generate.population: Defining an Animal Population
In dill/wisp: Wildlife Simulation Package (wisp)

Description Usage Arguments Details Value See Also Examples

This function uses the data stored in the 'pars.population´ object to create a new population object.

1	generate.population(pars.population, seed = NULL)

`pars.population`	An object created by the function `setpars.population` defining the parameters of the population.
`seed`	the number passed to set.seed() to initialise random number generator

An animal population is generated as population object. generate.population works with the object 'pars.population´ that was generated by the function setpars.population. setpars.population has to be run prior.

generate.population returns an object of class 'population´ which has the following elements:

`region`	object of class 'region´
`groupID`	vector of identification numbers for the animal groups.
`posx`	vector of x-positions of the animal groups.
`posy`	vector of y-positions of the animal groups.
`groupsize`	vector of sizes of the animal groups.
`ntypes`	number of possible type properties for the animal groups.
`types`	vector of type properties of the animal groups.
`minexposure`	lowest possible group exposure value.
`maxexposure`	highest possible group exposure value.
`exposure`	vector of exposure values of the animal groups.
`parents`	Details of WiSP objects passed to function
`created`	Creation date and time
`seed`	Equal to the argument 'seed' passed to the function

setpars.population, summary.population plot.population

reg <- generate.region(x.length = 50, y.width = 80)
     
# set up a linear density, add a hotspot and a stripe
dens <- generate.density(reg, nint.x = 50, nint.y = 40, southwest = 1, southeast = 10, northwest = 20)
dens<-add.hotspot(dens, 20,10, 100,10)
dens<-set.stripe(dens, 2,5, 50,70, value = 0, width = 10)
pop.pars<-setpars.population(density.pop = dens, number.groups = 100, size.method = "poisson",
                             size.min = 1, size.max = 5, size.mean = 1, exposure.method = "beta",
                             exposure.min = 2, exposure.max = 10, exposure.mean = 6, exposure.shape = 1)

pop <- generate.population(pop.pars)
summary(pop)
plot(pop)