eval-demeter-final

#!/usr/bin/env Rscript

source("dependencies.R")
source("demeter.R")
source("pre_fit.R")
source("post_fit.R")
library(optparse)

flog.appender(appender.console())
flog.threshold(DEBUG)

option_list = list(
    make_option("--randseed", type="integer"),
    make_option("--G.S", type="numeric"),
    make_option("--alpha.beta.gamma", type="numeric"),
    make_option("--learning.rate", type="numeric"),
    make_option("--full.data.file", type="character"),
    make_option("--dest.dir", type="character"),
    make_option("--max.num.iter", type="integer")
); 
 
opt_parser = OptionParser(option_list=option_list);
print( commandArgs(trailingOnly = TRUE) )
opt = parse_args(opt_parser);

holdout.fold <- opt$holdout.fold
fold.count <- opt$fold.count
seed <- opt$randseed

# this will load 'm' and 'full.data'
load(opt$full.data.file)
stopifnot(!is.null(m))

set.seed(seed)

optval <- function(n) {
    v <- opt[[n]]
    if(is.null(v)) {
        stop("Expected a value for ", n, " but got NULL")
    }
    v
}

learning.rate <- optval("learning.rate")
max.num.iter <- optval("max.num.iter")
performance.log.file <- tempfile()
G.S <- optval("G.S")
alpha.beta.gamma <- optval("alpha.beta.gamma")
dest.dir <- optval("dest.dir")

# this will load 'm' and 'full.data'
load(opt$full.data.file)
stopifnot(!is.null(m))

mu <- 0
lambda <- c(G.S, G.S, alpha.beta.gamma, alpha.beta.gamma, mu, alpha.beta.gamma)

DEMETER(m, learning.rate, lambda, max.num.iter, dest.dir)