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10.6 kB
| """Build the combined IRexp release (v4 IR-attachment fix + 2026 SI expansion) with strict structure tiers. | |
| Inputs are the final local artifacts; nothing is fetched. Output: ../data (chmod 600).""" | |
| import gzip,json,os,re,collections,hashlib | |
| from rdkit import Chem, RDLogger; RDLogger.DisableLog('rdApp.*') | |
| import selfies as sf | |
| OUT='/workspace/irexp_release_237k/data/' | |
| V4R='/workspace/irexp_v4_build/release/data/' | |
| V4T='/workspace/irexp_growth/RESOLVE_237k/work/v4_tiers_final.jsonl.gz' | |
| SIH='/workspace/irexp_growth/harvest/out/' | |
| SIT='/workspace/irexp_growth/audit_rudra/new_tiers_final.jsonl' | |
| SIS='/workspace/irexp_growth/structures/' | |
| BENCH=set(json.load(open('/workspace/irexp_v4_build/work/bench_ik14.json'))) | |
| LIC={'CC BY':'CC-BY','CC BY-NC':'CC-BY-NC','CC BY-NC-ND':'CC-BY-NC-ND','CC BY-NC-SA':'CC-BY-NC-SA','CC BY-SA':'CC-BY-SA','CC0':'CC0'} | |
| def mol_fields(smi): | |
| m=Chem.MolFromSmiles(smi) if smi else None | |
| if m is None: return None | |
| can=Chem.MolToSmiles(m) | |
| try: s=sf.encoder(can) | |
| except Exception: s=None | |
| return dict(smiles=can,inchikey=Chem.MolToInchiKey(m),selfies=s,_mol=m) | |
| import sys as _sys | |
| _sys.path.insert(0,'/workspace/irexp_v4_build/spectro-agent'); _sys.path.insert(0,'/workspace/irexp_v4_build/spectro-agent/scripts') | |
| from quarantine_structure_nmr import gate_record as _gate_record | |
| def nmr_check(m,h,c): | |
| """spectro-agent scripts/quarantine_structure_nmr.py gate_record (same rules as the 2026-08-26 quarantine).""" | |
| return [x for x in _gate_record({'smiles':Chem.MolToSmiles(m),'h_nmr':h,'c_nmr':c,'ir_bands_cm-1':[]}) if x!='no_smiles'] | |
| def bands_ok(b): | |
| return all(350<=float(x)<=4000 for x in b) | |
| pools=collections.defaultdict(list); quar=[]; stats=collections.Counter(); tiers=collections.Counter(); tiers_pool=collections.Counter() | |
| # ---------- v4 rows ---------- | |
| T={} | |
| for l in gzip.open(V4T,'rt'): | |
| d=json.loads(l); T[d['id']]=d | |
| for f,pool in [('irexp_commercial','commercial'),('irexp_non_commercial','non_commercial'),('irexp_sharealike','sharealike'),('irexp_other','other')]: | |
| for l in gzip.open(V4R+f+'.jsonl.gz','rt'): | |
| d=json.loads(l); t=T[d['id']]; tier=t['tier_final'] | |
| d['source_set']='pmc_v4' if pool!='sharealike' or d.get('pmcid') else 'chemotion' | |
| if pool=='sharealike' and d.get('source'): d['source_set']='chemotion' if 'hemotion' in str(d.get('source')) else 'pmc_v4' | |
| flags=[] | |
| if t.get('formula_conflict'): flags.append('formula_conflict') | |
| if t.get('pubchem_conflict'): flags.append('pubchem_conflict') | |
| mf=None | |
| if tier in 'ABCD' and t.get('smiles'): | |
| mf=mol_fields(t['smiles']) | |
| if mf is None: stats['v4_unparseable']+=1; tier='none' | |
| if tier=='X': | |
| if d.get('smiles'): stats['v4_x_structure_removed_'+pool]+=1 | |
| quar.append(dict(id=d['id'],license_pool=pool,source_set=d['source_set'],reasons=['tier_X:'+(t.get('x_reason') or t.get('base_why') or 'contradiction')])) | |
| if mf: | |
| if d.get('smiles') and Chem.MolToSmiles(Chem.MolFromSmiles(d['smiles']))==mf['smiles'] and d.get('selfies'): | |
| mf['selfies']=d['selfies'] | |
| if not d.get('smiles'): stats['v4_structure_added_'+pool]+=1 | |
| d.update(smiles=mf['smiles'],inchikey=mf['inchikey'],selfies=mf['selfies'],has_structure=True) | |
| else: | |
| d.update(smiles=None,inchikey=None,selfies=None,has_structure=False) | |
