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Autosave tests

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Louis 2026-01-28 15:51:17 +01:00
parent d5f1620361
commit 1fe1656700
1 changed files with 6 additions and 2 deletions
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8
lbm_at_diff_taxo_seq.R
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@ -6,6 +6,7 @@ library(R.utils)
library(stringr) library(stringr)
library(sbm) library(sbm)
library(blockmodels) library(blockmodels)
library(tictoc)
the_data <- import_biom("data/mach/kinetic.biom") the_data <- import_biom("data/mach/kinetic.biom")
@ -28,14 +29,17 @@ the_data <- import_biom("data/mach/kinetic.biom")
# And to compute with the dispatcher the previous values to init the models with ICL and memberships # And to compute with the dispatcher the previous values to init the models with ICL and memberships
per_taxa_networks <- collapse_otu_at_taxo(the_data) per_taxa_networks <- collapse_otu_at_taxo(the_data)
tic()
r2_model <- BM_poisson( r2_model <- BM_poisson(
membership_type = "LBM", membership_type = "LBM",
adj = per_taxa_networks[[2]], # Account for the root adj = per_taxa_networks[[2]], # Account for the root
verbosity = 6, verbosity = 6,
plotting = "", plotting = "",
ncores = parallelly::availableCores() ncores = 1, # parallelly::availableCores(),
autosave = "r2test.Rds"
) )
r2_model$estimate() r2_model$estimate()
r3_model <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 2, target_rank_id = 3, per_taxa_networks = per_taxa_networks) toc()
r3_model <- 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, autosave = "r3test.Rds")
r4_model <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 3, per_taxa_networks = per_taxa_networks, first_model = r3_model) r4_model <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 3, per_taxa_networks = per_taxa_networks, first_model = r3_model)
r5_model <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 4, per_taxa_networks = per_taxa_networks, first_model = r4_model) r5_model <- bm_propagate_taus_all_models(phyloseq_data = the_data, rank_id_start = 4, per_taxa_networks = per_taxa_networks, first_model = r4_model)