data-raw/runsom.R

In iagomosqueira/mseviz: Plots and Visualization Tools for Management Strategy Evaluation Results

# runsom.R - DESC
# /runsom.R

# Copyright European Union, 2018
# Author: Iago Mosqueira (EC JRC) <iago.mosqueira@ec.europa.eu>
#
# Distributed under the terms of the European Union Public Licence (EUPL) V.1.1.

library(FLasher)
library(FLBRP)

# DATA
data(ple4)
data(ple4.indices)

# SR and BRP
p4sr <- fmle(as.FLSR(ple4, model='ricker'))
p4rp <- brp(FLBRP(ple4, sr=p4sr))

# OMP
omp <- propagate(fwdWindow(ple4, p4rp, end=2038)[, ac(2008:2038)], 250)
residuals <- rlnorm(250, residuals(p4sr), 0.5)[,sample(1:51, 30)]
dimnames(residuals) <- list(year=2009:2038)

# fwd(omp)
omps <- FLStocks(parallel::mclapply(seq(0.1, 0.4, length=6), function(x) {
  fwd(omp, sr=p4sr, residuals=residuals,
    control=fwdControl(year=2009:2038, quant='f', value=runif(250*30, x, x*1.5)))
  }, mc.cores = 2))

# RUNS
names(omps) <- paste0("MP", 1:6)

library(data.table)

# METRICS
runs <- lapply(omps, metrics, metrics=list(F=fbar, SB=ssb, C=catch))
# runs <- rbindlist(lapply(runs, as.data.frame, drop=TRUE), idcol="mp")

# OM
om <- metrics(ple4, metrics=list(F=fbar, SB=ssb, C=catch))

save(om, runs, file="../data/omruns.RData")

# PERF

library(mse)

data(statistics)

perf <- performance(omps, metrics=list(F=fbar, SB=ssb, C=catch),
  refpts=FLPar(SB0=1500000, SBMSY=400000, Ftarget=0.21, FMSY=0.21, SBlim=200000),
  statistics=statistics[c(1,2,4,5,6,9,10,11,12)], years=list(2020:2038))

save(perf, file="../data/perf.RData")