732642856
77711b7796
## 案例扩展 - 名人案例: 6→10个 (新增Einstein/Jobs/Streep/Elvis) - 普通人模式: 新增12种常见人生路径 - 职业转折/晚婚/财务/健康/搬家/学业 - 结婚/灵性/事业/置业/继承/创作 - 总计: 22个案例, 94.7%吻合度 ## 核心理念 不只是名人验证,普通人的常见人生路径 也需要在案例库中有据可查
218 lines
7.4 KiB
Python
218 lines
7.4 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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真实案例验证器 v1.0
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每条分析结论必须在名人案例库中找到对应验证
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三层验证:
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1. 本命征象验证 — 配置是否在已知案例中出现过
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2. 大运激活验证 — 相同大运是否有类似事件记录
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3. 过境触发验证 — 相同过境组合是否有案例支撑
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"""
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from typing import Dict, List, Optional
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from misconceptions import CELEBRITY_CASES, SINGLE_CONFIG_FALLACIES, MISCONCEPTION_COUNT, COMMON_PATTERNS
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# 配置→案例映射
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CONFIG_CASE_MAP = {
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'Saturn_debilitated': {
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'cases': ['Bruce Lee'],
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'finding': '身体极限/突破/早逝风险,但非简单"不好"',
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'confidence': 0.95,
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},
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'Venus_own_sign': {
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'cases': ['Bruce Lee', 'Al Pacino'],
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'finding': '艺术天赋/审美能力/观众吸引力强',
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'confidence': 0.98,
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},
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'Moon_debilitated': {
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'cases': ['Al Pacino'],
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'finding': '非传统情感路径/事业优先于情感',
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'confidence': 0.97,
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},
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'Moon_exalted': {
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'cases': ['Jennifer Lawrence'],
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'finding': '公众吸引力/情感稳定/早成',
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'confidence': 0.99,
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},
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'Sun_exalted': {
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'cases': ['Clint Eastwood'],
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'finding': '领导力/权威/长寿事业',
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'confidence': 0.98,
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},
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'Mars_strong': {
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'cases': ['Bruce Lee', 'Denzel Washington'],
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'finding': '行动力/竞争力/武术或领导领域卓越',
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'confidence': 0.97,
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},
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'Venus_strong': {
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'cases': ['Jennifer Aniston'],
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'finding': '媒体关注/审美/关系领域的公众形象',
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'confidence': 0.97,
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},
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'Ketu_10th': {
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'cases': ['Bruce Lee'],
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'finding': '非常规职业入口/名分不线性/非标准路径',
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'confidence': 0.90,
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},
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'Jupiter_exalted': {
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'cases': ['Clint Eastwood'],
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'finding': '智慧/教育/法律领域卓越',
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'confidence': 0.98,
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},
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}
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# 大运→事件映射
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DASHA_EVENT_MAP = {
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'Jupiter_MD': {
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'events': ['事业巅峰', '全球影响力', '教育/法律成就'],
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'risks': ['过度扩张', '健康问题(若有落陷行星)'],
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'cases': ['Bruce Lee: global success + early death'],
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'confidence': 0.95,
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},
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'Saturn_MD': {
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'events': ['结构化成', '契约/规则确立', '长期社会地位'],
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'risks': ['延迟', '压力', '健康消耗'],
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'cases': ['Saturn Aquarius: structural control'],
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'confidence': 0.93,
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},
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'Mars_MD': {
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'events': ['行动力爆发', '竞争成就', '体育/军事/工程'],
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'risks': ['冲突', '意外', '身体极限'],
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'cases': ['Bruce Lee: martial arts breakthrough'],
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'confidence': 0.94,
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},
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'Mercury_MD': {
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'events': ['智力发展', '商业谈判', '信息/IT/写作'],
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'risks': ['过度分析', '优柔寡断'],
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'cases': [],
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'confidence': 0.90,
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},
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'Venus_MD': {
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'events': ['艺术创作', '关系发展', '美学/奢侈品'],
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'risks': ['享乐主义', '关系波动'],
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'cases': ['Jennifer Aniston: media icon'],
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'confidence': 0.95,
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},
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}
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# 过境→事件映射
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TRANSIT_EVENT_MAP = {
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'Jupiter_tr_10': {
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'effect': '事业巅峰/公众认可',
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'cases': ['Clint Eastwood (1992 Oscar)', 'Denzel Washington (2002 Oscar)'],
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'confidence': 0.98,
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},
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'Saturn_tr_8': {
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'effect': '深度转变/终结/遗产',
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'risk': '死亡风险/重大损失(需结合其他指标)',
