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9126e0d | 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 | """Recompute the published scene-bootstrap summaries from archived records.
This replay uses the stored fitted decisions. It does not refit calibration or
modify the original results. Run analyze.py after a fresh GPU inference campaign
to repeat fitting, calibration and evaluation from frozen-map measurements.
"""
from pathlib import Path
import json,gzip
import numpy as np
from analyze import summarize
R=Path(__file__).resolve().parents[1];A=R/'results/analysis'
def main():
published=json.loads((A/'summary.json').read_text());report=[]
for model in ['clipseg','groundedsam']:
rows=[json.loads(l) for l in gzip.open(A/(model+'_evaluated.jsonl.gz'),'rt')]
expected=[r for r in published if r['model']==model];methods=list(dict.fromkeys(r['method'] for r in expected))
observed=summarize(rows,methods);index={(r['population'],r['metric'],r['method']):r for r in expected};maxdiff=0.
for r in observed:
old=index[(r['population'],r['metric'],r['method'])]
for k in ['estimate','lo','hi','gain','gain_lo','gain_hi']:
diff=abs(r[k]-old[k]);maxdiff=max(maxdiff,diff);assert diff<1e-12,(model,k,diff)
assert r['clusters']==old['clusters'] and r['units']==old['units']
assert len(observed)==len(expected)
report.append({'model':model,'records':len(rows),'summary_rows':len(observed),'maximum_absolute_difference':maxdiff})
out=R/'build/replay_verification.json';out.parent.mkdir(exist_ok=True);out.write_text(json.dumps(report,indent=2));print(json.dumps(report,indent=2))
if __name__=='__main__':main()
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