File size: 4,663 Bytes
1263695 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | #!/usr/bin/env python3
"""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()
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