| d['structure_tier']=tier if tier in 'ABCD' else ('X' if tier=='X' else None) | |
| d['structure_method']=(('ocsr:'+str(t['src_ocsr'].get('method'))) if t.get('src_ocsr') else t.get('method')) if mf else None | |
| d['formula_match']=t.get('fm') if mf else None | |
| d['structure_second_method']=('pubchem' if t.get('a_strict') else None) if tier=='A' else None | |
| d['structure_flags']=flags | |
| if mf: | |
| q=nmr_check(mf['_mol'],d.get('h_nmr'),d.get('c_nmr')) | |
| if q: quar.append(dict(id=d['id'],license_pool=pool,source_set=d['source_set'],inchikey=mf['inchikey'],reasons=q)) | |
| tiers[d['structure_tier'] or 'none']+=1; tiers_pool[(pool,d['structure_tier'] or 'none')]+=1 | |
| pools[pool].append(d) | |
| stats['v4_rows']=sum(len(v) for v in pools.values()) | |
| # ---------- SI expansion ---------- | |
| NT={} | |
| for l in open(SIT): | |
| d=json.loads(l); NT[d['id']]=d | |
| SFL={} | |
| for f in ['structures_commercial.jsonl.gz','structures_non_commercial.jsonl.gz']: | |
| for l in gzip.open(SIS+f,'rt'): | |
| r=json.loads(l); SFL[r['id']]=r.get('ir_flags') or [] | |
| nsi=0 | |
| for p in ['commercial','non_commercial']: | |
| for l in gzip.open(SIH+f'irexp_si_{p}.jsonl.gz','rt'): | |
| s=json.loads(l); nsi+=1; t=NT[s['id']]; tier=t['tier'] | |
| b0=s['ir_bands_cm-1']; seenb=set(); nb=[] | |
| for x in b0: | |
| k=int(round(float(x))) | |
| if k not in seenb: seenb.add(k); nb.append(x) | |
| if len(nb)!=len(b0): stats['si_dup_int_band_rows_'+p]+=1 | |
| if len(nb)<3: stats['si_dropped_lt3_after_dedup_'+p]+=1; continue | |
| lic=LIC.get(s['license'],s['license']) | |
| d=dict(id=s['id'],**{'ir_bands_cm-1':nb,'ir_bands_old_cm-1':b0},ir_source=s['ir_source'],h_nmr=s.get('h_nmr'),c_nmr=s.get('c_nmr'), | |
| smiles=None,selfies=None,inchikey=None,has_structure=False,source_doi='PMC:'+s['pmcid'][3:],license=lic,license_raw=s['license'], | |
| license_pool=p,license_source='pmc_oa_s3',pmcid=s['pmcid'],doi=s.get('doi'),source_set='si_2026',si_label=s.get('label'),si_name=s.get('name'), | |
| ir_raw=s.get('ir'),parser=s.get('parser'),ir_shared_in_paper=False,ir_table_flatten_suspect=None,ir_refetch_confirmed=False,ir_refetch_merged=False) | |
| mf=None | |
| if tier in ('A','B','C','D') and t.get('smiles'): | |
| mf=mol_fields(t['smiles']) | |
| if mf is None: stats['si_unparseable']+=1; tier='none' | |
| if mf: | |
| d.update(smiles=mf['smiles'],inchikey=mf['inchikey'],selfies=mf['selfies'],has_structure=True) | |
| q=nmr_check(mf['_mol'],d.get('h_nmr'),d.get('c_nmr')) | |
| if q: quar.append(dict(id=d['id'],license_pool=p,source_set='si_2026',inchikey=mf['inchikey'],reasons=q)) | |
| if tier=='X': quar.append(dict(id=d['id'],license_pool=p,source_set='si_2026',reasons=['tier_X:'+(t.get('x_reason') or 'contradiction')])) | |
| d['structure_tier']=tier if tier in ('A','B','C','D','X') else None | |
| meth=t.get('method') | |
| if t.get('src')=='ocsr': meth='ocsr:'+str(meth) | |
| d['structure_method']=meth if mf else None | |
| d['formula_match']=t.get('formula_match') if mf else None | |
| sm=[c for c in t.get('confirm',[]) if 'DISAGREES' not in c] | |
| d['structure_second_method']=('; '.join(sm) or None) if d['structure_tier']=='A' else None | |
| fl=list(SFL.get(s['id'],[])) | |
| if any('DISAGREES' in c for c in t.get('confirm',[])): fl.append('pubchem_conflict') | |
| d['structure_flags']=fl | |
| tiers[d['structure_tier'] or 'none']+=1; tiers_pool[(p,d['structure_tier'] or 'none')]+=1 | |
| pools[p].append(d) | |
| stats['si_rows_in']=nsi | |
| grp=collections.Counter((r['pmcid'],tuple(int(round(float(x))) for x in r['ir_bands_cm-1'])) for p in ('commercial','non_commercial') for r in pools[p] if r['source_set']=='si_2026') | |
