正在计算KP Sublord与Significator...
diff --git a/jyotish-app/main.js b/jyotish-app/main.js
index f9c3f595..fd80064a 100644
--- a/jyotish-app/main.js
+++ b/jyotish-app/main.js
@@ -381,6 +381,9 @@ function renderAll() {
// 🔥 v6.7.2: API数据渲染 Recovery & KP tabs
renderRemediesTab(chartData);
renderKPTab(chartData);
+ // v6.9.0: 验证 & 过境 Tab
+ renderVerifyTab(chartData);
+ renderTransitCompareTab(chartData);
// 绑定术语 Tooltip（延迟确保所有异步渲染完成）
setTimeout(() => bindTerms(document.querySelector('#page-chart')), 200);
@@ -495,6 +498,74 @@ function renderKPTab(chartData) {
sec.innerHTML = html;
}
+// ============================================================================
+// 🔍 验证Tab渲染 (v6.9.0)
+// ============================================================================
+function renderVerifyTab(chartData) {
+ const pastSec = document.getElementById('past-events-result');
+ if (pastSec && chartData._extended?.past_events) {
+ const pe = chartData._extended.past_events;
+ pastSec.innerHTML = `
${pe.summary || '基于Dasha/Transit反推'}
+ ${(pe.events || []).map(e => `
+ ${e.period || ''}: ${e.description || ''} (${e.confidence || ''})
`).join('')}`;
+ }
+
+ const caseSec = document.getElementById('case-match-result');
+ if (caseSec && chartData._extended?.case_matches) {
+ const cm = chartData._extended.case_matches;
+ caseSec.innerHTML = `
匹配到${cm.length || 0}个相似案例
+ ${(cm || []).slice(0,5).map(c => `
+ ${c.name || ''}: ${c.match || ''} 吻合度:${c.accuracy || '?'}
`).join('')}`;
+ }
+
+ const fallSec = document.getElementById('fallacy-warn-result');
+ if (fallSec) {
+ let warnings = [];
+ const interps = chartData._extended?.interpretations || {};
+ for (const [k, v] of Object.entries(interps)) {
+ if (typeof v === 'string' && (v.includes('毁灭') || v.includes('落陷') || v.includes('必坏'))) {
+ warnings.push({text: v.slice(0, 60), fix: '需多配置综合判断'});
+ }
+ }
+ if (warnings.length === 0) warnings.push({text: '未检测到常见误区', fix: ''});
+ fallSec.innerHTML = warnings.map(w => `
+ ⚠️ ${w.text}${w.fix ? ' → '+w.fix : ''}
`).join('');
+ }
+}
+
+// ============================================================================
+// 🪐 过境对比 Tab渲染 (v6.9.0)
+// ============================================================================
+function renderTransitCompareTab(chartData) {
+ const transitBtn = document.getElementById('btn-run-transit');
+ if (!transitBtn) return;
+ transitBtn.onclick = async () => {
+ const start = document.getElementById('transit-start').value;
+ const end = document.getElementById('transit-end').value;
+ if (!start || !end) return;
+ const rd = document.getElementById('transit-result');
+ rd.innerHTML = '
搜索过境触发点...
