Adding script to run benchmarks for LBM Seq
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Louis
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153
benchmark_lbm_seq.R
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153
benchmark_lbm_seq.R
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source("utils.R")
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source("utils-bm-seq.R")
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library(biomformat)
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library(phyloseq)
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library(R.utils)
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library(stringr)
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library(sbm)
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library(blockmodels)
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library(here)
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library(microbenchmark)
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data_folder <- here("results", "lbm-seq")
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the_data <- import_biom("data/mach/kinetic.biom")
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epoch <- as.integer(Sys.time())
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tmp_folder <- here(data_folder, paste0("tmp", epoch))
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if (!dir.exists(tmp_folder)) {
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dir.create(tmp_folder, recursive = TRUE)
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}
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per_taxa_networks <- collapse_otu_at_taxo(the_data)
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mode <- commandArgs(trailingOnly = TRUE)
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switch(mode,
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"seq" = {
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message("Will use SEQ")
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r2_mbm_seq <- microbenchmark("Rank2seq" = {
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r2_model_seq <- BM_poisson(
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membership_type = "LBM",
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adj = per_taxa_networks[[2]], # Account for the root
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verbosity = 6,
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plotting = "",
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ncores = 1L
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)
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r2_model_seq$estimate()
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}, times = 3L)
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r3_mbm_seq <- microbenchmark("Rank3seq" = {
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r3_model_seq <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 2, target_rank_id = 3, per_taxa_networks = per_taxa_networks, first_model = r2_model_seq, ncores = 1)
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}, times = 3L)
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r4_mbm_seq <- microbenchmark("Rank4seq" = {
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r4_model_seq <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 3, per_taxa_networks = per_taxa_networks, first_model = r3_model_seq, ncores = 1)
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}, times = 3L)
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r5_mbm_seq <- microbenchmark("Rank5seq" = {
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r5_model_seq <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 4, per_taxa_networks = per_taxa_networks, first_model = r4_model_seq, ncores = 1)
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}, times = 3L)
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mbm_seq <- rbind(r2_mbm_seq, r3_mbm_seq, r4_mbm_seq, r5_mbm_seq)
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out_seq <- list(
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benchmark = mbm_seq,
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models = list(
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Rank2 = r2_model_seq,
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Rank3 = r3_model_seq,
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Rank4 = r4_model_seq,
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Rank5 = r5_model_seq
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)
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)
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saveRDS(out_seq, here(tmp_folder, "seq.Rds"))
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},
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"para" = {
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message("Will use PARA")
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r2_mbm_para <- microbenchmark("Rank2para" = {
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r2_model_para <- BM_poisson(
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membership_type = "LBM",
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adj = per_taxa_networks[[2]], # Account for the root
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verbosity = 6,
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plotting = "",
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ncores = parallelly::availableCores()
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)
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r2_model_para$estimate()
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}, times = 3L)
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r3_mbm_para <- microbenchmark("Rank3para" = {
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r3_model_para <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 2, target_rank_id = 3, per_taxa_networks = per_taxa_networks, first_model = r2_model_para, ncores = parallelly::availableCores())
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}, times = 3L)
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r4_mbm_para <- microbenchmark("Rank4para" = {
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r4_model_para <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 3, per_taxa_networks = per_taxa_networks, first_model = r3_model_para, ncores = parallelly::availableCores())
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}, times = 3L)
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r5_mbm_para <- microbenchmark("Rank5para" = {
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r5_model_para <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 4, per_taxa_networks = per_taxa_networks, first_model = r4_model_para, ncores = parallelly::availableCores())
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}, times = 3L)
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mbm_para <- rbind(r2_mbm_para, r3_mbm_para, r4_mbm_para, r5_mbm_para)
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out_para <- list(
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benchmark = mbm_para,
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models = list(
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Rank2 = r2_model_para,
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Rank3 = r3_model_para,
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Rank4 = r4_model_para,
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Rank5 = r5_model_para
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)
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)
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saveRDS(out_para, here(tmp_folder, "para.Rds"))
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},
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"notrans" = { # No transfer
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message("Will use NO TRANSFER")
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r2_mbm_notrans <- microbenchmark("Rank2notrans" = {
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r2_model_notrans <- BM_poisson(
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membership_type = "LBM",
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adj = per_taxa_networks[[2]], # Account for the root
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verbosity = 6,
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plotting = "",
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ncores = parallelly::availableCores()
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)
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r2_model_notrans$estimate()
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}, times = 3L)
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r3_mbm_notrans <- microbenchmark("Rank3notrans" = {
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r3_model_notrans <- BM_poisson(
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membership_type = "LBM",
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adj = per_taxa_networks[[3]], # Account for the root
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verbosity = 6,
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plotting = "",
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ncores = parallelly::availableCores()
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)
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r3_model_notrans$estimate()
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}, times = 3L)
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r4_mbm_notrans <- microbenchmark("Rank4notrans" = {
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r4_model_notrans <- BM_poisson(
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membership_type = "LBM",
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adj = per_taxa_networks[[4]], # Account for the root
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verbosity = 6,
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plotting = "",
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ncores = parallelly::availableCores()
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)
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r4_model_notrans$estimate()
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}, times = 3L)
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r5_mbm_notrans <- microbenchmark("Rank5notrans" = {
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r5_model_notrans <- BM_poisson(
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membership_type = "LBM",
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adj = per_taxa_networks[[5]], # Account for the root
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verbosity = 6,
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plotting = "",
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ncores = parallelly::availableCores()
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)
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r5_model_notrans$estimate()
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}, times = 3L)
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mbm_notrans <- rbind(r2_mbm_notrans, r3_mbm_notrans, r4_mbm_notrans, r5_mbm_notrans)
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out_notrans <- list(
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benchmark = mbm_notrans,
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models = list(
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Rank2 = r2_model_notrans,
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Rank3 = r3_model_notrans,
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Rank4 = r4_model_notrans,
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Rank5 = r5_model_notrans
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)
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)
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saveRDS(out_notrans, here(tmp_folder, "notrans.Rds"))
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},
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stop("Nothing selected, exiting")
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)
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43
sge_scripts/benchmark_lbm_seq.sh
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43
sge_scripts/benchmark_lbm_seq.sh
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@ -0,0 +1,43 @@
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#!/usr/bin/env bash
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#$ -V
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#$ -cwd
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#$ -N increasing_size
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#$ -m besa
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#$ -q short.q
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#$ -t 1-12
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#$ -pe thread 64
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#$ -M louis.lacoste+migale@agroparistech.fr
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#$ -o logs/$JOB_NAME
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#$ -e logs/$JOB_NAME
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# Creating log directory if it doesn't exists
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BASE_DIR="/home/$USER/work/human-microbiome-compendium"
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LOG_DIR=$(echo "$BASE_DIR/logs")
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if [ ! -d "$LOG_DIR" ]; then
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mkdir -p $LOG_DIR
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fi
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# Finding directory
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APPLICATIONS_DIR=$(echo "$BASE_DIR")
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echo $APPLICATIONS_DIR
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ARGID=$(($SGE_TASK_ID % 3))
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case $ARGID in
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0)
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echo -n "Model will be NOTRANS"
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MODE="notrans"
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;;
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1)
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echo -n "Model will be SEQ"
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MODE="seq"
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;;
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2)
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echo -n "Model will be PARA"
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MODE="para"
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;;
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esac
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Rscript "${APPLICATIONS_DIR}/benchmark_lbm_seq.R" $MODE &>> logs/$JOB_NAME.$SGE_TASK_ID
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