| for p in ('commercial','non_commercial'): | |
| for r in pools[p]: | |
| if r['source_set']=='si_2026' and grp[(r['pmcid'],tuple(int(round(float(x))) for x in r['ir_bands_cm-1']))]>1: r['ir_shared_in_paper']=True; stats['si_ir_shared_in_paper']+=1 | |
| stats['si_rows_out']=sum(1 for p in ('commercial','non_commercial') for r in pools[p] if r['source_set']=='si_2026') | |
| # ---------- write ---------- | |
| def w(name,rows): | |
| path=OUT+name | |
| with gzip.open(path,'wt',compresslevel=9) as g: | |
| for r in rows: g.write(json.dumps(r,ensure_ascii=False)+'\n') | |
| os.chmod(path,0o600); return len(rows) | |
| counts={} | |
| counts['commercial']=w('irexp_commercial.jsonl.gz',pools['commercial']) | |
| res=[r for r in pools['commercial'] if r['has_structure']] | |
| counts['resolved_commercial']=w('irexp_resolved_commercial.jsonl.gz',res) | |
| tnb=[r for r in res if r['inchikey'][:14] not in BENCH] | |
| counts['train_no_bench_commercial']=w('train_no_bench_commercial.jsonl.gz',tnb) | |
| counts['non_commercial']=w('irexp_non_commercial.jsonl.gz',pools['non_commercial']) | |
| counts['sharealike']=w('irexp_sharealike.jsonl.gz',pools['sharealike']) | |
| counts['other']=w('irexp_other.jsonl.gz',pools['other']) | |
| counts['structure_quarantine']=w('structure_quarantine.jsonl.gz',quar) | |
| # seen papers: v4 list + SI list | |
| seen=set(l.strip() for l in gzip.open('/workspace/irexp_v4_build/IRexp/data/seen_papers.txt.gz','rt') if l.strip()) | |
| n4=len(seen); seen|=set(l.strip() for l in open('/workspace/irexp_growth/harvest/seen_papers_si.txt') if l.strip()) | |
| with gzip.open(OUT+'seen_papers.txt.gz','wt') as g: g.write('\n'.join(sorted(seen))+'\n') | |
| os.chmod(OUT+'seen_papers.txt.gz',0o600) | |
| def agg(rows): | |
| st=[r for r in rows if r['has_structure']] | |
| return dict(records=len(rows),structure_linked=len(st),unique_inchikey=len({r['inchikey'] for r in st}), | |
| bands=sum(len(r['ir_bands_cm-1']) for r in rows),papers=len({r.get('pmcid') or r.get('source_doi') for r in rows}), | |
| tiers=dict(collections.Counter(r['structure_tier'] or 'none' for r in rows)), | |
| by_set=dict(collections.Counter(r['source_set'] for r in rows)), | |
| full_quadruple=sum(1 for r in st if r.get('h_nmr') and r.get('c_nmr')), | |
| lt3=sum(1 for r in rows if len(r['ir_bands_cm-1'])<3), | |
| band_out_of_range=sum(1 for r in rows if not bands_ok(r['ir_bands_cm-1']))) | |
| # research corpus (incl. empty/unknown licence pool, not redistributed) | |
| rc=collections.Counter(); | |
| for l in gzip.open(V4T,'rt'): rc[json.loads(l)['tier_final']]+=1 | |
| for d in NT.values(): rc[d['tier'] or 'none']+=1 | |
| N=sum(rc.values()) | |
| rep=dict(counts=counts,files={k:agg(v) for k,v in pools.items()},resolved_commercial=agg(res),train_no_bench_commercial=agg(tnb), | |
| released_total=sum(len(v) for v in pools.values()), | |
| research_corpus=dict(n=N,tiers=dict(rc),AB=rc['A']+rc['B'],AB_pct=round(100*(rc['A']+rc['B'])/N,2),AD=sum(rc[k] for k in 'ABCD'),AD_pct=round(100*sum(rc[k] for k in 'ABCD')/N,2)), | |
| released_tiers=dict(tiers),tiers_by_pool={'%s/%s'%k:v for k,v in sorted(tiers_pool.items())}, | |
| stats=dict(stats),seen_papers=dict(v4=n4,total=len(seen)),quarantine_reasons=dict(collections.Counter(r['reasons'][0].split(':')[0] for r in quar)), | |
| benchmark_ik14=len(BENCH)) | |
| json.dump(rep,open(OUT+'irexp_release_build_stats.json','w'),indent=1); os.chmod(OUT+'irexp_release_build_stats.json',0o600) | |
| print(json.dumps(rep,indent=1)) | |