"""LT1 · 31 · cotejo impl1 (DuckDB) frente a impl2 (pandas) (DEFINICIONES_PREVIAS §6)."""
import json, math
V1 = json.load(open('/w/interno/impl1_celdas.json')); V2 = json.load(open('/w/interno/impl2_celdas.json'))
E1 = {f"{r['norma']}|{r['serie']}|{r['grupo']}": r for r in json.load(open('/w/salidas/20_eventos.json')) if 'POSTERIOR' not in r.get('nota', '')}
E2 = json.load(open('/w/salidas/30_impl2.json'))
out = {'celdas': {}, 'puntuales': {}}
tot = ig = 0
for k in V2:
    for arm in V2[k]:
        a1, a2 = V1[k][arm], V2[k][arm]
        orgs = set(a1) | set(a2); dif = 0
        for o in orgs:
            tot += 1
            if o in a1 and o in a2 and all(abs(x - y) < 1e-6 for x, y in zip(a1[o][0] + a1[o][1], a2[o][0] + a2[o][1])): ig += 1
            else: dif += 1
        out['celdas'][f'{k}|{arm}'] = dict(organos_impl1=len(a1), organos_impl2=len(a2), organos_con_diferencias=dif)
for k, r2 in E2.items():
    r1 = E1[k]; K1 = r1['K']
    def ok(a, b): return abs(a - b) <= 0.005 or abs(a - b) <= 0.005 * abs(a)
    out['puntuales'][k] = dict(delta_impl1=r1['delta'], delta_impl2=r2['delta'], K_impl1=K1, K_impl2=r2['K'],
                               n_T=(r1['n_org_T'], r2['n_T']), coincide=ok(r1['delta'], r2['delta']) and ok(K1, r2['K']) and r1['n_org_T'] == r2['n_T'])
out['organo_ventana_iguales'] = f'{ig}/{tot}'; out['pct'] = 100 * ig / tot
out['veredicto'] = 'PASA' if ig / tot >= 0.995 and all(v['coincide'] for v in out['puntuales'].values()) else 'NO PASA'
json.dump(out, open('/w/salidas/31_cotejo_impl2.json', 'w'), indent=1, ensure_ascii=False)
print(json.dumps(out, indent=1, ensure_ascii=False))