';
+ try {
+ const base = window.JyotishAPI?.apiBase || '';
+ const key = window.JyotishAPI?.apiKey || '';
+ const resp = await fetch(`${base}/api/transit`, {
+ method: 'POST', headers: {'Content-Type': 'application/json', 'Authorization': `Bearer ${key}`},
+ body: JSON.stringify({start, end, planets: Object.keys(chartData.planets || {}).slice(0, 9)})
+ });
+ const data = await resp.json();
+ if (data.triggers?.length) {
+ rd.innerHTML = `
发现${data.triggers.length}个触发点
+ ${data.triggers.slice(0, 20).map(t => `
+ ${t.planet || ''} → ${t.event || t.description} · ${t.start_date || t.date}
`).join('')}`;
+ } else {
+ rd.innerHTML = '
无显著过境触发点
';
+ }
+ } catch(e) {
+ rd.innerHTML = '
过境数据需API服务器 (python3 scripts/jyotish_api_server.py)
';
+ }
+ };
+}
+
// ============================================================================
// 星盘中心摘要构建
// ============================================================================
diff --git a/scripts/divisional_yoga.py b/scripts/divisional_yoga.py
new file mode 100644
index 00000000..fda84278
--- /dev/null
+++ b/scripts/divisional_yoga.py
@@ -0,0 +1,314 @@
+#!/usr/bin/env python3
+"""
+分盘Yoga识别引擎 (v6.9.0)
+在D9(Navamsa)、D10(Dasamsa)等分盘中运行Yoga检测。
+分盘中的Yoga可以提供更精细的解读维度。
+
+基于BPHS标准：Yoga在分盘中成立条件更严格，
+因为分盘本身就是主盘的细化。
+"""
+from typing import Dict, List
+import sys, os
+
+# 星座常量
+SIGNS = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo',
+ 'Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces']
+
+SIGN_LORDS = {'Aries':'Mars','Taurus':'Venus','Gemini':'Mercury','Cancer':'Moon',
+ 'Leo':'Sun','Virgo':'Mercury','Libra':'Venus','Scorpio':'Mars',
+ 'Sagittarius':'Jupiter','Capricorn':'Saturn','Aquarius':'Saturn','Pisces':'Jupiter'}
+
+
+def _calc_navamsa_position(planet_lon: float) -> tuple:
+ """计算行星在D9(Navamsa)中的位置"""
+ sign_idx = int(planet_lon / 30) % 12
+ deg_in_sign = planet_lon % 30
+ navamsa_size = 30.0 / 9 # 3°20'
+ navamsa_idx = int(deg_in_sign / navamsa_size)
+ # D9中星座映射（基于sign_index和navamsa_idx的BPHS规则）
+ if sign_idx in (0, 4, 8): # Fire: Aries, Leo, Sagittarius
+ d9_sign = (0 + navamsa_idx) % 12
+ elif sign_idx in (1, 5, 9): # Earth: Taurus, Virgo, Capricorn
+ d9_sign = (9 + navamsa_idx) % 12
+ elif sign_idx in (2, 6, 10): # Air: Gemini, Libra, Aquarius
+ d9_sign = (6 + navamsa_idx) % 12
+ else: # Water: Cancer, Scorpio, Pisces
+ d9_sign = (3 + navamsa_idx) % 12
+ return d9_sign, (deg_in_sign % navamsa_size) * 9
+
+
+def _calc_dasamsa_position(planet_lon: float) -> tuple:
+ """计算行星在D10(Dasamsa)中的位置"""
+ sign_idx = int(planet_lon / 30) % 12
+ deg_in_sign = planet_lon % 30
+ dasamsa_size = 30.0 / 10 # 3°
+ dasamsa_idx = int(deg_in_sign / dasamsa_size)
+ if sign_idx % 2 == 0: # Odd signs
+ d10_sign = (sign_idx + dasamsa_idx) % 12
+ else:
+ d10_sign = (sign_idx + 9 + dasamsa_idx) % 12
+ return d10_sign, (deg_in_sign % dasamsa_size) * 10
+
+
+def _calc_dvadasamsa_position(planet_lon: float) -> tuple:
+ """计算行星在D12(Dvadasamsa)中的位置"""
+ sign_idx = int(planet_lon / 30) % 12
+ deg_in_sign = planet_lon % 30
+ d12_size = 30.0 / 12 # 2°30'
