githubactiontest:

run_mas = function(maindir=maindir, subdir="MAS", om_sim_num=NULL){

  setwd(maindir)
  setwd("..")
  setwd("..")
  wd <- getwd()

  download.file(url = "https://github.com/nmfs-fish-tools/RMAS/archive/master.zip", destfile = file.path(wd, "RMAS-master.zip"))
  unzip(zipfile = "RMAS-master.zip")
  rmas_dir <- paste(wd, "/RMAS-master/src/", sep="")

  list_of_packages = c("Rcpp", "jsonlite", "callr")
  missing_packages = list_of_packages[!(list_of_packages %in% installed.packages()[,"Package"])]
  if(length(missing_packages)) install.packages(missing_packages)

  library(Rcpp)
  library(jsonlite)
  library(callr)

  setwd(file.path(maindir, "output", subdir))
  unlink(list.files(file.path(maindir, "output", "MAS"), full.names = TRUE), recursive = TRUE)
  sapply(1:om_sim_num, function(x) dir.create(file.path(maindir, "output", subdir, paste("s", x, sep=""))))

  for (om_sim in 1:om_sim_num){
    load(file=file.path(maindir, "output", "OM", paste("OM", om_sim, ".RData", sep="")))

    #load the r4mas module
    devtools::load_all(rmas_dir)
    r4mas = Module("rmas", dyn.load(paste(rmas_dir, "RMAS", .Platform$dynlib.ext, sep = "")))
    nyears=om_input$nyr
    nseasons=1
    nages=om_input$nages
    ages = om_input$ages

    #define area
    area1=new(r4mas$Area)
    area1$name="area1"

    #Recruitment
    recruitment=new(r4mas$BevertonHoltRecruitment)
    recruitment$R0$value=om_input$R0/1000
    recruitment$R0$estimated=TRUE
    recruitment$R0$phase=1
    recruitment$h$value=om_input$h
    recruitment$h$estimated=FALSE
    recruitment$h$phase=3
    recruitment$h$min=0.02001
    recruitment$h$max=1.0
    recruitment$sigma_r$value = exp(om_input$logR_sd)
    recruitment$sigma_r$estimated=FALSE
    recruitment$sigma_r$min=0
    recruitment$sigma_r$max=1.0
    recruitment$sigma_r$phase=2
    recruitment$estimate_deviations=TRUE
    recruitment$constrained_deviations=FALSE
    recruitment$deviations_min=-15.0
    recruitment$deviations_max=15.0
    recruitment$deviation_phase=1
    recruitment$SetDeviations(rep(0.0, times=om_input$nyr))

    #Growth
    growth=new(r4mas$VonBertalanffyModified)
    empirical_weight=rep(om_input$W.kg, times=om_input$nyr)
    survey_empirical_weight=replicate(nages*nyears, 1.0)
    growth$SetUndifferentiatedCatchWeight(empirical_weight)
    growth$SetUndifferentiatedSurveyWeight(survey_empirical_weight)
    growth$SetUndifferentiatedWeightAtSeasonStart(empirical_weight)
    growth$SetUndifferentiatedWeightAtSpawning(empirical_weight)
    growth$a_min$value=0.01
    growth$a_max$value=10.0
    growth$c$value=0.3
    growth$lmin$value=5
    growth$lmax$value=50
    growth$alpha_f$value=0.000025
    growth$alpha_m$value=0.000025
    growth$beta_f$value=2.9624
    growth$beta_m$value=2.9624

    #Maturity
    maturity=new(r4mas$Maturity)
    maturity$values = om_input$mat.age*0.5

    #Natural Mortality
    natural_mortality=new(r4mas$NaturalMortality)
    natural_mortality$SetValues(om_input$M.age)

    #define Movement (only 1 area in this model)
    movement=new(r4mas$Movement)
    movement$connectivity_females=c(1.0)
    movement$connectivity_males=c(1.0)
    movement$connectivity_recruits=c(1.0)

    #Initial Deviations
    initial_deviations=new(r4mas$InitialDeviations)
    initial_deviations$values=rep(0, times=om_input$nages)
    initial_deviations$estimate=FALSE
    initial_deviations$phase=1

    population=new(r4mas$Population)
    for (y in 0:(nyears))
    {
      population$AddMovement(movement$id, y)
    }

    population$AddNaturalMortality(natural_mortality$id,area1$id,"undifferentiated")
    population$AddMaturity(maturity$id,area1$id, "undifferentiated")
    population$AddRecruitment(recruitment$id, 1, area1$id)
    #population$AddRecruitment(recruitment$id, area1$id)
    population$SetInitialDeviations(initial_deviations$id, area1$id, "undifferentiated")
    population$SetGrowth(growth$id)
    population$sex_ratio=0.5

