source("Zhang_simfuns.R")
library(R2admb)
setup_admb()
compile_admb("analyzer_df",re=TRUE)
compile_admb("analyzer",re=TRUE)

##################
tauvec <- c(0.001,0.5,2)
nMCMC <- 500
fn <- "Zhang_ADMBsim.RData"

set.seed(1001)
reslist <- list()
reslist$res_admb_LX <- sfun2(admb.LX_fun,nMCMC=nMCMC,debug=TRUE)
save("reslist",file=fn)
reslist$res_admb_L <- sfun2(admb.L_fun,nMCMC=nMCMC,debug=TRUE)
save("reslist",file=fn)
reslist$res_admb_LX_is100 <- sfun2(admb.LX_fun,is=100,nMCMC=nMCMC)
save("reslist",file=fn)

## if (FALSE) {
##   ## testing 
##   for (i in 1:100) {
##     cat(i,"\n")
##     options(warn=2)
##     set.seed(1000+i)
##     admb.L_fun(n=50,tau=0.001,clean=FALSE)
##   }

##   load("current_run.RData")
##   debug(fun)
##   fun(n=nvec[i],tau=tauvec[j],clean=FALSE,verbose=TRUE)

##   admb.L_fun0(n=50)

## admb.L_fun0 <- function(...,n,clean=TRUE,verbose=FALSE,is=0,
##                         tpl="analyzer_var0") {
##   xargs <- "-mno 100000 -gbs 200000000 -cbs 100000000"
##     d <- simfun(n=n,...)
##     write_dat(tpl,list(n=n,x=d$x,Y=d$y))
##     if (is>0) {
##       xargs <- paste(xargs,"-is",is)
##     }
##     run_admb(tpl,extra.args=xargs,verbose=verbose)
##     g0 <- read_admb(tpl)
##     if (clean) clean_admb(tpl)
##     coef(summary(g0))[4:5,]
## }

## }