72 lines
1.9 KiB
R
72 lines
1.9 KiB
R
source("utils.R")
|
|
library(biomformat)
|
|
library(phyloseq)
|
|
library(R.utils)
|
|
library(stringr)
|
|
library(sbm)
|
|
library(blockmodels)
|
|
|
|
the_data <- import_biom("data/chaillou/chaillou.biom")
|
|
|
|
per_taxa_network <- collapse_otu_at_taxo(the_data)
|
|
|
|
# Detect if first rank (higher) is fully collapsed
|
|
if (nrow(per_taxa_network[[1]]) <= 1L) {
|
|
message("The first network has only one row. Removing it.")
|
|
per_taxa_network <- per_taxa_network[-1]
|
|
}
|
|
|
|
# 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)
|
|
# })
|
|
|
|
model <- BM_poisson(
|
|
membership_type = "LBM",
|
|
adj = per_taxa_network[[1]],
|
|
verbosity = 0,
|
|
plotting = "",
|
|
ncores = 1L
|
|
)
|
|
model$estimate()
|
|
# Here we extract the memberships
|
|
best_model_memberships <- model$memberships[[which.max(model$ICL)]]
|
|
next_cc <- list(Z1 = best_model_memberships$Z1, Z2 = best_model_memberships$Z2)
|
|
|
|
# Here we dispatch the memberships for the OTU
|
|
## Propagate the rownames
|
|
rank_id <- 3
|
|
|
|
|
|
rownames(next_cc$Z1) <- rownames(per_taxa_network[[rank_id - 2]])
|
|
next_Z1 <- propagate_taus(tau_matrix = next_cc$Z1, physeq = the_data, taxrank = phyloseq::rank_names(the_data)[rank_id])
|
|
|
|
## Noising of the next_Z1
|
|
dZ1 <- dim(next_Z1)
|
|
nZ1 <- dZ1[1] * dZ1[2]
|
|
next_Z1 <- next_Z1 + matrix(rnorm(n = nZ1, mean = 0, sd = 0.001), nrow = dZ1[1], ncol = dZ1[2])
|
|
|
|
## Normalizing by rows
|
|
C_Z1 <- rowSums(next_Z1)
|
|
next_Z1 <- next_Z1 / C_Z1
|
|
|
|
next_cc$Z1 <- next_Z1
|
|
|
|
next_res <- blockmodels:::dispatcher(
|
|
membership_name = "LBM",
|
|
membership_init = next_cc,
|
|
model_name = "poisson",
|
|
network = list(adjacency = per_taxa_network[[2]]), real_EM = TRUE
|
|
)
|
|
next_cc <- next_res[["membership"]][c("Z1", "Z2")]
|
|
rank_id <- rank_id + 1
|