimation by spatially explicit capture-recapture: likelihood-based methods. In: D. L. Thomson, E. G. Cooch and M. J. Conroy (eds) Modeling Demographic Processes in Marked Populations. Springer, New York. Pp. 255–269.
read.traps, print.traps, plot.traps, traps
demo.traps <- make.grid()
plot(demo.traps)
## compare numbering schemes
par (mfrow = c(2,4), mar = c(1,1,1,1), xpd = TRUE)
for (id in c('numx', 'numy', 'alphax', 'alphay', 'numxb',
'numyb'))
{
temptrap <- make.grid(nx = 7, ny = 5, ID = id)
plot (temptrap, border = 10, lab = TRUE, offset = 7,
gridl = FALSE)
}
temptrap <- make.grid(nx = 7, ny = 5, hollow = TRUE)
plot (temptrap, border = 10, lab = TRUE, gridl = FALSE)
plot(make.circle(n = 20, spacing = 30), lab = TRUE, offset = 9)
summary(make.circle(n = 20, spacing = 30))