Source identity
| Field | Recorded value |
|---|---|
| Source type | archive member |
| Original record | diagnostic_unnormalized.py |
| Date | Not specified in source |
| Path or archive member | archives/libsrc-ef5e6c3ea329/quantum_mip_benchmark/code/diagnostic_unnormalized.py |
| Original SHA-256 | c0b77fc5783706397a392b3b48532c44047121e70f2aafbf40f2317a4502f678 |
| Reading-copy SHA-256 | c0b77fc5783706397a392b3b48532c44047121e70f2aafbf40f2317a4502f678 |
| Archive source | {"sourceId": "libsrc-ef5e6c3ea329", "member": "quantum_mip_benchmark/code/diagnostic_unnormalized.py"} |
Recovered source transcript
Download complete source text ↓27 lines · 1.4 KB
#!/usr/bin/env python3
"""Post-run diagnostic, explicitly separate from the frozen main protocol."""
import os
os.environ['OPENBLAS_NUM_THREADS']='1'
import json
from pathlib import Path
import numpy as np
from benchmark import queyranne
root=Path(__file__).resolve().parents[1]
rows=[]
for p in sorted((root/'results').glob('n*.json')):
r=json.loads(p.read_text());d=np.load(root/'data'/f'{r["instance"]}.npz',allow_pickle=False)
n=r['n'];full=(1<<n)-1
def f(mask):
if not mask&1:mask=full^mask
return 0.0 if mask==full else float(d['Phi_SI'][mask>>1])
m,val=queyranne(n,f);star=float(d['Phi_SI'].min());eps=1e-10+1e-8*star
rows.append({'instance':r['instance'],'unnormalized_Queyranne_hit':val<=star+eps,
'unnormalized_Queyranne_phi':val,'unnormalized_exact_phi':star,
'unnormalized_Queyranne_z':m>>1,'unnormalized_exact_z':int(d['Phi_SI'].argmin()),
'normalization_changes_MIP':int(d['Phi_SI'].argmin())!=r['exact_z']})
out={'status':'post-run diagnostic, not part of frozen primary protocol','results':rows,
'unnormalized_Queyranne_hits':sum(x['unnormalized_Queyranne_hit'] for x in rows),
'normalization_changes_MIP_count':sum(x['normalization_changes_MIP'] for x in rows)}
(root/'validation/unnormalized_diagnostic.json').write_text(json.dumps(out,indent=2)+'\n')
print(out['unnormalized_Queyranne_hits'],out['normalization_changes_MIP_count'])