Using autosave
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1 changed files with 12 additions and 12 deletions
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@ -32,18 +32,19 @@ switch(mode,
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adj = per_taxa_networks[[2]], # Account for the root
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adj = per_taxa_networks[[2]], # Account for the root
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verbosity = 6,
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verbosity = 6,
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plotting = "",
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plotting = "",
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autosave = here(tmp_folder, "r2_seq.Rds"),
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ncores = 1L
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ncores = 1L
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)
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)
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r2_model_seq$estimate()
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r2_model_seq$estimate()
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}, times = 3L)
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}, times = 3L)
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r3_mbm_seq <- microbenchmark("Rank3seq" = {
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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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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, autosave = here(tmp_folder, "r3_seq.Rds"))
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}, times = 3L)
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}, times = 3L)
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r4_mbm_seq <- microbenchmark("Rank4seq" = {
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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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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, autosave = here(tmp_folder, "r4_seq.Rds"))
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}, times = 3L)
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}, times = 3L)
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r5_mbm_seq <- microbenchmark("Rank5seq" = {
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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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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, autosave = here(tmp_folder, "r5_seq.Rds"))
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}, times = 3L)
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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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mbm_seq <- rbind(r2_mbm_seq, r3_mbm_seq, r4_mbm_seq, r5_mbm_seq)
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@ -68,18 +69,18 @@ switch(mode,
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adj = per_taxa_networks[[2]], # Account for the root
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adj = per_taxa_networks[[2]], # Account for the root
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verbosity = 6,
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verbosity = 6,
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plotting = "",
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plotting = "",
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ncores = parallelly::availableCores()
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ncores = parallelly::availableCores(), autosave = here(tmp_folder, "r2_para.Rds")
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)
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)
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r2_model_para$estimate()
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r2_model_para$estimate()
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}, times = 3L)
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}, times = 3L)
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r3_mbm_para <- microbenchmark("Rank3para" = {
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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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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(), autosave = here(tmp_folder, "r3_para.Rds"))
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}, times = 3L)
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}, times = 3L)
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r4_mbm_para <- microbenchmark("Rank4para" = {
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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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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(), autosave = here(tmp_folder, "r4_para.Rds"))
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}, times = 3L)
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}, times = 3L)
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r5_mbm_para <- microbenchmark("Rank5para" = {
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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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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(), autosave = here(tmp_folder, "r5_para.Rds"))
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}, times = 3L)
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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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mbm_para <- rbind(r2_mbm_para, r3_mbm_para, r4_mbm_para, r5_mbm_para)
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@ -101,8 +102,7 @@ switch(mode,
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membership_type = "LBM",
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membership_type = "LBM",
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adj = per_taxa_networks[[2]], # Account for the root
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adj = per_taxa_networks[[2]], # Account for the root
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verbosity = 6,
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verbosity = 6,
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plotting = "",
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ncores = parallelly::availableCores(), autosave = here(tmp_folder, "r2_notrans.Rds")
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ncores = parallelly::availableCores()
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)
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)
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r2_model_notrans$estimate()
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r2_model_notrans$estimate()
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}, times = 3L)
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}, times = 3L)
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@ -112,7 +112,7 @@ switch(mode,
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adj = per_taxa_networks[[3]], # Account for the root
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adj = per_taxa_networks[[3]], # Account for the root
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verbosity = 6,
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verbosity = 6,
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plotting = "",
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plotting = "",
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ncores = parallelly::availableCores()
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ncores = parallelly::availableCores(), autosave = here(tmp_folder, "r3_notrans.Rds")
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)
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)
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r3_model_notrans$estimate()
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r3_model_notrans$estimate()
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}, times = 3L)
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}, times = 3L)
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@ -122,7 +122,7 @@ switch(mode,
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adj = per_taxa_networks[[4]], # Account for the root
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adj = per_taxa_networks[[4]], # Account for the root
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verbosity = 6,
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verbosity = 6,
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plotting = "",
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plotting = "",
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ncores = parallelly::availableCores()
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ncores = parallelly::availableCores(), autosave = here(tmp_folder, "r4_notrans.Rds")
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)
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)
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r4_model_notrans$estimate()
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r4_model_notrans$estimate()
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}, times = 3L)
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}, times = 3L)
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@ -132,7 +132,7 @@ switch(mode,
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adj = per_taxa_networks[[5]], # Account for the root
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adj = per_taxa_networks[[5]], # Account for the root
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verbosity = 6,
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verbosity = 6,
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plotting = "",
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plotting = "",
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ncores = parallelly::availableCores()
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ncores = parallelly::availableCores(), autosave = here(tmp_folder, "r5_notrans.Rds")
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)
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)
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r5_model_notrans$estimate()
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r5_model_notrans$estimate()
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}, times = 3L)
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}, times = 3L)
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