retro_historical.R

dirs<-c("NorthSeaKeyRun_2014","NorthSeaKeyRun_2017", "NorthSeaKeyRun_2020")   # directory files to be compared
labels<-c("2014 keyrun","2017 keyrun","2020 keyrun") # output legends

prog.path<-file.path(root.prog,"r_prog")

getwd()
#source(file.path(prog.path.func,"compare_runs_objective_function.R"))
compare_runs(
  dirs=dirs,
  labels=labels,
  nox=2, noy=2,
  paper=TRUE,      # graphics on paper=file (TRUE) or on screen (FALSE)
  run.ID='hist_retro',         # file id used for paper output
  doGrid=TRUE,
  extent.SSB=FALSE,  # plot SSB for the year after last assessment year
  first.year.on.plot=1974,
  last.year.on.plot=2020,
  plot.MCMC=FALSE,                        # plot values from MCMC scenarios. FALSE=plot hindcast values from "summary_table_raw.out"
  single.species=FALSE,                   # single species mode or multi species mode
  include.assess.forcast.line=FALSE,      # vertical line at last assessment year
  include.F.reference.points=FALSE,
  include.SSB.reference.points=FALSE,
  include.1.std=FALSE,                   # Include values plus/minus 1 times the standard deviation
  include.2.std=FALSE,
  #incl.sp=c('Herring'),                      # species number to be included. Numbers or "all"
  #incl.sp="all",
  first.pch=0,    # first pch symbol
  first.color=1,   # first color
  palette="default"               # good for colour full plots
  #palette(gray(seq(0,.9,len=10)))  # gray scale for papers, use len =500 to get black only
)  

compare_runs_M2(
  dirs=dirs,
  labels=labels,
  sumQuarterly=FALSE,  # calc M2 as sum of quarterly M2
  nox=3, noy=2,
  paper=TRUE,      # graphics on paper=file (TRUE) or on screen (FALSE)
  run.ID='hist_retro',         # file id used for paper output
  doGrid=TRUE,
  extent.SSB=FALSE,  # plot SSB for the year after last assessment year
  first.year.on.plot=1974,
  last.year.on.plot=2020,
  include.assess.forcast.line=FALSE,      # vertical line at last assessment year
  include.F.reference.points=FALSE,
  include.SSB.reference.points=FALSE,
  include.1.std=FALSE,                   # Include values plus/minus 1 times the standard deviation
  include.2.std=FALSE,
  #incl.sp=c('Herring'),                      # species  to be included.
  #incl.sp="all",
  first.pch=0,    # first pch symbol
  first.color=1,   # first color
  palette="default"               # good for colorfull plots
  #palette(gray(seq(0,.9,len=10)))  # gray scale for papers, use len =500 to get black only
)