| |
| """Deterministically export existing scientific records as Hub-viewable JSONL.""" |
| import json |
| from pathlib import Path |
|
|
| ROOT=Path(__file__).resolve().parent.parent |
| V=ROOT/'verification' |
| GROUPS=[ |
| ('verification_results.json','fixed_contraction_cases','balanced_half', '1.3'), |
| ('verification_results.json','general_rho_cases','balanced_general_rho','1.3'), |
| ('verification_results.json','markov_and_spd_cases','stochastic_and_spd','15.1'), |
| ('broadening_verification_results.json','scalar_cases','scalar_exact_hitting','1.2'), |
| ('broadening_verification_results.json','approximation_cases','scalar_additive','6.1'), |
| ('revision3_scalar_verification_results.json','direct_recurrence_cases','sentinel_recurrence','3.2'), |
| ('revision3_scalar_verification_results.json','partition_cases','sentinel_partition','3.3'), |
| ('revision3_fluid_verification_results.json','cases','one_interruption','9.3'), |
| ('revision3_observable_results.json','assignment_cases','observable_rank','7.1'), |
| ('revision3_observable_results.json','quotient_cases','observable_quotient','8.1'), |
| ] |
| SUITES=[ |
| ('original','verification_results.json','verify_nhairun.py'), |
| ('scalar_matching','broadening_verification_results.json','verify_broadening.py'), |
| ('sentinel','revision3_scalar_verification_results.json','verify_revision3_scalar.py'), |
| ('markers','revision3_marker_results.json','verify_revision3_markers.py'), |
| ('one_interruption','revision3_fluid_verification_results.json','verify_revision3_fluid.py'), |
| ('observable','revision3_observable_results.json','verify_revision3_observable.py'), |
| ] |
|
|
| def load(name):return json.loads((V/name).read_text(encoding='utf-8')) |
| def packed(value):return json.dumps(value,ensure_ascii=False,sort_keys=True,separators=(',',':')) |
| def has_float(value): |
| if isinstance(value,float):return True |
| if isinstance(value,dict):return any(has_float(v) for v in value.values()) |
| if isinstance(value,list):return any(has_float(v) for v in value) |
| return False |
| def integer(case,*keys): |
| for key in keys: |
| if key in case and isinstance(case[key],int) and not isinstance(case[key],bool):return case[key] |
| return -1 |
|
|
| def rows(): |
| ledger=load('claim_ledger.json') |
| claims=[dict(claim_id=c['id'],status=c['status'],statement=c['statement'], |
| assumptions=c.get('assumptions',[]),limitations=c.get('limits',[]), |
| supporting_code=c.get('code',[]),record_json=packed(c)) for c in ledger['claims']] |
| cases=[] |
| for filename,key,family,theorem in GROUPS: |
| for index,c in enumerate(load(filename)[key]): |
| count=integer(c,'requests','size','N') |
| if count<0 and 'centers' in c:count=len(c['centers']) |
| if count<0 and 'original_centers' in c:count=len(c['original_centers'])+3 |
| if count<0 and 'values' in c:count=(2*len(c['values'])+3 if family=='sentinel_partition' else 2*len(c['values'])) |
| cases.append(dict(case_id=f'{family}-{index:03d}',family=family, |
| theorem_reference=theorem,source_record='verification/'+filename, |
| source_collection=key,source_index=index,request_count=count, |
| state_dimension=integer(c,'hidden_dimension','dimension','ambient_dimension'), |
| observed_dimension=integer(c,'observed_dimension'),variation_rank=integer(c,'variation_rank'), |
| rho=str(c.get('rho',c.get('contraction',''))), |
| orders_checked=integer(c,'orders','orders_enumerated','unsplit_orders','distinct_matrix_orders'), |
| contains_float_diagnostics=has_float(c),case_json=packed(c))) |
| audits=[] |
| for suite,filename,script in SUITES: |
| d=load(filename) |
| audits.append(dict(suite_id=suite,source_record='verification/'+filename, |
| verifier='code/'+script,assertions_count=d.get('assertions_total',0), |
| placements_checked=d.get('ordered_distinct_sentinel_placements',0), |
| scope=d.get('scope','Finite implementation checks; all-instance claims rely on manuscript proofs.'), |
| arithmetic=d.get('arithmetic','Exact integer marker identities'), |
| details_json=packed({k:v for k,v in d.items() if not isinstance(v,list)}))) |
| return {'claims':claims,'cases':cases,'verification_suites':audits} |
|
|
| def main(): |
| data=rows();destination=ROOT/'data';destination.mkdir(exist_ok=True) |
| for name,records in data.items(): |
| (destination/(name+'.jsonl')).write_text(''.join(packed(r)+'\n' for r in records),encoding='utf-8') |
| stats={name:len(records) for name,records in data.items()} |
| stats.update(assertions_total=sum(r['assertions_count'] for r in data['verification_suites']), |
| separate_marker_placements=sum(r['placements_checked'] for r in data['verification_suites'])) |
| (ROOT/'metadata'/'dataset_summary.json').write_text(json.dumps(stats,indent=2)+'\n',encoding='utf-8') |
| print(json.dumps(stats,indent=2)) |
|
|
| if __name__=='__main__':main() |
|
|