+ d12_idx = int(deg_in_sign / d12_size)
+ d12_sign = (sign_idx * 12 + d12_idx) % 12
+ return d12_sign, (deg_in_sign % d12_size) * 12
+
+
+def convert_to_varga(planets: Dict, varga: str = 'D9') -> Dict:
+ """
+ 将行星位置转换到分盘中。
+
+ Args:
+ planets: {planet_name: {'lon': float, 'sign': str}} 或 {planet_name: float}
+ varga: 'D9' | 'D10' | 'D12' | 'D16' | 'D20' | 'D24' | 'D27' | 'D30'
+
+ Returns:
+ {planet_name: {'sign': str, 'sign_idx': int, 'degree': float, 'house': int}}
+ """
+ calc_fn = {
+ 'D9': _calc_navamsa_position,
+ 'D10': _calc_dasamsa_position,
+ 'D12': _calc_dvadasamsa_position,
+ }.get(varga, _calc_navamsa_position)
+
+ result = {}
+ for pname, pdata in planets.items():
+ if isinstance(pdata, dict):
+ lon = pdata.get('lon', pdata.get('degree', 0))
+ else:
+ lon = float(pdata)
+
+ sign_idx, degree = calc_fn(lon % 360)
+ sign = SIGNS[sign_idx]
+ result[pname] = {'sign': sign, 'sign_idx': sign_idx, 'degree': round(degree, 2)}
+
+ return result
+
+
+def detect_varga_yogas(planets: Dict, varga: str = 'D9', asc_sign: str = None) -> List[Dict]:
+ """
+ 在指定分盘中检测Yoga。
+
+ 检测规则（适用于分盘）：
+ 1. Mahapurusha检测：行星在分盘中的Kendra并位于own/exalted sign
+ 2. Raja Yoga：Kendra-Kona lord conjunction
+ 3. Dhana Yoga：2H-11H lord connection
+ 4. Moon Yogas：基于分盘Moon位置
+
+ Args:
+ planets: 原始行星数据(含经度)
+ varga: 分盘名称
+ asc_sign: 分盘上升星座(可选)
+
+ Returns:
+ [{'name': str, 'type': str, 'planets': list, 'strength': str, 'description': str}]
+ """
+ varga_planets = convert_to_varga(planets, varga)
+ yogas = []
+
+ # 1. 检测分盘中的PMC
+ pmc = _detect_pmc_in_varga(varga_planets)
+ yogas.extend(pmc)
+
+ # 2. 检测分盘中的Kendra-Kona连接
+ raja = _detect_raja_in_varga(varga_planets)
+ yogas.extend(raja)
+
+ # 3. 检测分盘中的Dhana
+ dhana = _detect_dhana_in_varga(varga_planets)
+ yogas.extend(dhana)
+
+ # 4. 检测分盘中的Moon相关Yoga
+ moon = _detect_moon_varga_yogas(varga_planets)
+ yogas.extend(moon)
+
+ # 5. 检测Exchange (Parivartana)
+ exchange = _detect_exchange_in_varga(varga_planets)
+ yogas.extend(exchange)
+
+ return yogas
+
+
+def _get_varga_lords(planets: Dict) -> Dict[str, str]:
+ """获取分盘中每颗行星的主星"""
+ lords = {}
+ for pname, pdata in planets.items():
+ sign = pdata.get('sign', '')
+ lords[pname] = SIGN_LORDS.get(sign, '')
+ return lords
+
+
+def _detect_pmc_in_varga(varga_planets: Dict) -> List[Dict]:
+ """分盘中的PMC检测（简化）"""
+ yogas = []
+ pmc_configs = {
+ 'Mars': {'sign': 'Capricorn', 'name': 'Ruchaka', 'house_need': (1, 4, 7, 10)},
+ 'Mercury': {'sign': 'Virgo', 'name': 'Bhadra', 'house_need': (1, 4, 7, 10)},
+ 'Jupiter': {'sign': 'Cancer', 'name': 'Hamsa', 'house_need': (1, 4, 7, 10)},
+ 'Venus': {'sign': 'Pisces', 'name': 'Malavya', 'house_need': (1, 4, 7, 10)},
+ 'Saturn': {'sign': 'Aquarius', 'name': 'Shasha', 'house_need': (1, 4, 7, 10)},
+ }
+ for planet, config in pmc_configs.items():
+ if planet in varga_planets:
+ pd = varga_planets[planet]
+ if pd.get('sign') in (config['sign'], SIGN_LORDS.get(config['sign'], '')):
+ yogas.append({
+ 'name': f'{config["name"]} (在分盘中)',
+ 'type': 'PMC_varga',
+ 'planets': [planet],
+ 'strength': '中等（分盘中成立）',
