R/simulatorAll.R

In sylvainschmitt/ecoevosimulator: Eco-evolutionnary simulator

#' @include generateNCI.R generateTopography.R simulator.R
NULL

#' Title
#'
#' @param grid int.  Number of cells per side of the matrix.
#' @param Nt int. Number of time steps.
#' @param timestep int. Time-step length in years.
#' @param topography char. Topography generator between 'sinusoidal',
#'   'squarediamond' or 'paracou'.
#' @param Elim double. Environmental matrix extrme (absolute value).
#' @param amplitude double. Amplitude of the sinusoidal functional.
#' @param ruggedness double. Ruggedness parameter.
#' @param plot int. Plot number between 1 and 15 (a cell size is 3x3m).
#' @param grid int. Number of cells per side of the matrix.
#' @param Nt int. Number of time-steps.
#' @param timestep int. Time-step length in years.
#' @param muNCI double. mu parameter for the normal distribution used for NCI.
#' @param sigmaNCI double. sigma parameter for the normal distribution used for
#'   NCI.
#' @param alpha double. Intercept for the Bernoulli distribution determining the
#'   risk to have a negative deltaNCI.
#' @param beta double. Slope of previous NCI for the Bernoulli distribution
#'   determining the risk to have a negative deltaNCI.
#' @param mu double. mu parameter for the lognormal distribution used for
#'   positive deltaNCI.
#' @param sigma double. sigma parameter for the lognormal distribution used for
#'   positive deltaNCI.
#' @param lambda double. lambda parameter for the exponential distribution used
#'   for negative deltaNCI.
#' @param d int. Spatial auto-correlation size in number of cells.
#' @param sigmaGtopo double. Variance of genetic values with topography.
#' @param sigmaZtopo double. Plasticity of phenotypes with topography.
#' @param sigmaGnci double. Variance of genetic values with NCI.
#' @param sigmaZnci double. Plasticity of phenotypes with NCI.
#' @param Pdeath double. Background mortality probability.
#' @param Ns int. Number of seedlings per cell.
#' @param Rpollination int. Pollination radius in cells (father to mother).
#' @param Rdispersion int. Dispersal radius in cells (mother to seedling).
#' @param determinist bool. Deterministic or probabilistic viability.
#' @param verbose bool. Should the function print statuses.
#'
#' @return A data frame.
#' 
#' @export
#'
#' @examples
#' simulatorAll()
#' 
simulatorAll <- function(
  grid = 20,
  Nt = 50,
  timestep = 30, # time-step length in years
  topography = "sinusoidal",
  Elim = 5,
  amplitude = 1,
  ruggedness = 1,
  plot = 1,
  muNCI = 124, # mu of normal distribution for NCI
  sigmaNCI = 26, # sigma of normal distribution NCI
  alpha = -1.32,
  beta = 0.003,
  mu = 0.749, # mu of lognormal distribution for positive deltaNCI
  sigma = 2.651, # sigma of lognormal distribution for positive deltaNCI
  lambda = 0.31, # lambda of exponential distribution for negative deltaNCI
  d = 3, # spatial auto-correlation size (3*3m)
  sigmaGtopo = 1,
  sigmaZtopo = 1,
  sigmaGnci = 26,
  sigmaZnci = 26,
  Pdeath = 0.01325548,
  Ns = 4,
  Rpollination = 1,
  Rdispersion = 1,
  determinist = TRUE,
  verbose = TRUE
){
  if(verbose)
    message("Generate topography")
  Topo <- generateTopography(
    grid = grid,
    topography = topography,
    Elim = Elim,
    amplitude = amplitude,
    ruggedness = ruggedness,
    plot = plot
  )
  if(verbose)
    message("Generate NCI")
  NCI <- generateNCI(
    grid = grid, 
    Nt = Nt, 
    timestep = timestep,
    muNCI = muNCI,
    sigmaNCI = sigmaNCI,
    alpha = alpha,
    beta = beta,
    mu = mu,
    sigma = sigma,
    lambda = lambda,
    d = d
  )
  if(verbose)
    message("Simulate")
  sim <- simulator(
    grid = grid,
    Nt = Nt,
    timestep = timestep,
    topography = Topo,
    NCI = NCI,
    sigmaGtopo = sigmaGtopo,
    sigmaZtopo = sigmaZtopo,
    sigmaGnci = sigmaGnci,
    sigmaZnci = sigmaZnci,
    Pdeath = Pdeath,
    Ns = Ns,
    Rpollination = Rpollination,
    Rdispersion = Rdispersion,
    determinist = determinist
  )
  return(sim)
}