githubactiontest:

# library("rstudioapi")
# maindir <<- dirname(dirname(getActiveDocumentContext()$path))
# subdir <<- "MAS"


setwd("C:/Users/bai.li/Documents/Github/RMAS-master/")
devtools::load_all()
library(RMAS)
library(Rcpp)
library(jsonlite)
library(callr)

load(file.path(maindir, "output", subdir, "om_sim.RData"))
#load(file.path(maindir, "output", subdir, "myEnvironment.RData"))

#load the r4mas module
load(file=file.path(maindir, "output", "OM", paste("OM", om_sim, ".RData", sep="")))

r4mas <- Module("rmas", dyn.load(paste("C:/Users/bai.li/Documents/Github/RMAS-master/src/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, area1$id)
population$AddRecruitment(recruitment$id, 1, area1$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)
#The other four models uses standard multinomial for age comp nll
survey_index_comp_nll<-new(r4mas$Lognormal)
survey_age_comp_nll<-new(r4mas$Multinomial)
#The other four models uses standard multinomial for age comp nll


#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()
om_sim <<- om_sim+1
save(om_sim, file=file.path(maindir, "output", subdir, "om_sim.RData"))
#gc()
#rm(list=setdiff(ls(), c("maindir", "subdir", "om_sim", "om_sim_num")))

# .rs.restartR(afterRestartCommand = 'source("C:/Users/bai.li/Documents/Github/Age_Structured_Stock_Assessment_Model_Comparison/ASSAMC/example/em_input/mas.R")')

#install.packages("RDCOMClient", repos = "http://www.omegahat.net/R")
# if (om_sim <= om_sim_num){
#   library(RDCOMClient)
#   wsh <- COMCreate("Wscript.Shell")
#   wsh$SendKeys("^+{F10}")
#   source("C:/Users/bai.li/Documents/Github/Age_Structured_Stock_Assessment_Model_Comparison/ASSAMC/example/em_input/mas.R")
# }


if (om_sim <= om_sim_num){
  Sys.sleep(0.5)
  .rs.restartR(afterRestartCommand = 'source("C:/Users/bai.li/Documents/Github/Age_Structured_Stock_Assessment_Model_Comparison/ASSAMC/example/em_input/mas.R")')
}

# if (om_sim <= om_sim_num){
#   source("C:/Users/bai.li/Documents/Github/Age_Structured_Stock_Assessment_Model_Comparison/ASSAMC/example/em_input/mas.R")
# }
#


# gc()
#library(rstudioapi)
# if (om_sim <= om_sim_num){
#   restartSession(command='source("C:/Users/bai.li/Documents/Github/Age_Structured_Stock_Assessment_Model_Comparison/ASSAMC/example/em_input/mas.R")')
# }