# Template for script to start a new burnin
# Run this script from within a directory that will also
# contain the output
library(mSigHdp)
library(hdpx)
if (file.exists("parameters.csv")) {
params <- read.csv("parameters.csv")
cpiter <- params$cpiter
burnin <- params$burnin
} else {
cpiter <- 3
burnin <- 15000
write.csv(data.frame(cpiter = cpiter, burnin = burnin),
"parameters.csv")
}
setwd("~/panc.test/panc.syn.binom.size.100/") ##the dir to get catalog and output
seedNumber <- 20616
no.chains <- 1 ##number of independent initial burn-ins
K.guess <- 400
input.catalog <- ICAMS::ReadCatalog("ground.truth.syn.catalog.csv") # Update this
run.activateandburn <- function(seed){
message(paste0("Start ",burnin, " burn-in iterations with seed ",seed))
burnin.output <- ActivateAndBurnin(input.catalog = input.catalog,
seedNumber = seed,
K.guess = K.guess, # Change this
multi.types = TRUE,
verbose = TRUE,
burnin = burnin,
cpiter = cpiter,
burnin.verbosity = 0,
gamma.alpha = 1,
gamma.beta = 1)
burnin.output$number <- 1
burnin.output$all.lik <- burnin.output$likelihood ##this will be used in continue burnin
pdf(file = paste0(seed,".1.burnin.lik.pdf"), paper = "a4")
plot(burnin.output$likelihood, pch=16, cex=0.5) ##change to a bigger dot
dev.off()
save(burnin.output, file = paste0(seed,".1.burnin.alpha1beta1output.k400.Rdata"))
}
if(no.chains ==1){
run.activateandburn(seedNumber)
}else{
parallel::mclapply(
# Must choose a different seed for each of the chains
X = (seedNumber + 1:no.chains * 10^6) ,
FUN = run.activateandburn,
mc.cores = no.chains)
}
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