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Fix parallelization in clustering (#31) #37

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Fix parallelization in clustering (#31) #37

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55 changes: 38 additions & 17 deletions COMEBin/cluster.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
from utils import get_length, calculateN50, save_result
from scripts.gen_bins_from_tsv import gen_bins as gen_bins_from_tsv
from typing import List, Optional, Union
from joblib import Parallel, delayed


logger = logging.getLogger('COMEBin')
Expand Down Expand Up @@ -309,6 +310,24 @@ def run_leiden(output_file: str, namelist: List[str],
f.write(namelist[contigIdx] + "\t" + str(contig_labels_dict[namelist[contigIdx]]) + "\n")
f.close()

ann_neighbor_indices = None
ann_distances = None
norm_embeddings = None

def set_shared_data(_ann_indices, _ann_distances, _norm_embeddings):
global ann_neighbor_indices, ann_distances, norm_embeddings
ann_neighbor_indices = _ann_indices
ann_distances = _ann_distances
norm_embeddings = _norm_embeddings

def run_leiden_wrapper(output_file, namelist, ann_neighbor_indices, ann_distances,
length_weight, max_edges, norm_embeddings,
bandwidth, initial_list, is_membership_fixed,
para, partgraph_ratio):
run_leiden(output_file, namelist, ann_neighbor_indices, ann_distances,
length_weight, max_edges, norm_embeddings,
bandwidth, 'l2', initial_list, is_membership_fixed,
para, partgraph_ratio)

def cluster(logger, args, prefix=None):
"""
Expand Down Expand Up @@ -378,8 +397,6 @@ def cluster(logger, args, prefix=None):
logger.info(k)
seed_kmeans_full(logger, contig_file, namelist, output_path, norm_embeddings, k, mode, length_weight, seed_file)

import multiprocessing

num_workers = args.num_threads


Expand All @@ -400,21 +417,25 @@ def cluster(logger, args, prefix=None):
time_end = time.time()
logger.info('knn query time cost:\t' +str(time_end - time_start) + "s")


with multiprocessing.Pool(num_workers) as multiprocess:
for partgraph_ratio in partgraph_ratio_list:
for bandwidth in bandwidth_list:
for para in parameter_list:
output_file = output_path + 'Leiden_bandwidth_' + str(
bandwidth) + '_res_maxedges' + str(max_edges) + 'respara_'+str(para)+'_partgraph_ratio_'+str(partgraph_ratio)+'.tsv'

if not (os.path.exists(output_file)):
multiprocess.apply_async(run_leiden, (output_file, namelist, ann_neighbor_indices, ann_distances, length_weight, max_edges, norm_embeddings,
bandwidth, 'l2', initial_list,is_membership_fixed,
para, partgraph_ratio))

multiprocess.close()
multiprocess.join()
set_shared_data(ann_neighbor_indices, ann_distances, norm_embeddings)

tasks = []
for partgraph_ratio in partgraph_ratio_list:
for bandwidth in bandwidth_list:
for para in parameter_list:
output_file = (
output_path + f'Leiden_bandwidth_{bandwidth}_res_maxedges{max_edges}'
f'respara_{para}_partgraph_ratio_{partgraph_ratio}.tsv'
)
tasks.append((output_file, bandwidth, para, partgraph_ratio))

Parallel(n_jobs=num_workers, prefer="processes")(
delayed(run_leiden_wrapper)(output_file, namelist, ann_neighbor_indices, ann_distances,
length_weight, max_edges, norm_embeddings,
bandwidth, initial_list,is_membership_fixed,
para, partgraph_ratio)
for output_file, bandwidth, para, partgraph_ratio in tasks
)
logger.info('multiprocess Done')


Expand Down