C.E.L_Slide_test2/tests/matching/phase21b.py

"""Phase 21b — ontology 기반 구조축 (tie-breaker 가중치)

공식: 점수 = 0.5 × 키워드 + 0.3 × 내용 + 0.1 × 구조(v3 ontology)
(구조는 tie-breaker 수준)

Phase 21(원본, old structure) vs Phase 21b(new ontology) 비교 의도.
"""
import sys
import json
import math
from pathlib import Path

sys.path.insert(0, str(Path(__file__).parent))

from phase_common import (
    TARGET_UNITS, load_synonyms, load_32_frames, compute_df_idf_tier,
    extract_mdx_keywords, keyword_score, content_scores_batch,
    load_target_units, load_frame_index, normalize_with_synonyms,
)
from structure_v3 import load_ontology, detect_mdx_structure_v3, structural_match_v3

ROOT = Path(r"d:\ad-hoc\kei\design_agent")
PREVIEW_DIR = ROOT / "data" / "figma_previews"


def main():
    synonyms = load_synonyms()
    frames = load_32_frames()
    df, idf, tier, N = compute_df_idf_tier(frames)
    vocab = set()
    for v in frames.values(): vocab.update(v["keywords"])
    units_full, units_title = load_target_units()
    idx_data, frame_to_short = load_frame_index()
    ontology = load_ontology()

    W_KW, W_CONTENT, W_STRUCT = 0.5, 0.3, 0.1

    reports = []
    hits = 0
    for uid, display, correct_sid, *_ in TARGET_UNITS:
        text_orig = units_full[uid]
        text = normalize_with_synonyms(text_orig, synonyms)  # synonym 정규화 공통 적용
        title = units_title[uid]
        mdx_kws = extract_mdx_keywords(text, vocab, synonyms=None)  # 이미 정규화됨
        mdx_schema = detect_mdx_structure_v3(text, title)           # 정규화된 text 사용
        c_scores = content_scores_batch(title, frames)

        ranked = []
        for fid, v in frames.items():
            fig_kws = set(v["keywords"])
            k_s, inter = keyword_score(mdx_kws, fig_kws, idf, tier)
            c_s = c_scores.get(fid, 0.0)
            s_s, aligns = structural_match_v3(mdx_schema, ontology.get(fid, {}))
            final = W_KW * k_s + W_CONTENT * c_s + W_STRUCT * s_s
            ranked.append((fid, final, {
                "kw": k_s, "content": c_s, "struct": s_s,
                "aligns": aligns, "inter": sorted(inter),
            }))
        ranked.sort(key=lambda x: -x[1])
        top3 = ranked[:3]
        top_sid = frame_to_short.get(top3[0][0], "?")
        if top_sid == correct_sid:
            hits += 1
        reports.append({
            "uid": uid, "display": display, "correct_sid": correct_sid,
            "mdx_kws": mdx_kws, "mdx_title": title, "mdx_schema": mdx_schema,
            "top3": top3,
        })
        print(f"{uid}(정답={correct_sid}): "
              f"Top1={top_sid} ({top3[0][1]:.3f}) "
              f"[{'✓' if top_sid == correct_sid else '✗'}] "
              f"struct={top3[0][2]['struct']:.2f}")

    print(f"\n=== Phase 21b 결과: {hits}/4 ===")

    # MD 리포트
    png_rel = "../../data/figma_previews/"
    lines = []
    lines.append(f"# Phase 21b — Ontology 기반 구조축 (tie-breaker)")
    lines.append("")
    lines.append(f"**공식**: `점수 = {W_KW} × 키워드 + {W_CONTENT} × 내용 + {W_STRUCT} × 구조(ontology)`")
    lines.append(f"**결과: {hits}/4**")
    lines.append("")
    lines.append("**Phase 21 원본 대비 차이:**")
    lines.append("- 구조 매칭 로직: `structural_match_v2` (layout 문자열) → `structural_match_v3` (속성 교집합)")
    lines.append("- 구조 가중치: 0.2 → 0.1 (tie-breaker 수준)")
    lines.append("- 구조 ontology: layout 문자열 → `structure_ontology.yaml` 속성 schema")
    lines.append("- MDX 구조 감지: ### 서브섹션/표헤더/블릿 기반 schema emit")
    lines.append("- confidence 체크: low면 구조 점수 0")
    lines.append("")

