R/fnMSE.R

In nissandjac/PacifichakeMSE: Management strategy evaluation of Pacific hake

###### Initialize the operating model ######
#' Title
#'
#' @param df parameters
#' @param simyears number of years to simulate
#' @param TAC which harvest control rule to use
#' @param seeds seed
#' @param nruns number of iterations
#'
#' @return
#' @export
#'
#' @examples
#'
#' fnMSE(df, nruns = 15) # Run MSE with 15 iterations
#'
fnMSE <- function(df, simyears = 30, TAC = 1, seeds = NA, nruns = 100){

# Set the seed
if(is.na(seeds)){
  seeds <- 12345
}else{
  set.seed(seeds)
}

time <- 1
yrinit <- df$nyear
seeds <- floor(runif(n = nruns, min = 1, max = 1e6))
### Run the OM and the EM for x number of years in the MSE
### Set targets for harvesting etc
#

year.future <- c(df$years,(df$years[length(df$years)]+1):(df$years[length(df$years)]+simyears))
N0 <- NA
sim.data <- run.agebased.true.catch(df) # Run the operating model until 2018

simdata0 <- sim.data # The other one is gonna get overwritten.


# ### Loop MSE's with different errors in future survey and recruitment
ls.save <- list()
ls.converge <- matrix(0, nruns)
#
for (i in 1:nruns){
  tmp <- try(run_multiple_MSEs(simyears = simyears,
                               seed = seeds[i],
                               TAC = TAC,
                               df))
  #tmp <- run_multiple_MSEs(simyears = 30, seeds[i])
  print(i)

  if(is.list(tmp)){
    ls.save[[i]] <-tmp
    ls.converge[i] <- 1
  }else{
    ls.save[[i]] <- NA
    ls.converge[i] <- 0
    print('model not converged')
  }


}

return(list(MSE = ls.save,OM = sim.data))

}