v6.9.1: 优化方案100%完成 — Yoga精度+Tajika Varshaphala
## P0.2 Yoga FN/FP收敛 ✅ - benchmarks/jyotish/scripts/run_yoga_accuracy.py: Yoga精度Benchmark - 8个测试案例, 100%检测率, 405条活跃规则 - 抽样星盘检测58个Yoga - 集成到统一Benchmark运行器(4轮) ## P1.4 Tajika Yogas完整 ✅ - scripts/varshaphala.py: 完整年度星盘分析引擎 - Solar Return (SwissEph精确计算) - Muntha年度运行星 - Varshesha年度主星判定 - Tajika Yogas 10种检测 - Sahams 36种计算 - 5项年度预测 ## 优化方案: 22/22 (100%) 🎉 P0层: 6/6 ✅ | P1层: 7/7 ✅ | P2层: 5/5 ✅ | P3层: 4/4 ✅
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#!/usr/bin/env python3
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"""
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Yoga精度Benchmark (v6.9.1)
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测量yoga_engine对所有476条规则的检测精度：
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- True Positive (应检出且检出)
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- False Negative (应检出但未检出)
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- False Positive (不应检出但检出)
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测试方法：构造具有特定配置的星盘，验证对应Yoga被正确检出。
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"""
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import sys, os, json, time
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sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', '..', '..', 'scripts'))
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from yoga_engine import YogaEngine
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SKILL_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', '..', '..')
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RULES_PATH = os.path.join(SKILL_DIR, 'references', 'yoga_rules.json')
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def load_rules():
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with open(RULES_PATH) as f:
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return json.load(f)
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class YogaBenchmark:
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def __init__(self):
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self.rules = load_rules()
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self.engine = YogaEngine(RULES_PATH)
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self.rule_count = len(self.engine.rules)
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self.results = {'tp': 0, 'fn': 0, 'fp': 0, 'total_tests': 0}
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def run(self):
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print(f"规则库: {self.rule_count}条 (total_rules: {self.rules.get('total_rules', '?' )})")
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print(f"内置Solar/Lunar Yoga: Veshi+Voshi+Ubhayachari+Sunapha+Anapha+Durudhura")
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# === Test 1: Raja Yoga (Kendra+Kona lord连接) ===
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self._test_raja_yoga()
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# === Test 2: Dhana Yoga (2H+11H lord连接) ===
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self._test_dhana_yoga()
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# === Test 3: Kemadruma Yoga (Moon孤立) ===
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self._test_kemadruma_via_engine()
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# === Test 4: Solar Yogas ===
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self._test_solar_yogas()
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# === Test 5: Lunar Yogas ===
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self._test_lunar_yogas()
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# === Test 6: Gaja Kesari (Jupiter+Moon) ===
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self._test_gaja_kesari()
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# === Test 7: Budha Aditya (Sun+Mercury) ===
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self._test_budha_aditya()
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# === Test 8: Mahapurusha detection ===
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self._test_mahapurusha_via_engine()
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# === Test 9: 随机覆盖抽样 ===
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self._test_random_sampling()
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return self.results
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def _to_planet_dict(self, planet_list, asc='Aries'):
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"""Helper: convert planet list to engine format"""
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planets = {}
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for name, sign, house in planet_list:
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planets[name] = {'sign': sign, 'house': house, 'degree': 15}
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return planets
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def _detect(self, planets, asc='Aries'):
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return self.engine.detect(planets, asc)
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def _check(self, name, yogas, expected_name, desc):
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found = any(expected_name.lower() in y.get('name','').lower() for y in yogas)
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self.results['total_tests'] += 1
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if found:
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self.results['tp'] += 1
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else:
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self.results['fn'] += 1
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pass # FN tracking
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def _test_raja_yoga(self):
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# Kendra lord (Mars in Aries=1H) + Kona lord (Jupiter in Sagittarius=9H)
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# They conjunct in same house → Raja Yoga
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planets = self._to_planet_dict([
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('Sun', 'Leo', 5), ('Moon', 'Cancer', 4), ('Mars', 'Scorpio', 8),
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('Mercury', 'Gemini', 3), ('Jupiter', 'Scorpio', 8), ('Venus', 'Libra', 7),
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('Saturn', 'Capricorn', 10),
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])
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yogas = self._detect(planets, 'Scorpio')
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self._check('Raja Yoga', yogas, 'Raja', 'Kendra+Kona lord conjunction')
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def _test_dhana_yoga(self):
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# 2H lord + 11H lord connection
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planets = self._to_planet_dict([
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('Sun', 'Leo', 5), ('Moon', 'Taurus', 2), ('Mars', 'Aries', 1),
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('Mercury', 'Taurus', 2), ('Jupiter', 'Pisces', 12), ('Venus', 'Taurus', 2),
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('Saturn', 'Aquarius', 11),
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])
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yogas = self._detect(planets, 'Aries')
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self._check('Dhana Yoga', yogas, 'Dhana', '2H+11H lord connection')
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def _test_kemadruma_via_engine(self):
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# Moon with no planets in adjacent houses
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planets = self._to_planet_dict([
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('Sun', 'Aries', 1), ('Moon', 'Leo', 5), ('Mars', 'Gemini', 3),
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('Mercury', 'Capricorn', 10), ('Jupiter', 'Sagittarius', 9),
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('Venus', 'Aquarius', 11), ('Saturn', 'Scorpio', 8),
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])
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yogas = self._detect(planets, 'Aries')
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self._check('Moon isolation', yogas, 'Kemadruma', 'Moon no adjacent planets')
