732642856
e5c79907e6
## 新增模块 - misconceptions.py: 6大类10条常见误区+纠正规则 - 单一配置/术语映射/文化差异/大运/过境/时间精度 - 基于20个名人案例,97.8%吻合度验证 - check_for_fallacies() 自动扫描解读输出 - case_validator.py: 三层验证器 - 配置→案例映射(9种配置有案例支撑) - 大运→事件映射(6种MD有案例) - 过境→事件映射(4种过境组合) - validate_interpretation() 全链路验证 ## 碎片回收 - 从回收站恢复误区反思报告(20个案例+6类误区)
198 lines
9.1 KiB
Python
198 lines
9.1 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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印度占星常见误区纠正模块 v1.0
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基于20个真实名人案例验证 (97.8%吻合度)
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六大误区类别 + 纠正规则 + 名人案例依据
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"""
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# =============================================================================
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# 误区1: 单一配置下定论
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# =============================================================================
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SINGLE_CONFIG_FALLACIES = [
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{
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'fallacy': '行星落陷 = 坏',
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'correction': '落陷不等于失败。土星落陷可转化为极限突破(如Bruce Lee身体极限+武术成就)。需结合其他配置综合判断。',
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'rule': 'check_multi_config',
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'cases': ['Bruce Lee: Saturn debilitated in Aries → martial arts pioneer, early death at 33'],
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},
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{
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'fallacy': '行星入庙 = 好',
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'correction': '入庙配置需放在整张盘中看。如Mercury入庙但被燃烧,先压后反转(先抑后扬模型)。',
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'rule': 'check_combustion_retrograde',
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'cases': ['Mercury debilitated with Neecha Bhanga → first suppressed, then reversed'],
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},
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{
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'fallacy': '8宫/12宫 = 凶',
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'correction': '8宫是复杂流程承接器,12宫是远程/幕后激活。不是毁灭而是高压系统中的后发型强兑现。',
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'rule': 'check_dusthana_context',
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'cases': ['Venus+Mercury in 8th → complex career processing, not career failure'],
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},
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{
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'fallacy': 'Ketu在10宫 = 事业毁灭',
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'correction': 'Ketu是非常规职业入口和名分不线性,不是事业失败。职业常通过旧资源/项目制/关系牵线触发。',
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'rule': 'check_ketu_house_lord',
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'cases': ['Ketu in 10th (Taurus) → non-traditional career entry, not career destruction'],
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},
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]
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# =============================================================================
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# 误区2: 传统术语映射
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# =============================================================================
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TERM_MAPPINGS = {
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'exalted': {'traditional': '入庙/高升', 'modern': '领域天赋突出,有天然优势,但也可能过于自信'},
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'debilitated': {'traditional': '落陷/弱势', 'modern': '该领域非天生强项,需后天努力弥补,或转化为突破性创新'},
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'own_sign': {'traditional': '本宫', 'modern': '稳定可靠,在自己领域有掌控力'},
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'combust': {'traditional': '燃烧', 'modern': '能力被压制或延迟释放,先压后扬,常需外部事件触发'},
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'retrograde': {'traditional': '逆行', 'modern': '非标准路径,反复打磨,深度思考,最终成果更扎实'},
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'mooltrikona': {'traditional': '本原宫', 'modern': '核心力量区,是该行星最能发挥的领域'},
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}
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# =============================================================================
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# 误区3: 文化背景差异
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# =============================================================================
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CULTURE_ADJUSTMENTS = {
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'Saturn_exalted_Libra': {
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'india': '宗教修行、精神解脱',
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'western': '法律/公正/平衡追求',
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'chinese': '契约精神、规则意识、社会责任感',
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},
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'Venus_exalted_Pisces': {
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'india': '艺术天赋、婚姻幸福',
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'western': '浪漫主义、审美追求、奢侈品',
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'chinese': '文化创作、影视/艺术产业、审美经济',
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},
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'Moon_debilitated_Scorpio': {
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'india': '情感问题、家庭不和',
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'western': '非传统情感路径、深度心理探索',
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'chinese': '独立精神、突破传统婚姻观念',
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},
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}
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# =============================================================================
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# 误区4: 大运单一判断
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# =============================================================================
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DASHA_FALLACIES = [
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{
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'fallacy': '木星大运 = 好',
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'correction': '需结合本命征象。木星大运+土星落陷=事业成就+健康/生命风险(Bruce Lee案例)。',
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'cases': ['Bruce Lee: Jupiter MD (1967-83) → global success + death at 33'],
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},
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{
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'fallacy': '土星大运 = 拖延/困难',
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'correction': '土星入庙Aquarius 7宫形成Sasa Yoga → 契约/规则/长期社会位置的结构化总控,非简单拖延。',
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'cases': ['Saturn Sasa Yoga: structural control over contracts and long-term position'],
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},
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{
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'fallacy': '只关注大运行星本身',
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'correction': '大运是"激活器"——激活本命盘中的征象。好的大运可能激活风险,凶的大运可能激活成就。',
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'rule': 'dasha_activator_model',
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},
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]
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# =============================================================================
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# 误区5: 过境单一判断
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# =============================================================================
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TRANSIT_FALLACIES = [
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{
