R/deprecated/deprecated_calculate_seed_kernel.R

In mhesselbarth/rABMP: R agent-based model for plants

#' #' deprecated_calculate_seed_kernel
#' #'
#' #' @description Calculate seed kernel
#' #'
#' #' @param species Current species
#' #' @param distance distance for which probability is calculated
#' #' @param max_dist maximum distance
#' #'
#' #' @details
#' #' Calculates the probability for a certain distance a species-specific
#' #' seed kernel.
#' #'
#' #' @return vector
#' #'
#' #' @examples
#' #' deprecated_calculate_seed_kernel(species = "Beech", distance = 10, max_dist = 120)
#' #'
#' #' @aliases deprecated_calculate_seed_kernel
#' #' @rdname deprecated_calculate_seed_kernel
#' #'
#' #' @references
#' #' Ribbens, E., Silander, J. A., & Pacala, S. W. (1994). Seedling recruitment in forests:
#' #' Calibrating models to predict patterns of tree seedling dispersion. Ecology, 75(6), 1794-1806.
#' #'
#' #' @export
#' deprecated_calculate_seed_kernel <- function(species, distance, max_dist) {
#'
#'   # Rather us integrate than loop to get normalizer ?
#'   n <- 0
#'
#'   if(species == "Beech"){
#'     kernel_species <- exp(-3.412413 / 10 ^ 5 * distance ^ 3)
#'     for(i in 0:max_dist){
#'       n <- n + exp(-3.412413 / 10 ^ 5 * i ^ 3) # n <- integrate(function(r){exp(-3.412413/10^5*r^3)}, lower=0, upper=Inf)$value
#'     }
#'     kernel_return <- (1 / n) * kernel_species
#'
#'     # Probability based on Milleron et al. (2013) Year 2007
#'     #beta <- stats::runif(n = 1, min = 197.9, max =  244.7)
#'     #kernel_return <- 1 / (pi * beta * (1 + (distance^2 / beta))^2)
#'
#'   }
#'
#'   else if(species == "Ash"){
#'     kernel_species <- exp(-0.922805 / 10 ^ 5 * distance ^ 3)
#'     for(i in 0:max_dist){
#'       n <- n + exp(-0.922805 / 10 ^ 5* i ^ 3) # n <- integrate(function(r){exp(-0.922805/10^5*r^3)}, lower=0, upper=Inf)$value
#'     }
#'     kernel_return <- (1 / n) * kernel_species
#'   }
#'
#'   else if(species == "Sycamore"){
#'     kernel_species <- exp(-7.435026 / 10 ^ 5 * distance ^ 3)
#'     for(i in 0:max_dist){
#'       n <- n + exp(-7.435026 / 10 ^ 5 * i ^ 3) # n <- integrate(function(r){exp(-7.435026/10^5*r^3)}, lower=0, upper=Inf)$value
#'     }
#'     kernel_return <- (1 / n) * kernel_species
#'   }
#'
#'   else if(species == "Hornbeam"){ # same as Beech
#'     kernel_species <- exp(-3.412413 / 10 ^ 5 * distance ^ 3)
#'     for(i in 0:max_dist){
#'       n <- n + exp(-3.412413 / 10 ^ 5 * i ^ 3) # n <- integrate(function(r){exp(-3.412413/10^5*r^3)}, lower=0, upper=Inf)$value
#'     }
#'     kernel_return <- (1 / n) * kernel_species
#'   }
#'
#'   else if(species=="others"){ # mean all other species
#'     kernel_species <- exp(-3.795664 / 10 ^ 5 * distance ^ 3)
#'     for(i in 0:max_dist){
#'       n <- n + exp(-3.795664 / 10 ^ 5 * i ^ 3) # n <- integrate(function(r){exp(-3.795664/10^5*r^3)}, lower=0, upper=Inf)$value
#'     }
#'     kernel_return <- (1 / n) * kernel_species
#'   }
#'
#'   else{
#'     print("Please select valid species - kernel=0 returned")
#'     kernel_species <- 0
#'   }
#'
#'   return(kernel_return)
#' }