#!/usr/bin/env python3 """ Chara Dasha KN Rao Benchmark v1.1 比较 v6.1.11 yinduzhanxing Chara Dasha 与 PyJHora KN Rao method。 策略：用 PyJHora 计算行星位置作为共享输入，两个实现基于相同数据运行。 这样隔离算法差异，消除天文计算差异。 依赖: pip install jhora numpy """ import sys, json, os # 添加scripts路径 sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', '..', 'scripts'))) from jaimini import SIGNS, _chara_dasha_duration_knrao, _chara_progression_knrao, _EVEN_FOOTED_SIGNS # PyJHora from jhora.horoscope.dhasa.raasi import chara as pj_chara from jhora.horoscope.chart import charts from jhora.panchanga import drik from jhora import const, utils # ───────────────────────────────────────────── # 10个测试案例（与Round 7相同） # ───────────────────────────────────────────── TEST_CASES = [ {"id": "smoke_beijing_1990_noon", "year":1990, "month":6, "day":15, "hour":12, "minute":0, "lat":39.9, "lon":116.4, "tz":8}, {"id": "smoke_newyork_1985_morning", "year":1985, "month":3, "day":22, "hour":9, "minute":30, "lat":40.7, "lon":-74.0, "tz":-5}, {"id": "smoke_london_1970_evening", "year":1970, "month":9, "day":12, "hour":19, "minute":0, "lat":51.5, "lon":-0.1, "tz":0}, {"id": "smoke_delhi_2000_midnight", "year":2000, "month":1, "day":1, "hour":0, "minute":0, "lat":28.6, "lon":77.2, "tz":5.5}, {"id": "smoke_sydney_1999_afternoon", "year":1999, "month":8, "day":7, "hour":15, "minute":45, "lat":-33.9, "lon":151.2, "tz":10}, {"id": "smoke_tokyo_1964_noon", "year":1964, "month":10, "day":10,"hour":12, "minute":0, "lat":35.7, "lon":139.7, "tz":9}, {"id": "smoke_cairo_1952_dawn", "year":1952, "month":7, "day":23, "hour":6, "minute":0, "lat":30.0, "lon":31.2, "tz":2}, {"id": "smoke_paris_1989_noon", "year":1989, "month":11,"day":9, "hour":12, "minute":30, "lat":48.9, "lon":2.3, "tz":1}, {"id": "smoke_losangeles_1995_night", "year":1995, "month":2, "day":14, "hour":22, "minute":15, "lat":34.1, "lon":-118.2,"tz":-8}, {"id": "smoke_sao_paulo_2004_morning","year":2004, "month":12,"day":25, "hour":7, "minute":0, "lat":-23.5, "lon":-46.6, "tz":-3}, ] # 行星名称到PyJHora ID PLANET_NAMES = { const.SUN_ID: "Sun", const.MOON_ID: "Moon", const.MARS_ID: "Mars", const.MERCURY_ID: "Mercury", const.JUPITER_ID: "Jupiter", const.VENUS_ID: "Venus", const.SATURN_ID: "Saturn", const.RAHU_ID: "Rahu", const.KETU_ID: "Ketu", } def run_benchmark(): total_sign = 0; sign_match = 0 total_dur = 0; dur_match = 0 detail_lines = [] sample_details = [] for case in TEST_CASES: # 1. 用 PyJHora 获取行星位置 dob = drik.Date(case["year"], case["month"], case["day"]) tob = (case["hour"], case["minute"], 0) place = drik.Place(f'test_{case["id"]}', case["lat"], case["lon"], case["tz"]) jd = utils.julian_day_number(dob, tob) pp = charts.divisional_chart(jd, place, divisional_chart_factor=1)[:const._pp_count_upto_ketu] asc_house = pp[0][1][0] # 0-indexed ascendant sign (pp[0] = Lagna) # 2. 构建共享的行星经度字典（供我们的代码使用） # 注意: pp[0]=Lagna, pp[1]=Sun, pp[2]=Moon, ... 即 pp[planet_id+1]=planet planet_longitudes = {} for planet_id, pname in PLANET_NAMES.items(): sign = pp[planet_id + 1][1][0] deg = pp[planet_id + 1][1][1] planet_longitudes[pname] = sign * 30 + deg # 3. 