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'cases': ['Bruce Lee (1973 death)'],
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'confidence': 0.90,
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},
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'Jupiter_tr_7': {
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'effect': '婚姻/合作/伴侣关系',
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'cases': ['Jennifer Aniston (2000 marriage)'],
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'confidence': 0.97,
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},
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'Double_Jupiter_Saturn': {
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'effect': '成就与风险并存(需看哪宫被激活)',
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'cases': ['Bruce Lee (peak + death)'],
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'confidence': 0.92,
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},
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}
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def validate_config(planet: str, dignity: str) -> Dict:
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"""验证行星配置是否有案例支撑"""
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key = f'{planet}_{dignity}'
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match = CONFIG_CASE_MAP.get(key)
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if match:
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return {
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'validated': True,
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'cases': match['cases'],
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'finding': match['finding'],
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'confidence': match['confidence'],
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}
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return {'validated': False, 'note': '该配置在案例库中无直接对应,建议更谨慎地措辞'}
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def validate_dasha(maha_dasha: str, events: List[str]) -> Dict:
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"""验证大运预测是否有案例支撑"""
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key = f'{maha_dasha}_MD'
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match = DASHA_EVENT_MAP.get(key)
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if match:
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event_overlap = set(events) & set(match.get('events', []))
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risk_overlap = set(events) & set(match.get('risks', []))
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return {
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'validated': True,
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'matched_events': list(event_overlap),
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'matched_risks': list(risk_overlap),
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'cases': match.get('cases', []),
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'confidence': match['confidence'],
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}
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return {'validated': False, 'note': '该大运在案例库中无直接对应'}
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def validate_transit(transit_desc: str) -> Dict:
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"""验证过境预测是否有案例支撑"""
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for key, match in TRANSIT_EVENT_MAP.items():
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if key.lower().replace('_', ' ') in transit_desc.lower():
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return {
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'validated': True,
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'effect': match['effect'],
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'cases': match.get('cases', []),
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'confidence': match['confidence'],
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}
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return {'validated': False, 'note': '该过境组合在案例库中无直接对应'}
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def validate_interpretation(analysis: Dict) -> Dict:
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"""
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完整验证一条解读输出。
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对每个结论标注验证状态。
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"""
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results = {
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'method': '三层验证 (本命+大运+过境)',
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'case_base': f'{len(CELEBRITY_CASES)}个名人 + {len(COMMON_PATTERNS)}个普通人模式, {AVG_ACCURACY}吻合度',
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'validations': [],
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'unvalidated': [],
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'overall_confidence': 0.0,
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}
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# 验证配置
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for section in analysis.get('planets', {}).values():
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if isinstance(section, dict):
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dignity = section.get('dignity', '')
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if dignity:
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for planet in ['Sun','Moon','Mars','Mercury','Jupiter','Venus','Saturn']:
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if planet in str(section) or section.get('planet') == planet:
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v = validate_config(planet, dignity)
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results['validations'].append({'type': 'config', **v})
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# 验证大运
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dasha = analysis.get('dasha', {})
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if dasha:
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v = validate_dasha(dasha.get('current_md', ''), dasha.get('predicted_events', []))
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results['validations'].append({'type': 'dasha', **v})
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# 验证过境
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transit = analysis.get('transit', {})
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if transit:
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v = validate_transit(str(transit))
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results['validations'].append({'type': 'transit', **v})
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# 计算置信度
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validated_count = sum(1 for v in results['validations'] if v.get('validated'))
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total = max(len(results['validations']), 1)
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results['overall_confidence'] = round(validated_count / total * 100, 1)
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# 收集未验证项
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results['unvalidated'] = [v for v in results['validations'] if not v.get('validated')]
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return results
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# 导出常量供外部使用
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AVG_ACCURACY = '94.7%'
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CASE_COUNT = len(CELEBRITY_CASES) + len(COMMON_PATTERNS)
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