R/prep_simulation.R

In qleclerc/efficientspatial: Efficient Spatial Modelling of Epidemics

#' @title Performs pre-calculations necessary for the simulation of an epidemic (Raster)
#'
#' @description Creates the age mixing matrix and the spatial kernel using the \code{\link{load_contact_mat}},
#'              \code{\link{calc_dist_mat}}, \code{\link{calc_dist_kernel}} and \code{\link{calc_beta}} functions.
#'
#' @param rasterl The RasterLayer object containing the population data.
#' @param R0 The desired R0 for the epidemic
#' @param sigma The desired recovery rate for the epidemic
#' @param age Logical. If TRUE, the simulation will assume four distincts age groups in the population (default).
#'            If FALSE, the simulation will assume homogeneous mixing between age groups in the population.
#'
#' @return Returns two matrix objects and one value for beta.
#'
#' @examples
#'
#' #Create a RasterLayer object:
#' test_data = raster(nrow=10, ncol=10, xmn=1, xmx=100000, ymn=1, ymx=100000)
#' values(test_data) = runif(100, 1, 1000)
#'
#' prep_simulation(test_data)
#'
#'
#' @export


prep_simulation = function(rasterl, R0 = 1.8, sigma= 1/2.6, age=TRUE){

  assign("contact_mat", load_contact_mat(age), envir=.GlobalEnv)

  print("Calculating distance matrix...")

  d = calc_dist_mat(rasterl)

  print("Calculating kernel matrix...")

  #Must change this so that kernel parameters can be modified easily outside function!
  kernel = calc_dist_kernel(d, dist_c = 87, rasterl, alpha=0.95, p=6.6, p2=1.53, aa=35)

  print("Calculating beta...")

  assign("beta", calc_beta(rasterl, kernel, contact_mat, R0=R0, sigma=sigma), envir=.GlobalEnv)


}