    # 통합 매트릭스
    lines.append("## 테스트 결과")
    lines.append("")
    lines.append("| 콘텐츠 | 1순위 | 2순위 | 3순위 |")
    lines.append("|--------|-------|-------|-------|")
    for r in reports:
        row = [f"**{r['display']}**<br>정답 Frame **{r['correct_sid']}**"]
        for rank_idx in range(3):
            fid, score, bd = r["top3"][rank_idx]
            sid = frame_to_short.get(fid, "?")
            info = idx_data.get(sid, {})
            png = info.get("png", "")
            title = info.get("title_text", "").strip().replace("\n", " ")[:15] + "…"
            inner = f"![{sid}]({png_rel}{png})<br>**{sid}** ({score:.3f})<br>{title}"
            if sid == r["correct_sid"]:
                cell = f"<div style='background:#fff3cd;border:3px solid #dc2626;padding:8px;border-radius:6px'>🎯 <b>정답</b><br>{inner}</div>"
            else:
                cell = inner
            row.append(cell)
        lines.append("| " + " | ".join(row) + " |")
    lines.append("")

    # 세부 결과
    lines.append("## 테스트 결과 세부")
    lines.append("")
    for r in reports:
        lines.append(f"### {r['display']} — 정답 Frame **{r['correct_sid']}**")
        lines.append("")
        lines.append(f"**MDX 구조 (v3 emit)**")
        lines.append("```yaml")
        for k, vv in r["mdx_schema"].items():
            lines.append(f"{k}: {vv}")
        lines.append("```")
        lines.append("")
        lines.append(f"**MDX 키워드 ({len(r['mdx_kws'])}개)**: {', '.join(sorted(r['mdx_kws']))}")
        lines.append("")
        for rank, (fid, score, bd) in enumerate(r["top3"], 1):
            sid = frame_to_short.get(fid, "?")
            fig_schema = ontology.get(fid, {})
            info = idx_data.get(sid, {})
            png = info.get("png", "")
            fig_content = frames[fid].get("content", "")
            common = ", ".join(bd["inter"]) if bd["inter"] else "(없음)"
            align_str = ", ".join(bd["aligns"]) if bd["aligns"] else "-"
            is_correct = sid == r["correct_sid"]
            if is_correct:
                lines.append(f"**<span style='background:#fff3cd;border:2px solid #dc2626;padding:2px 8px;border-radius:3px'>🎯 {rank}위 Frame {sid} (정답)</span>**")
            else:
                lines.append(f"**{rank}위 Frame {sid}**")
            lines.append("")
            lines.append(f"![{sid}]({png_rel}{png})")
            lines.append("")
            lines.append(f"- **매칭 내용**: {fig_content}")
            lines.append(f"- **매칭 키워드**: {common}")
            lines.append(f"- **Figma schema**: family=`{fig_schema.get('family')}`, "
                         f"columns={fig_schema.get('columns')}, "
                         f"role=`{fig_schema.get('semantic_role')}`, "
                         f"conf=`{fig_schema.get('confidence')}`")
            lines.append(f"- **구조 속성 정렬**: {align_str}")
            lines.append(f"- **축별 점수**: 키워드 {bd['kw']:.3f} / 내용 {bd['content']:.3f} / 구조 {bd['struct']:.2f}")
            lines.append(f"- **최종**: **{score:.3f}**")
            lines.append("")

    out = Path(__file__).parent / "MATRIX_PHASE21b.md"
    out.write_text("\n".join(lines), encoding="utf-8")
    print(f"완료: {out}")

    # 별도 결과 저장 (phase22용)
    import pickle
    serializable = {
        "phase": "21b",
        "desc": "synonym + 키워드 + 내용 + 구조(ontology v3)",
        "weights": (W_KW, W_CONTENT, W_STRUCT),
        "hits": hits,
        "reports": [{
            "uid": r["uid"], "display": r["display"], "correct_sid": r["correct_sid"],
            "mdx_kws_count": len(r["mdx_kws"]),
            "top3": [(fid, score, frame_to_short.get(fid, "?"), bd) for fid, score, bd in r["top3"]],
        } for r in reports]
    }
    with open(Path(__file__).parent / "_phase21b_results.pkl", "wb") as f:
        pickle.dump(serializable, f)


if __name__ == "__main__":
    main()