我们的 KN Rao 实现 our_progression = _chara_progression_knrao(asc_house, planet_longitudes) our_durations = [_chara_dasha_duration_knrao(planet_longitudes, s) for s in our_progression] # 4. PyJHora KN Rao 实现（oracle） pj_progression = pj_chara._dhasa_progression_knrao_method(pp) pj_durations = [pj_chara._dhasa_duration_knrao_method(pp, s) for s in pj_progression] # 5. 比较 case_sign_match = 0; case_dur_match = 0 mismatches = [] for i in range(12): our_s = our_progression[i] pj_s = pj_progression[i] our_d = our_durations[i] pj_d = pj_durations[i] if our_s == pj_s: case_sign_match += 1 else: mismatches.append(f"sign[{i}]: us={SIGNS[our_s]}, pj={SIGNS[pj_s]}") if our_d == pj_d: case_dur_match += 1 else: mismatches.append(f"dur[{i}]: us={our_d}, pj={pj_d}") total_sign += 12; sign_match += case_sign_match total_dur += 12; dur_match += case_dur_match our_first3 = ",".join(SIGNS[s] for s in our_progression[:3]) pj_first3 = ",".join(SIGNS[s] for s in pj_progression[:3]) line = f" {case['id']:35s} | sign {case_sign_match:2d}/12 | dur {case_dur_match:2d}/12" detail_lines.append(line) sample_details.append({ "case": case['id'], "asc": SIGNS[asc_house], "our_first_3": our_first3, "pj_first_3": pj_first3, "sign_match": f"{case_sign_match}/12", "dur_match": f"{case_dur_match}/12", "mismatches": mismatches[:5] # 最多5个不匹配项 }) # ── 输出 ── print("=" * 80) print("Chara Dasha KN Rao Benchmark v1.1") print(f"Skill: v6.1.11 (共享PyJHora行星位置)") print("=" * 80) print(f"\n{'Case':40s} | Sign Match | Dur Match | Us first3 vs PJ first3") print("-" * 80) for i, s in enumerate(sample_details): line = f" {s['case']:35s} | {s['sign_match']:>10s} | {s['dur_match']:>9s} | {s['our_first_3']} | {s['pj_first_3']}" print(line) print("-" * 80) total_all = total_sign + total_dur match_all = sign_match + dur_match print(f"\nSign Sequence Match: {sign_match}/{total_sign} = {sign_match/total_sign*100:.2f}%") print(f"Duration Match: {dur_match}/{total_dur} = {dur_match/total_dur*100:.2f}%") print(f"Overall Match: {match_all}/{total_all} = {match_all/total_all*100:.2f}%") if match_all / total_all >= 0.95: status = "✅ PASS ✓" elif match_all / total_all >= 0.85: status = "⚠️ BORDERLINE" else: status = "❌ FAIL" print(f"\nBenchmark Result: {status}") # 放生不匹配 if status != "✅ PASS ✓": print("\n--- 不匹配详情 ---") for s in sample_details: if s["mismatches"]: print(f"\n{s['case']}:") for m in s["mismatches"]: print(f" {m}") # 保存 JSON out = os.path.join(os.path.dirname(__file__), "..", "outputs", "chara_dasha_knrao_benchmark.json") os.makedirs(os.path.dirname(out), exist_ok=True) result = { "version": "v6.1.11", "benchmark": "chara_dasha_kn_rao", "total_sign_match": sign_match, "total_dur_match": dur_match, "total_sign": total_sign, "total_dur": total_dur, "sign_match_rate": round(sign_match/total_sign, 4) if total_sign else 0, "dur_match_rate": round(dur_match/total_dur, 4) if total_dur else 0, "status": status, "samples": sample_details, } with open(out, 'w') as f: json.dump(result, f, indent=2, ensure_ascii=False) print(f"\n结果已保存: {out}") if __name__ == "__main__": run_benchmark()