polarolouis/mia-stage-2024
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

dev : using the now universal extract_best_partition

Browse source
This commit is contained in:
Louis Lacoste 2024-06-19 14:29:57 +02:00
parent bb1f8c7fec
commit ded626f750
9 changed files with 9 additions and 9 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
code/analysis/investigating/impact_of_vem_max_steps.R
View file

@ -129,7 +129,7 @@ results <- parallel::mclapply(seq_len(nrow(conditions)), function(idx) {
elapsed_time <- stop_time - start_time
unlisted_best_partition <- extract_best_bipartite_partition(clust)
unlisted_best_partition <- extract_best_partition(clust)
if (!is.list(unlisted_best_partition)) {
unlisted_best_partition <- list(unlisted_best_partition)

2
code/analysis/investigating/profiling_clustering.R
View file

@ -121,7 +121,7 @@ results <- parallel::mclapply(seq_len(nrow(conditions)), function(idx) {
elapsed_time <- stop_time - start_time
unlisted_best_partition <- extract_best_bipartite_partition(clust)
unlisted_best_partition <- extract_best_partition(clust)
if (!is.list(unlisted_best_partition)) {
unlisted_best_partition <- list(unlisted_best_partition)

2
code/applications/base_analysis.qmd
View file

@ -16,7 +16,7 @@ library(latex2exp)
```
```{r}
list_collection <- readRDS("{{clustering}}")
unlisted_best_partition <- unlist(extract_best_bipartite_partition(list_collection))
unlisted_best_partition <- unlist( extract_best_partition(list_collection))
BICL <- sum(sapply(unlisted_best_partition, function(col) col$BICL))
```

2
code/applications/dore/02_dore_analysis.qmd
View file

@ -40,7 +40,7 @@ Les clustering donne le critère suivant :
vec_bicl <- sapply(list_clustering, function(clustering) {
list_collection <- readRDS(clustering)
unlisted_best_partition <- unlist(
extract_best_bipartite_partition(list_collection)
extract_best_partition(list_collection)
)
BICL <- sum(sapply(unlisted_best_partition, function(col) col$BICL))
BICL

2
code/applications/dore_no_small/02_dore_no_small_analysis.qmd
View file

@ -121,7 +121,7 @@ Les clustering donne le critère suivant :
vec_bicl <- sapply(list_clustering, function(clustering) {
list_collection <- readRDS(clustering)
unlisted_best_partition <- unlist(
extract_best_bipartite_partition(list_collection)
extract_best_partition(list_collection)
)
BICL <- sum(sapply(unlisted_best_partition, function(col) col$BICL))
BICL

2
code/applications/herbivores/03_herbivores_analysis.qmd
View file

@ -31,7 +31,7 @@ Les clustering donne le critère suivant :
vec_bicl <- sapply(list_clustering, function(clustering) {
list_collection <- readRDS(clustering)
unlisted_best_partition <- unlist(
extract_best_bipartite_partition(list_collection)
extract_best_partition(list_collection)
)
BICL <- sum(sapply(unlisted_best_partition, function(col) col$BICL))
BICL

2
code/applications/utils.R
View file

@ -50,7 +50,7 @@ build_graph_size_dataframe <- function(collection_list) {
}
extract_clustering <- function(clustering) {
partition <- colSBM::extract_best_bipartite_partition(
partition <- colSBM::extract_best_partition(
l = clustering,
unnest = TRUE
)

2
code/simulations/clustering/02_synthetic_clustering_analysis.qmd
View file

@ -41,7 +41,7 @@ Les clustering donne le critère suivant :
vec_bicl <- sapply(list_clustering, function(clustering) {
list_collection <- readRDS(clustering)
unlisted_best_partition <- unlist(
extract_best_bipartite_partition(list_collection)
extract_best_partition(list_collection)
)
BICL <- sum(sapply(unlisted_best_partition, function(col) col$BICL))
BICL

2
code/simulations/simulations_network_clustering.R
View file

@ -198,7 +198,7 @@ results <- bettermc::mclapply(seq_len(nrow(conditions)), function(s) {
silent_parallelization = TRUE
)
best_partitions <- unlist(extract_best_bipartite_partition(list_collection))
best_partitions <- unlist( extract_best_partition(list_collection))
if (!is(best_partitions, "list")) {
best_partitions <- list(best_partitions)
}