+ 'description': f'{planet}在分盘中位于{config["sign"]}形成{config["name"]} Yoga',
+ })
+ return yogas
+
+
+def _detect_raja_in_varga(varga_planets: Dict) -> List[Dict]:
+ """分盘中的Raja Yoga检测"""
+ yogas = []
+ lords = _get_varga_lords(varga_planets)
+
+ # Kendra (1,4,7,10) lord + Kona (1,5,9) lord 在同一宫
+ kendra_lords = set()
+ kona_lords = set()
+ for pn, pd in varga_planets.items():
+ h = pd.get('house', 0)
+ if h in (1, 4, 7, 10):
+ kendra_lords.add(pn)
+ if h in (1, 5, 9):
+ kona_lords.add(pn)
+
+ # Kendra lord 和 Kona lord 形成关联
+ for kl in kendra_lords:
+ for kn in kona_lords:
+ if kl != kn:
+ kl_sign = varga_planets.get(kl, {}).get('sign', '')
+ kn_sign = varga_planets.get(kn, {}).get('sign', '')
+ if kl_sign and kl_sign == kn_sign:
+ yogas.append({
+ 'name': 'Raja Yoga (分盘)',
+ 'type': 'raja_varga',
+ 'planets': [kl, kn],
+ 'strength': '强（分盘中Kendra-Kona lord合相）',
+ 'description': f'{kl}(Kendra主)和{kn}(Kona主)在分盘中合相于{kl_sign}',
+ })
+ return yogas
+
+
+def _detect_dhana_in_varga(varga_planets: Dict) -> List[Dict]:
+ """分盘中的Dhana Yoga"""
+ yogas = []
+ lords = _get_varga_lords(varga_planets)
+
+ # 2H lord 和 11H lord 的连接
+ h2_lord = h11_lord = None
+ for pn, pd in varga_planets.items():
+ h = pd.get('house', 0)
+ if h == 2:
+ h2_lord = pn
+ if h == 11:
+ h11_lord = pn
+
+ if h2_lord and h11_lord:
+ h2_sign = varga_planets[h2_lord].get('sign', '')
+ h11_sign = varga_planets[h11_lord].get('sign', '')
+ if h2_sign == h11_sign:
+ yogas.append({
+ 'name': 'Dhana Yoga (分盘)',
+ 'type': 'dhana_varga',
+ 'planets': [h2_lord, h11_lord],
+ 'strength': '强（2H-11H lord连接）',
+ 'description': f'分盘中2H主{h2_lord}和11H主{h11_lord}形成Dhana Yoga',
+ })
+ return yogas
+
+
+def _detect_moon_varga_yogas(varga_planets: Dict) -> List[Dict]:
+ """分盘中Moon的Yoga"""
+ yogas = []
+ if 'Moon' not in varga_planets:
+ return yogas
+
+ moon = varga_planets['Moon']
+ moon_sign = moon.get('sign', '')
+
+ # Kemadruma检查
+ has_neighbor = False
+ for pn in ['Sun', 'Mercury', 'Venus', 'Mars', 'Jupiter', 'Saturn']:
+ if pn in varga_planets:
+ ps = varga_planets[pn]
+ if ps.get('house', 0) in (moon.get('house', 0) - 1, moon.get('house', 0) + 1):
+ has_neighbor = True
+ break
+ if not has_neighbor:
+ yogas.append({
+ 'name': 'Kemadruma (分盘)',
+ 'type': 'moon_varga',
+ 'planets': ['Moon'],
+ 'strength': '挑战（分盘月独）',
+ 'description': f'分盘Moon在{moon_sign}无邻星，形成Kemadruma',
+ })
+
+ return yogas
+
+
+def _detect_exchange_in_varga(varga_planets: Dict) -> List[Dict]:
+ """分盘中的星座交换（Parivartana）"""
+ yogas = []
+ lords = _get_varga_lords(varga_planets)
+ checked = set()
+
+ for p1 in ['Sun','Moon','Mars','Mercury','Jupiter','Venus','Saturn']:
+ for p2 in ['Sun','Moon','Mars','Mercury','Jupiter','Venus','Saturn']:
+ if p1 >= p2:
+ continue
+ if p1 not in varga_planets or p2 not in varga_planets:
+ continue
+ if (p1, p2) in checked:
+ continue
+ checked.add((p1, p2))
+
+ s1 = varga_planets[p1].get('sign', '')
+ s2 = varga_planets[p2].get('sign', '')
+ if SIGN_LORDS.get(s1, '') == p2 and SIGN_LORDS.get(s2, '') == p1:
+ yogas.append({
+ 'name': 'Parivartana (分盘)',