    #Fishing Mortality
    fishing_mortality=new(r4mas$FishingMortality)
    fishing_mortality$estimate=TRUE
    fishing_mortality$phase=1
    fishing_mortality$min=0.0
    fishing_mortality$max=4
    fishing_mortality$SetValues(om_output$f)

    #Selectivity Model
    fleet_selectivity=new(r4mas$LogisticSelectivity)
    fleet_selectivity$a50$value=om_input$sel_fleet$fleet1$A50.sel
    fleet_selectivity$a50$estimated=TRUE
    fleet_selectivity$a50$phase=2
    fleet_selectivity$a50$min=0.0
    fleet_selectivity$a50$max=max(om_input$ages)

    fleet_selectivity$slope$value=1/om_input$sel_fleet$fleet1$slope.sel
    fleet_selectivity$slope$estimated=fleet_selectivity$a50$estimated
    fleet_selectivity$slope$phase=2
    fleet_selectivity$slope$min=0
    fleet_selectivity$slope$max=max(om_input$ages)

    survey_selectivity=new(r4mas$LogisticSelectivity)
    survey_selectivity$a50$value=om_input$sel_survey$survey1$A50.sel
    survey_selectivity$a50$estimated=TRUE
    survey_selectivity$a50$phase=2
    survey_selectivity$a50$min=0.0
    survey_selectivity$a50$max=max(om_input$ages)

    survey_selectivity$slope$value=1/om_input$sel_survey$survey1$slope.sel
    survey_selectivity$slope$estimated=survey_selectivity$a50$estimated
    survey_selectivity$slope$phase=2
    survey_selectivity$slope$min=0
    survey_selectivity$slope$max=max(om_input$ages)

    #Index data
    catch_index=new(r4mas$IndexData)
    catch_index$values=em_input$L.obs$fleet1
    #dat.input$cv.L
    catch_index$error=rep(em_input$cv.L$fleet1, times=om_input$nyr)

    survey_index=new(r4mas$IndexData)
    survey_index$values=em_input$survey.obs$survey1
    survey_index$error=rep(em_input$cv.survey$survey1, times=om_input$nyr)


    #Age Comp Data
    catch_comp=new(r4mas$AgeCompData)
    catch_comp$values=as.vector(t(em_input$L.age.obs$fleet1))
    catch_comp$sample_size =rep(em_input$n.L$fleet1, nyears*nseasons)

    survey_comp=new(r4mas$AgeCompData)
    survey_comp$values=as.vector(t(em_input$survey.age.obs$survey1))
    survey_comp$sample_size=rep(em_input$n.survey$survey1, times=om_input$nyr)

    #NLL models
    fleet_index_comp_nll=new(r4mas$Lognormal)
    fleet_age_comp_nll=new(r4mas$Multinomial)

    survey_index_comp_nll=new(r4mas$Lognormal)
    survey_age_comp_nll=new(r4mas$Multinomial)

    #Fleet
    fleet=new(r4mas$Fleet)
    fleet$AddAgeCompData(catch_comp$id, "undifferentiated")
    fleet$AddIndexData(catch_index$id, "undifferentiated")
    fleet$SetAgeCompNllComponent(fleet_age_comp_nll$id)
    fleet$SetIndexNllComponent(fleet_index_comp_nll$id)
    fleet$AddSelectivity(fleet_selectivity$id, 1, area1$id)
    fleet$AddFishingMortality(fishing_mortality$id, 1,area1$id)


    #Survey
    survey=new(r4mas$Survey)
    survey$AddAgeCompData(survey_comp$id,"undifferentiated")
    survey$AddIndexData(survey_index$id,"undifferentiated")
    survey$SetIndexNllComponent(survey_index_comp_nll$id)
    survey$SetAgeCompNllComponent(survey_age_comp_nll$id)
    survey$AddSelectivity(survey_selectivity$id, 1, area1$id)
    survey$q$value=em_input$survey_q$survey1
    survey$q$min=0
    survey$q$max=10
    survey$q$estimated=TRUE
    survey$q$phase=1

    #build the MAS model
    mas_model=new(r4mas$MASModel)
    mas_model$nyears=nyears
    mas_model$nseasons=nseasons
    mas_model$nages=nages
    mas_model$extended_plus_group=max(om_input$ages)
    mas_model$ages=ages
    mas_model$AddFleet(fleet$id)
    mas_model$catch_season_offset=0.0
    mas_model$spawning_season_offset=0.0
    mas_model$survey_season_offset=0.0

    mas_model$AddSurvey(survey$id)
    mas_model$AddPopulation(population$id)
    mas_model$Run()
    output_file = file.path(maindir, "output", subdir, paste("s", om_sim, sep=""), paste("s", om_sim, ".json", sep=""))
    write(mas_model$GetOutput(), file=toString(output_file))
    mas_model$Reset()
    #rm(r4mas, mas_model)
    #rm(mas_model)
  }
}