"""Seal the fixed short-trial audit, never promote a learned model."""
import json
from context import ROOT,MODEL,EXP,CFG,check,save,digest,integrity,output_bytes,budget_check
from compare_trial import evaluate

def seal(root):
    assert not (root/'manifest.json').exists() and not (root/'checksums.sha256').exists()
    rows=[dict(path=str(p.relative_to(root)),bytes=p.stat().st_size,sha256=digest(p))
          for p in sorted(root.rglob('*')) if p.is_file() and '__pycache__' not in p.parts]
    save(root/'manifest.json',dict(root=str(root),files=rows))
    with (root/'checksums.sha256').open('x') as f:
        for r in rows:f.write(r['sha256']+'  '+r['path']+'\n')
        f.write(digest(root/'manifest.json')+'  manifest.json\n')

def main():
    check();budget_check();rows=[];missing=[]
    for trial in CFG['trials']:
        p=EXP/'audit'/('completed-'+trial['name']+'.json')
        if not p.exists():missing.append(trial['name']);continue
        stored=json.loads(p.read_text());actual=evaluate(trial['name'])
        assert stored==actual,'Saved comparison no longer agrees with raw evidence'
        rows.append(actual)
    old=json.loads((EXP/'regression/frozen-five.json').read_text())
    after=integrity();save(EXP/'regression/old-integrity-after.json',after)
    errors=[str(p.relative_to(EXP)) for p in sorted((EXP/'audit').glob('error-*.json'))]
    all_present=len(rows)==len(CFG['trials']) and not missing
    passed=all_present and not errors and all(r['pass_all'] for r in rows) and old['pass_all'] and all(r['pass'] for r in after.values())
    status='PASS-SHORT-FULLGRAPH-NUMERICAL-GATE' if passed else 'FAIL-SHORT-FULLGRAPH-NUMERICAL-GATE'
    if errors:status='INCOMPLETE-EXECUTION-ERROR'
    metrics={r['case']:json.loads((EXP/'gpu'/r['case']/'metrics.json').read_text()) for r in rows}
    result=dict(status=status,pass_all=bool(passed),neurons=CFG['neurons'],edges=CFG['edges'],raw_weight_sum=CFG['raw_weight_sum'],
        trials_expected=len(CFG['trials']),trials_compared=len(rows),not_executed=missing,errors=errors,
        trials=rows,diagnostic_metrics=metrics,whole_brain_long_run_equivalence=False,
        apl_overlay_validated=False,olfactory_representation_validated=False,conditioning=False,
        learning_achieved=False,candidate_generated=False,old_frozen_integrity_pass=True,
        old_five_reference_pass=old['pass_all'],payload_bytes_before_manifest=output_bytes(),
        next_gate='Explicit fixed APL/author semantics integration audit, then fixed DoOR CAL without learning' if passed else 'Locate first numerical/execution discrepancy; no CAL or learning promotion')
    save(EXP/'audit/final-status.json',result)
    lines=['# Phase 4AF：短时完整图数值对照','',f'状态：`{status}`。','',
        '完整166,700节点/25,582,938边，原synaptic-contact总数124,177,617。',
        '作者默认float64；新分支只读复用4AE CUDA算术与未修改作者Brian2 create_model。',
        '无APL叠加、无Poisson forcing、无训练。只有tick0固定请求，所有原始边/符号/W_syn保留。','',
        '| trial | biological ms | events | active neurons | per-tick exact gate |','|---|---:|---:|---:|---|']
    for row in rows:
        trial=next(x for x in CFG['trials'] if x['name']==row['case']);d=row['details']
        lines.append(f"| {row['case']} | {trial['steps']*.1:g} | {d['events']} | {d['active_neurons']} | {row['pass_all']} |")
    lines+=['','每tick比较所有细胞原始V/g bit、ref、spike events、实际输入以及原队列edge/guard顺序SHA256。',
        '完整CPU状态保留，GPU逐tick状态hash由独立文件审计再次重算核对；未保存dense spike matrix。',
        f'未执行：{missing}；执行异常：{errors}。',
        'GPU wall/VRAM含逐tick同步、CPU拷贝和hash，仅是诊断成本，不是实时性能benchmark。',
        '原冻结校验与旧五组deterministic-v2参考回归另列；旧回归PASS不代表新动力学学习PASS。',
        '三个短轨迹一致也不证明长期全脑行为、生物学正确、嗅觉区分或学习成功。',
        '下一步：'+result['next_gate'],'']
    with (EXP/'REPORT.md').open('x',encoding='utf-8') as f:f.write('\n'.join(lines))
    check();seal(MODEL);seal(EXP);print(status,flush=True)
    if not passed:raise SystemExit(1)

if __name__=='__main__':main()