source("utils.R")
source("utils-bm-seq.R")
library(biomformat)
library(phyloseq)
library(R.utils)
library(stringr)
library(sbm)
library(blockmodels)
library(tictoc)

the_data <- import_biom("data/mach/kinetic.biom")

# fit_res <- lapply(per_taxa_network, function(network) {
#     withTimeout(
#         expr = {
#             fit <- estimateBipartiteSBM(network, model = "poisson", estimOptions = list(plot = 0))
#         }, timeout = 300,
#         onTimeout = "warning"
#     )
#     if (exists("fit")) {
#         out <- fit
#     } else {
#         out <- NULL
#     }
#     return(fit)
# })

# To init a BM model I need to provide memberships and ICL
# 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)
tic()
r2_model <- BM_poisson(
    membership_type = "LBM",
    adj = per_taxa_networks[[2]], # Account for the root
    verbosity = 6,
    plotting = "",
    ncores = 1, # parallelly::availableCores(),
    autosave = "r2test.Rds"
)
r2_model$estimate()
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)
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)