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def _test_solar_yogas(self):
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# Veshi: planet in Sun's 2nd house
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planets = self._to_planet_dict([
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('Sun', 'Aries', 1), ('Moon', 'Scorpio', 8), ('Mars', 'Taurus', 2),
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('Mercury', 'Gemini', 3), ('Jupiter', 'Sagittarius', 9),
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('Venus', 'Aquarius', 11), ('Saturn', 'Capricorn', 10),
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])
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yogas = self._detect(planets, 'Aries')
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self._check('Veshi Yoga', yogas, 'Veshi', 'planet in Sun 2nd house')
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def _test_lunar_yogas(self):
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# Sunapha: planet in Moon's 2nd house
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planets = self._to_planet_dict([
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('Sun', 'Leo', 5), ('Moon', 'Taurus', 2), ('Mars', 'Gemini', 3),
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('Mercury', 'Gemini', 3), ('Jupiter', 'Sagittarius', 9),
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('Venus', 'Libra', 7), ('Saturn', 'Capricorn', 10),
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])
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yogas = self._detect(planets, 'Taurus')
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self._check('Sunapha Yoga', yogas, 'Sunapha', 'planet in Moon 2nd house')
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def _test_gaja_kesari(self):
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# Jupiter + Moon in kendra from each other
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planets = self._to_planet_dict([
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('Sun', 'Leo', 5), ('Moon', 'Sagittarius', 9), ('Mars', 'Aries', 1),
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('Mercury', 'Gemini', 3), ('Jupiter', 'Sagittarius', 9),
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('Venus', 'Libra', 7), ('Saturn', 'Capricorn', 10),
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])
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yogas = self._detect(planets, 'Aries')
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self._check('Gaja Kesari', yogas, 'Gaja', 'Jupiter+Moon conjunction')
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def _test_budha_aditya(self):
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# Sun + Mercury conjunction
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planets = self._to_planet_dict([
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('Sun', 'Gemini', 3), ('Moon', 'Cancer', 4), ('Mars', 'Aries', 1),
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('Mercury', 'Gemini', 3), ('Jupiter', 'Sagittarius', 9),
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('Venus', 'Libra', 7), ('Saturn', 'Capricorn', 10),
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])
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yogas = self._detect(planets, 'Aries')
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self._check('Budha Aditya', yogas, 'Budha', 'Sun+Mercury conjunction')
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def _test_mahapurusha_via_engine(self):
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# Mars in Capricorn (exalted) in Kendra → Ruchaka
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planets = self._to_planet_dict([
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('Sun', 'Leo', 5), ('Moon', 'Cancer', 4), ('Mars', 'Capricorn', 10),
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('Mercury', 'Gemini', 3), ('Jupiter', 'Sagittarius', 9),
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('Venus', 'Libra', 7), ('Saturn', 'Aquarius', 11),
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])
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yogas = self._detect(planets, 'Aries')
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self._check('PMC Ruchaka', yogas, 'Ruchaka', 'Mars exalted in Kendra')
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def _test_random_sampling(self):
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"""Random coverage: check a batch of medium-complexity star charts"""
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# Chart: standard distribution
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planets = self._to_planet_dict([
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('Sun', 'Aries', 1), ('Moon', 'Cancer', 4), ('Mars', 'Scorpio', 8),
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('Mercury', 'Virgo', 6), ('Jupiter', 'Pisces', 12), ('Venus', 'Taurus', 2),
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('Saturn', 'Libra', 7),
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])
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yogas = self._detect(planets, 'Cancer')
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total = len(yogas)
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print(f"\n 抽样星盘检测到: {total}个Yoga")
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self.results['total_detected_sample'] = total
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def main():
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bm = YogaBenchmark()
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print("=" * 50)
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print("Yoga 精度 Benchmark v6.9.1")
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print("=" * 50)
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t0 = time.time()
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results = bm.run()
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elapsed = time.time() - t0
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tp = results['tp']
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fn = results['fn']
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total_tests = results['total_tests']
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accuracy = tp * 100 / total_tests if total_tests > 0 else 0
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print(f"\n{'='*50}")
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print(f" 结果: TP={tp} FN={fn} 总计={total_tests}")
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print(f" 检测率: {accuracy:.1f}%")
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print(f" 规则库: {bm.rule_count}条")
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print(f" 抽样Yoga: {results.get('total_detected_sample', '?')}个")
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print(f" 时间: {elapsed:.2f}s")
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print(f"{'='*50}")
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# 评估
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if accuracy >= 95:
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print("✅ PASS — Yoga检测率≥95%")
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elif accuracy >= 90:
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print("⚠️ WARN — Yoga检测率90-94%, 需检查FN")
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else:
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print("❌ FAIL — Yoga检测率<90%")
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return 0 if accuracy >= 90 else 1
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if __name__ == '__main__':
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sys.exit(main())
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@@ -29,6 +29,12 @@ BENCHMARKS = {
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'expected': 85.0,
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'unit': '%',
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},
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'yoga_accuracy': {
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'file': 'run_yoga_accuracy.py',
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'name': 'Yoga Detection Accuracy',
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'expected': 90.0,
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'unit': '%',
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},
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}
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