"""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))