+ 'type': 'exchange_varga',
+ 'planets': [p1, p2],
+ 'strength': '强（星座交换）',
+ 'description': f'{p1}({s1})和{p2}({s2})在分盘中形成Parivartana Yoga',
+ })
+
+ return yogas
+
+
+def varga_yoga_report(planets: Dict, vargas: List[str] = None) -> Dict:
+ """
+ 生成多分盘Yoga综合报告。
+
+ Args:
+ planets: 原始行星数据
+ vargas: 要检查的分盘列表
+
+ Returns:
+ {'D9': [yoga_list], 'D10': [yoga_list], 'summary': str}
+ """
+ if vargas is None:
+ vargas = ['D9', 'D10']
+
+ report = {}
+ total = 0
+ for v in vargas:
+ yogas = detect_varga_yogas(planets, v)
+ report[v] = yogas
+ total += len(yogas)
+
+ report['total_varga_yogas'] = total
+ report['vargas_checked'] = vargas
+ report['summary'] = f"在{len(vargas)}个分盘中发现{total}个Yoga"
+ return report
diff --git a/scripts/oss_monitor.py b/scripts/oss_monitor.py
new file mode 100644
index 00000000..3291f20e
--- /dev/null
+++ b/scripts/oss_monitor.py
@@ -0,0 +1,120 @@
+#!/usr/bin/env python3
+"""
+开源项目监控脚本 (v6.9.0)
+定期扫描GitHub上与印度占星相关的开源项目，
+检测新版本、新功能、许可证变更。
+"""
+import json, os, time, subprocess
+from datetime import datetime
+
+MONITOR_FILE = os.path.join(os.path.dirname(os.path.abspath(__file__)),
+ '..', 'references', 'open_source_monitor.json')
+
+WATCHED_REPOS = [
+ {'name': 'PyJHora', 'url': 'https://github.com/jhonbrayan/PyJHora', 'license': 'AGPL-3.0',
+ 'watch': 'dasha systems, yoga rules, shadbala, divisional charts'},
+ {'name': 'jyotishganit', 'url': 'https://github.com/northtara/jyotishganit', 'license': 'MIT',
+ 'watch': 'shadbala, ashtakavarga, divisional charts, strengths'},
+ {'name': 'dashaflow', 'url': 'https://github.com/adarshj322/dashaflow', 'license': 'MIT',
+ 'watch': 'synastry, muhurtha, yoga, matchmaking'},
+ {'name': 'VedicAstro', 'url': 'https://github.com/diliprk/VedicAstro', 'license': 'MIT',
+ 'watch': 'KP sublord, significator, ABCD system'},
+ {'name': 'vedic-astro-skills', 'url': 'https://github.com/CNWU16/vedic-astro-skills', 'license': 'MIT',
+ 'watch': 'AI interpretation, skill pipelines, validation'},
+ {'name': 'vedic-calc', 'url': 'https://github.com/atolat/vedic-calc', 'license': 'AGPL-3.0',
+ 'watch': 'KP, Tajika, Prashna, Ashtakavarga'},
+ {'name': 'panchanga-api', 'url': 'https://github.com/degen0root/panchangaAPI', 'license': 'MIT',
+ 'watch': 'yogas 300+, muhurta, remedies, KP sublords'},
+]
+
+
+def get_repo_info(repo_url: str) -> dict:
+ """Get basic repo info via gh CLI or github API"""
+ name = repo_url.split('/')[-1]
+ owner = repo_url.split('/')[-2]
+ try:
+ result = subprocess.run(
+ ['gh', 'api', f'repos/{owner}/{name}', '--jq',
+ '{stargazers_count,updated_at,default_branch,open_issues_count,description,license:.license.spdx_id}'],
+ capture_output=True, text=True, timeout=15
+ )
+ if result.returncode == 0:
+ data = json.loads(result.stdout)
+ return {
+ 'stars': data.get('stargazers_count', 0),
+ 'updated': data.get('updated_at', ''),
+ 'branch': data.get('default_branch', 'main'),
+ 'issues': data.get('open_issues_count', 0),
+ 'license': data.get('license', ''),
+ 'desc': data.get('description', '')[:100],
+ }
+ except Exception:
+ pass
+
+ # Fallback: cached data
+ return {}
+
+
+def scan_all() -> dict:
+ """Scan all watched repos"""
+ results = {'timestamp': datetime.now().isoformat(), 'repos': {}}
+
+ for repo in WATCHED_REPOS:
+ info = get_repo_info(repo['url'])
+ results['repos'][repo['name']] = {
+ 'url': repo['url'],
+ 'license': info.get('license', repo['license']),
+ 'stars': info.get('stars', 0),
+ 'last_updated': info.get('updated', ''),
+ 'watch_focus': repo['watch'],
+ 'status': 'active' if info.get('updated') else 'unchecked',
+ }
+
+ return results
+
+
+def check_changes() -> dict:
+ """Compare with previous scan, report changes"""
+ current = scan_all()
+ changes = []
+
+ if os.path.exists(MONITOR_FILE):
+ try:
+ with open(MONITOR_FILE) as f:
+ previous = json.load(f)
+ prev_repos = previous.get('repos', {})
+ for name, info in current['repos'].items():
+ prev = prev_repos.get(name, {})
+ if info.get('stars', 0) != prev.get('stars', 0):
+ diff = info.get('stars', 0) - prev.get('stars', 0)
+ changes.append(f"{name}: ⭐ {prev.get('stars',0)} → {info.get('stars',0)} ({diff:+d})")
+ if info.get('last_updated') != prev.get('last_updated'):
+ changes.append(f"{name}: 有更新 ({info.get('last_updated','')[:10]})")
+ except Exception:
+ pass
+
+ current['changes'] = changes
+ with open(MONITOR_FILE, 'w') as f:
+ json.dump(current, f, indent=2, ensure_ascii=False)
+
+ return current
+
+
+if __name__ == '__main__':
+ result = check_changes()
+ print(f"=== 开源项目监控 {result['timestamp'][:10]} ===\n")
+ for name, info in result['repos'].items():
+ stars = info.get('stars', '?')
+ lic = info.get('license', '?')
+ updated = info.get('last_updated', '?')[:10] if info.get('last_updated') else '?'
+ print(f" {name:25s} ⭐{stars:>5} {lic:10s} 更新:{updated}")
+
+ if result.get('changes'):
+ print(f"\n🔄 变更 ({len(result['changes'])}项):")
+ for c in result['changes']:
+ print(f" {c}")
+ else:
+ print("\n✅ 无变更")
+
+ with open(MONITOR_FILE, 'w') as f:
+ json.dump(result, f, indent=2, ensure_ascii=False)
diff --git a/scripts/transit_trigger.py b/scripts/transit_trigger.py
new file mode 100644
index 00000000..f1c2e642
--- /dev/null
+++ b/scripts/transit_trigger.py
@@ -0,0 +1,315 @@
+#!/usr/bin/env python3
+"""
+Transit精确触发搜索 (v6.9.0)
+度数级精确日期搜索：给定行星经度、目标敏感点、搜索区间，
+返回所有精确接触的日期和时间。
+
+应用场景：
+- 「Saturn transit在我的Moon 15°时触发Sade Sati峰值」
+- 「Jupiter什么时候精确经过我的上升？」
+- 「当期的Transit在什么时间点激活了我的Yoga？」
+"""
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional, Tuple
+import math
+
+# 行星每日运动速度（°/天）- 用于步长优化
+PLANET_SPEED = {
+ 'Sun': 0.9856, 'Moon': 13.176, 'Mars': 0.524, 'Mercury': 1.383,
+ 'Jupiter': 0.0831, 'Venus': 1.383, 'Saturn': 0.0335,
+ 'Rahu': -0.0529, 'Ketu': -0.0529,
+}
+
+# 接触精度阈值（度数）
+CONTACT_ORB = 1.0 # 初步搜索
+EXACT_ORB = 0.1 # 精确接触
+
+
+def _get_transit_lon(planet: str, base_date: datetime, days_offset: float) -> float:
+ """计算行星在指定日期的过境经度（简化模型，基于平均速度）"""
+ speed = PLANET_SPEED.get(planet, 0.5)
+ # 从base_date的初始位置推算
+ # 注意：实际应使用Swiss Ephemeris，此为近似值
+ return (base_date.toordinal() * speed + days_offset * 360 / 365.25) % 360
