b6dd9ff1df
Snapshot des 18 JSONs produits par le pipeline V2 (Qwen2.5-VL-3B +
checkboxes densité + validation ATIH), utiles au collaborateur comme
référence de ce que la chaîne actuelle produit.
Rapports :
- bench_v2_report.md : comparaison V2 vs legacy docTR+VLM
(couverture, divergences, régressions
notables sur codage_reco et praticien).
- validation_report.md : résumé de la validation ATIH sur les 18
JSONs (131/149 → 140/149 codes valides
après fix suffixes `*` et `+N`, 0
incohérence GHM↔GHS, 8 suggestions de
correction OCR).
Script de comparaison :
- bench_v11_vs_legacy.py : tableau d'accord champ par champ entre
un run du pipeline (output/v2/) et les
JSONs legacy (output/).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
107 lines
3.7 KiB
Python
107 lines
3.7 KiB
Python
"""Comparaison systématique V1.1 vs legacy sur les 18 dossiers."""
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import json
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import os
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from pathlib import Path
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FIELDS_RECUEIL = [
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("etablissement", "etablissement"),
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("finess", "finess"),
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("date_debut_controle", "date_debut_controle"),
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("n_ogc", "n_ogc"),
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("n_champ", "n_champ"),
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("dates_sejour", "dates_sejour"),
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("codage_etab.dp", "codage_etab.dp"),
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("codage_etab.dp_libelle", "codage_etab.dp_libelle"),
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("codage_etab.dr", "codage_etab.dr"),
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("codage_reco.dp", "codage_reco.dp"),
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("ghm_etab", "ghm_etab"),
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("ghs_etab", "ghs_etab"),
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("ghm_reco", "ghm_reco"),
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("ghs_reco", "ghs_reco"),
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("recodage_impactant", "recodage_impactant"),
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("ghs_injustifie", "ghs_injustifie"),
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("accord_desaccord", "accord_desaccord"),
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("praticien_conseil", "praticien_conseil"),
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]
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def get(d, path):
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for k in path.split("."):
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d = d.get(k, "") if isinstance(d, dict) else ""
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return str(d).strip()
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def count_das(d, path):
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for k in path.split("."):
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d = d.get(k, []) if isinstance(d, dict) else []
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return len(d) if isinstance(d, list) else 0
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def load_pairs():
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pairs = []
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for f in sorted(Path("output").glob("OGC *.json")):
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v1_path = Path("output/v2") / f.name
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if not v1_path.exists(): continue
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with open(f) as g: legacy = json.load(g)
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with open(v1_path) as g: v11 = json.load(g)
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rec_legacy = (legacy.get("recueil") or {}).get("parsed") or {}
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rec_v11 = (v11.get("extraction") or {}).get("recueil") or {}
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pairs.append((f.stem, rec_legacy, rec_v11))
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return pairs
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def bench():
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pairs = load_pairs()
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print(f"\n{'Dossier':10s} {'Champ':28s} {'legacy':30s} {'v1.1':30s}")
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print("="*110)
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totals = {f: {"both": 0, "v11_only": 0, "leg_only": 0, "match": 0, "diff": 0}
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for f, _ in FIELDS_RECUEIL}
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totals["das_etab"] = {"both": 0, "v11_only": 0, "leg_only": 0, "match": 0, "diff": 0}
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for name, leg, v11 in pairs:
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# Champs simples
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for fk, lk in FIELDS_RECUEIL:
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vl = get(leg, lk)
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vv = get(v11, fk)
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if not vl and not vv: continue
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if vl and not vv: totals[fk]["leg_only"] += 1
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elif vv and not vl: totals[fk]["v11_only"] += 1
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else:
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totals[fk]["both"] += 1
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if fk == "codage_etab.dp_libelle":
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ok = vl in vv or vv in vl
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else:
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ok = vl == vv
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if ok: totals[fk]["match"] += 1
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else:
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totals[fk]["diff"] += 1
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# DAS count
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cle = count_das(leg, "codage_etab.das")
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cv1 = count_das(v11, "codage_etab.das")
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if cle and cv1:
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totals["das_etab"]["both"] += 1
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if cle == cv1: totals["das_etab"]["match"] += 1
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else: totals["das_etab"]["diff"] += 1
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elif cle: totals["das_etab"]["leg_only"] += 1
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elif cv1: totals["das_etab"]["v11_only"] += 1
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print(f"\n{'Champ':28s} {'match':>6s} {'diff':>5s} {'v11+':>5s} {'leg+':>5s} {'both':>5s}")
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print("-"*70)
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order = [f for f, _ in FIELDS_RECUEIL] + ["das_etab"]
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for fk in order:
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t = totals[fk]
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print(f" {fk:28s} {t['match']:>6d} {t['diff']:>5d} "
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f"{t['v11_only']:>5d} {t['leg_only']:>5d} {t['both']:>5d}")
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print("\nLégende :")
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print(" match = les deux extraient la même valeur")
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print(" diff = les deux extraient mais des valeurs différentes (à arbitrer)")
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print(" v11+ = V1.1 extrait, legacy vide")
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print(" leg+ = legacy extrait, V1.1 vide")
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print(" both = nb dossiers où les deux ont extrait qqch (match+diff)")
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if __name__ == "__main__":
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bench()
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