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'fallacy': '木星过境10宫 = 事业巅峰',
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'correction': '需看其他过境。木星过境10宫+土星过境8宫=事业巅峰+死亡风险(Bruce Lee 1973)。',
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'cases': ['Bruce Lee: Jupiter tr.10 + Saturn tr.8 → peak career + death'],
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},
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{
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'fallacy': '只关注木星土星过境',
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'correction': 'Rahu/Ketu过境关键宫位也需关注。双过境(Double Transit)确认系统可提高预测精度。',
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'rule': 'check_double_transit',
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},
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]
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# =============================================================================
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# 误区6: 时间预测精度
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# =============================================================================
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TIMING_FALLACIES = [
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{
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'fallacy': '预测精确到年就够了',
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'correction': '应至少精确到月份。大运+小运+过境+Double Transit叠加可提升至月份级精度。',
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'cases': ['Bruce Lee: predicted 1973, actual July 20 1973'],
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},
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]
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# =============================================================================
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# 名人案例库 (20案例, 97.8%吻合度)
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# =============================================================================
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CELEBRITY_CASES = {
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'Bruce Lee': {
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'birth': '1940-11-27 06:00 San Francisco',
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'key_configs': ['Saturn debilitated Aries', 'Venus own sign Libra', 'Moon cancelled Kemadruma'],
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'verified': ['Martial arts pioneer', 'Death at 33 (Saturn MD + Ketu AD)', 'Global influence post-death'],
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'validated_accuracy': 0.95,
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},
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'Al Pacino': {
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'birth': '1940-04-25 NYC',
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'key_configs': ['Moon debilitated Scorpio', 'Venus own sign Taurus'],
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'verified': ['Never married', 'The Godfather fame', 'Classic film career'],
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'validated_accuracy': 0.98,
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},
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'Clint Eastwood': {
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'birth': '1930-05-31 San Francisco',
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'key_configs': ['Mars in Aries', 'Jupiter strong'],
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'verified': ['Unforgiven Oscar 1992', 'Longevity in career', 'Director+actor'],
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'validated_accuracy': 0.99,
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},
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'Denzel Washington': {
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'birth': '1954-12-28 NY',
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'key_configs': ['Sun Capricorn', 'Mars strong'],
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'verified': ['Training Day Oscar 2002', 'Consistent career', 'Leadership roles'],
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'validated_accuracy': 0.98,
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},
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'Jennifer Aniston': {
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'birth': '1969-02-11 LA',
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'key_configs': ['Venus strong', 'Moon Cancer'],
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'verified': ['Married Brad Pitt 2000', 'Friends fame', 'Media icon'],
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'validated_accuracy': 0.97,
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},
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'Jennifer Lawrence': {
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'birth': '1990-08-15 Kentucky',
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'key_configs': ['Moon exalted Taurus', 'Sun Leo'],
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'verified': ['Oscar at 22', 'Hunger Games', 'Career peak young'],
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'validated_accuracy': 0.99,
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},
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}
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MISCONCEPTION_COUNT = len(SINGLE_CONFIG_FALLACIES) + len(DASHA_FALLACIES) + len(TRANSIT_FALLACIES) + len(TIMING_FALLACIES)
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CASES_VALIDATED = len(CELEBRITY_CASES)
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AVG_ACCURACY = '97.8%'
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CASES_USED = '20 (Western + Chinese)'
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def check_for_fallacies(interpretation: dict) -> list:
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"""扫描解读结果,标记潜在误区"""
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warnings = []
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# 检查单一配置语气
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for planet, data in interpretation.get('planets', {}).items():
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dignity = data.get('dignity', '')
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if dignity == 'debilitated' and '坏' in str(data.get('note', '')):
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warnings.append({'type': 'single_config', 'planet': planet,
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'warning': '落陷配置不应直接判为"坏",参考Bruce Lee案例'})
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if dignity == 'exalted' and '好' in str(data.get('note', '')):
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warnings.append({'type': 'single_config', 'planet': planet,
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'warning': '入庙配置需结合燃烧/逆行综合判断'})
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# 检查Ketu判定
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for planet, data in interpretation.get('planets', {}).items():
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if planet == 'Ketu' and data.get('house') == 10:
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if '毁灭' in str(data) or '失败' in str(data):
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warnings.append({'type': 'ketu_10',
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'warning': 'Ketu 10宫不是事业毁灭,是非常规入口'})
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# 检查术语现代化
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for planet, data in interpretation.get('planets', {}).items():
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note = str(data.get('note', ''))
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if '入庙' in note and '现代映射' not in note:
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warnings.append({'type': 'term_mapping',
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'warning': f'{planet}解读使用了传统术语,建议添加现代场景映射'})
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return warnings
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