Simulates a static spatial, sex, and age-structured population (no feedback loop)

Usage

Simulate_Pop_Static(sim_list, output_path)

Arguments

sim_list: Simulation list objects
output_path: path to output simulation objects

Value

a list object with a bunch of simulated values and outputs

Examples

if (FALSE) { # \dontrun{
  # Set up model dimensions
 sim_list <- Setup_Sim_Dim(n_sims = 100,
                           n_yrs = 10,
                           n_regions = 2,
                           n_ages = 8,
                           n_sexes = 1,
                           n_fish_fleets = 1,
                           n_srv_fleets = 1
 )

 # set up containers
 sim_list <- Setup_Sim_Containers(sim_list)

 # Setup fishing mortality
 sim_list <- Setup_Sim_FishMort(sim_list = sim_list,
                                sigmaC = 1e-3,
                                init_F = matrix(0, nrow = sim_list$n_regions, ncol = sim_list$n_fish_fleets),
                                Fmort_pattern = matrix(c('two-way', "two-way"), nrow = sim_list$n_regions, ncol = sim_list$n_fish_fleets),
                                Fmort_start = matrix(c(0.01, 0.01), nrow = sim_list$n_regions, ncol = sim_list$n_fish_fleets),
                                Fmort_fct = matrix(c(15, 15), nrow = sim_list$n_regions, ncol = sim_list$n_fish_fleets),
                                proc_error = TRUE,
                                proc_error_sd = 0.1)

 # Setup fishery selectivity
 sim_list <- Setup_Sim_FishSel(sel_model = matrix(c('logistic', "logistic"), nrow = sim_list$n_regions, ncol = sim_list$n_fish_fleets),
                               # a50, k for logistic shared across regions
                               fixed_fish_sel_pars = array(c(3,3,1,1), dim = c(sim_list$n_regions, sim_list$n_sexes, sim_list$n_fish_fleets, 2)),
                               sim_list = sim_list
 )

 # Setup survey catchability and selectivity
 sim_list <- Setup_Sim_Survey(
   sim_list = sim_list,
   sigmaSrvIdx = array(0.2, dim = c(sim_list$n_regions, sim_list$n_srv_fleets)), # survey observation error
   base_srv_q = array(1, dim = c(sim_list$n_regions, sim_list$n_srv_fleets)), # base survey catchability value
   srv_q_pattern = matrix(c('constant', "constant"), nrow = sim_list$n_regions, ncol = sim_list$n_srv_fleets), # catchability pattern
   sel_model = matrix(c('logistic', "logistic"), nrow = sim_list$n_regions, ncol = sim_list$n_srv_fleets), # selectivity model
   # a50, k, for logistic shared across regions
   fixed_srv_sel_pars = array(c(3,3,1,1), dim = c(sim_list$n_regions, sim_list$n_sexes, sim_list$n_srv_fleets, 2))
 )

 # Setup recruitment stuff
 sim_list <- Setup_Sim_Rec(
   sim_list = sim_list,
   do_recruits_move = "dont_move", # == 0, recruits don't move , == 1 recruits move
   base_rec_sexratio = 1, # single sex
   rec_sexratio_vary = "constant",
   base_r0 = c(50, 50),
   r0_vary = "constant",
   base_h = c(0.8, 0.8),
   init_sigmaR = 0.5,
   sigmaR = 0.5,
   recruitment_opt = "bh_rec",
   rec_dd = "global",
   init_dd = "global",
   rec_lag = 1
 )

 # Setup biologicals
 sim_list <- Setup_Sim_Biologicals(
   sim_list = sim_list,
   base_M_value = array(0.5, dim = c(sim_list$n_regions, sim_list$n_ages, sim_list$n_sims)),
   M_pattern = "constant",
   base_WAA_values = array(rep(5 * (1 - exp(-0.1 * 1:sim_list$n_ages)), each = sim_list$n_regions * sim_list$n_sexes),
                           dim = c(sim_list$n_regions, sim_list$n_ages, sim_list$n_sexes)),
   WAA_pattern = "constant",
   base_Maturity_AA_values = array(rep(1 / (1 + exp(-0.3 * 1:sim_list$n_ages)), each = sim_list$n_regions * sim_list$n_sexes),
                                   dim = c(sim_list$n_regions, sim_list$n_ages, sim_list$n_sexes)),
   Maturity_AA_pattern = "constant"
 )

 # Setup tagging stuff
 sim_list <- Setup_Sim_Tagging(
   sim_list = sim_list,
   n_tags = 5000,
   max_liberty = 30,
   tag_years = seq(1, sim_list$n_yrs, 3),
   t_tagging = 0.5,
   base_Tag_Reporting = c(0.2, 0.2),
   Tag_Reporting_pattern = "constant",
   Tag_Ind_Mort = 0,
   Tag_Shed = 0
 )

 # Setup observation processes
 sim_list <- Setup_Sim_Observation_Proc(
   sim_list = sim_list,
   Comp_Structure = "spltR_jntS",
   Comp_Srv_Like = "Multinomial",
   Comp_Fish_Like = "Multinomial",
   ISS_FishAge_Pattern = 'F_pattern',
   FishAgeTheta = 3,
   SrvAgeTheta = 2,
   Srv_Like_Pars = NA,
   base_ISS_FishAge = 200,
   base_ISS_SrvAge = 200,
   Tag_Like = "Poisson",
   Tag_Like_Pars = NA
 )

 # IID Movement Matrix across years and ages
 ref <- 1
 movement_matrix <- array(0, dim = c(sim_list$n_regions, sim_list$n_regions, sim_list$n_yrs, sim_list$n_ages, sim_list$n_sexes, sim_list$n_sims)) # From, To
 base <- matrix(0, sim_list$n_regions, sim_list$n_regions)

 # Plug in movement process error
 for(sim in 1:sim_list$n_sims) {
   for(a in 1:sim_list$n_ages) {
     for(s in 1:sim_list$n_sexes) {
       for(y in 1:sim_list$n_yrs) {
         for(r in 1:sim_list$n_regions) {
           if(a > 1) pe_err <- rnorm(length(tmp_move[-ref]), 0, 0.4) # logit proces error
           else pe_err <- 0
           tmp_move <- base[r,]
           tmp_move[-ref] <- tmp_move[-ref] + pe_err
           movement_matrix[r,,y,a,s,sim] <- exp(tmp_move) / sum(exp(tmp_move))
         }
       } # end y loop
     } # end s loop
   } # end a loop
 } # end sim loop

 sim_list$movement_matrix <- movement_matrix

 # Run Simulation ----------------------------------------------------------
 Simulate_Pop_Static(sim_list = sim_list, output_path = here("sim_out.RDS"))
} # }