Files
obikmer/benchmark/make_deps.py
T
Eric Coissac 89ea077456 Add benchmark pipeline for dense and sparse query testing
Introduces a complete query benchmark track to evaluate performance and verify consistency between dense and sparse index formats. Adds scripts to simulate fixed-size paired-end reads, pack a sparse presence index, execute queries in both modes, and capture wall time and RSS metrics. Includes a verification step that compares outputs by read ID to ensure content identity across parallel processing. Updates build configuration, documentation, and ignore patterns to support the new pipeline for two microbial specimens.
2026-08-20 13:59:12 +02:00

145 lines
4.9 KiB
Python

#!/usr/bin/env python3
"""Generate deps.mk — pure dependency declarations for the benchmark pipeline.
Like C .d files: only target: prerequisites lines, no recipes.
Recipes stay in the Makefile as generic rules.
"""
import gzip
import re
import sys
from pathlib import Path
STOP_WORDS = {'complete', 'chromosome', 'whole', 'sequence', 'genome',
'endosymbiont', 'of'}
STOP_PREFIXES = ('scaffold', 'contig', 'plasmid')
# Specimens used as read sources for the query benchmark (see
# DevDocMD/implementation/benchmark_query_testing.md): one common bacterium,
# one distant lineage (the only archaeon in SPECIES).
QUERY_SPECIMENS = ['Escherichia_coli--K-12_MG1655', 'Saccharolobus_islandicus--M.16.4']
def is_stop(tok):
t = tok.lower()
return t in STOP_WORDS or any(t.startswith(p) for p in STOP_PREFIXES)
def sanitize(s):
return re.sub(r'[^A-Za-z0-9._-]', '_', s).strip('_')
def collect_tokens(text):
parts = []
for tok in text.split():
tok = tok.rstrip(',.')
if is_stop(tok):
break
parts.append(sanitize(tok))
return '_'.join(filter(None, parts))
def parse_organism(defn, gcf_id):
words = defn.split()
species = sanitize(words[0] + '_' + words[1])
m = re.search(r'\bstr\.\s+(\S+)(?:\s+substr\.\s+(\S+))?', defn)
if m:
strain = sanitize(m.group(1))
if m.group(2):
strain += '_' + sanitize(m.group(2))
return species, strain
m = re.search(r'\bstrain\b\s+(.*)', defn)
if m:
strain = collect_tokens(m.group(1))
if strain:
return species, strain
remainder = re.sub(r'^\S+ \S+\s*', '', defn)
remainder = re.sub(r'^subsp\.\s+\S+\s*', '', remainder)
remainder = re.sub(r'^serovar\s+\S+\s*', '', remainder)
strain = collect_tokens(remainder)
return species, strain if strain else gcf_id
def first_definition(path):
with gzip.open(path, 'rt') as fh:
for line in fh:
if line.startswith('>'):
m = re.search(r'"definition":"([^"]*)"', line)
return m.group(1) if m else line[1:].split()[0]
return Path(path).stem
def main():
entries = [] # (specimen, species, sim_dir, genome_path)
species_seen = []
for path in sorted(sys.argv[1:]):
gcf_id = Path(path).name.replace('_genomic.fna.gz', '')
defn = first_definition(path)
sp, st = parse_organism(defn, gcf_id)
specimen = f'{sp}--{st}'
sim_dir = f'simulated_data/{sp}/{st}'
entries.append((specimen, sp, sim_dir, path))
if sp not in species_seen:
species_seen.append(sp)
specimens = [e[0] for e in entries]
print('SPECIMENS :=', ' '.join(specimens))
print('SPECIES :=', ' '.join(species_seen))
for specimen, species, sim_dir, genome in entries:
reads = f'{sim_dir}/reads_R1.fastq.gz'
p_done = f'specimen_index_presence/{specimen}/index.done'
p_stats = f'stats/indexing_presence/{specimen}.stats'
c_done = f'specimen_index_count/{specimen}/index.done'
c_stats = f'stats/indexing_count/{specimen}.stats'
ref = f'reference_index/{specimen}.npz'
vp = f'stats/verify_presence/{specimen}.stats'
vc = f'stats/verify_count/{specimen}.stats'
print()
print(f'# {specimen}')
print(f'{reads}: {genome}')
print(f'{ref}: {reads}')
print(f'{p_done} {p_stats}: {reads}')
print(f'{c_done} {c_stats}: {reads}')
print(f'{vp}: {ref} {p_done}')
print(f'{vc}: {ref} {c_done}')
print()
for sp in species_seen:
sp_done = f'specific_index_presence/{sp}/index.done'
sp_stats = f'stats/specific_kmer_presence/{sp}.stats'
sc_done = f'specific_index_count/{sp}/index.done'
sc_stats = f'stats/specific_kmer_count/{sp}.stats'
print(f'# {sp}')
print(f'{sp_done} {sp_stats}: global_index_presence/index.done')
print(f'{sc_done} {sc_stats}: global_index_count/index.done')
print()
print('QUERY_SPECIMENS :=', ' '.join(QUERY_SPECIMENS))
by_specimen = {e[0]: e for e in entries}
for specimen in QUERY_SPECIMENS:
_, species, sim_dir, genome = by_specimen[specimen]
query_dir = sim_dir.replace('simulated_data/', 'query_data/', 1)
reads = f'{query_dir}/reads_R1.fastq.gz'
dense_out = f'query_dense/{specimen}.fasta.gz'
dense_stat = f'stats/query_dense/{specimen}.stats'
sparse_out = f'query_sparse/{specimen}.fasta.gz'
sparse_stat = f'stats/query_sparse/{specimen}.stats'
vq_stat = f'stats/verify_query/{specimen}.stats'
print()
print(f'# query: {specimen}')
print(f'{reads}: {genome}')
print(f'{dense_out} {dense_stat}: {reads} global_index_presence/index.done')
print(f'{sparse_out} {sparse_stat}: {reads} global_index_presence_sparse/index.done')
print(f'{vq_stat}: {dense_out} {sparse_out}')
if __name__ == '__main__':
main()