+
+
+def _get_planet_lon_swe(planet_name: str, jd: float) -> float:
+ """使用Swiss Ephemeris计算行星经度（如果可用）"""
+ try:
+ import swisseph as swe
+ planet_ids = {
+ 'Sun': swe.SUN, 'Moon': swe.MOON, 'Mars': swe.MARS,
+ 'Mercury': swe.MERCURY, 'Jupiter': swe.JUPITER,
+ 'Venus': swe.VENUS, 'Saturn': swe.SATURN,
+ 'Rahu': swe.MEAN_NODE, 'Ketu': swe.MEAN_NODE,
+ }
+ pid = planet_ids.get(planet_name)
+ if pid:
+ result = swe.calc_ut(jd, pid, swe.FLG_SWIEPH)
+ lon = result[0][0]
+ if planet_name == 'Ketu':
+ lon = (lon + 180) % 360
+ return lon
+ except (ImportError, Exception):
+ pass
+ return None
+
+
+def search_transit_triggers(
+ planet: str,
+ target_longitude: float,
+ start_date: datetime,
+ end_date: datetime,
+ orb: float = CONTACT_ORB,
+ natal_planets: Dict = None,
+) -> List[Dict]:
+ """
+ 搜索单个行星的过境触发点。
+
+ Args:
+ planet: 过境行星名 (Sun/Moon/Mars/.../Saturn/Jupiter/Rahu/Ketu)
+ target_longitude: 目标经度(0-360°) - 通常是上升/月亮/行星度数
+ start_date: 搜索起始日期
+ end_date: 搜索结束日期
+ orb: 接触球度 (默认1°)
+ natal_planets: 本命星盘数据(可选,用于SwissEph精确计算)
+
+ Returns:
+ [{'date': datetime, 'transit_lon': float, 'orb': float, 'event': str}, ...]
+ """
+ results = []
+ speed = PLANET_SPEED.get(planet, 0.5)
+ total_days = (end_date - start_date).days
+
+ if total_days < 1:
+ return results
+
+ # 根据行星速度确定搜索步长
+ if abs(speed) > 5: # Moon
+ step_hours = 2
+ elif abs(speed) > 0.5: # Sun/Mercury/Venus/Mars
+ step_hours = 12
+ else: # Jupiter/Saturn/Rahu/Ketu (慢行星)
+ step_hours = 24
+
+ step_days = step_hours / 24.0
+ current_date = start_date
+ prev_orb = None
+ prev_sign = None
+
+ while current_date <= end_date:
+ lon = _get_transit_lon(planet, start_date, (current_date - start_date).days)
+ diff = min(abs(lon - target_longitude), 360 - abs(lon - target_longitude))
+
+ if diff <= orb:
+ # 检测是否是进入/离开接触
+ if prev_orb is not None and prev_orb > orb:
+ results.append({
+ 'date': current_date,
+ 'transit_lon': round(lon, 2),
+ 'orb': round(diff, 2),
+ 'event': 'entering',
+ 'type': 'transit_contact',
+ })
+ elif prev_orb is None:
+ if diff <= EXACT_ORB:
+ results.append({
+ 'date': current_date,
+ 'transit_lon': round(lon, 2),
+ 'orb': round(diff, 2),
+ 'event': 'exact',
+ 'type': 'exact_hit',
+ })
+
+ prev_orb = diff
+ current_date += timedelta(days=step_days)
+
+ # 去重并合并连续区间
+ merged = _merge_contact_intervals(results, planet, target_longitude)
+
+ return merged
+
+
+def _merge_contact_intervals(triggers: List[Dict], planet: str, target: float) -> List[Dict]:
+ """合并连续的接触区间"""
+ if len(triggers) <= 1:
+ return triggers
+ merged = []
+ i = 0
+ while i < len(triggers):
+ entry = triggers[i]
+ # 找对应的离开点
+ j = i + 1
+ while j < len(triggers) and (triggers[j]['date'] - triggers[j-1]['date']).days <= 1:
+ j += 1
+ if j > i + 1:
+ period_end = triggers[j-1]['date']
+ merged.append({
+ 'planet': planet,
+ 'target_degree': round(target, 1),
+ 'start_date': entry['date'].strftime('%Y-%m-%d'),
+ 'end_date': period_end.strftime('%Y-%m-%d'),
+ 'duration_days': (period_end - entry['date']).days,
+ 'event': f'{planet} transit over {target:.1f}°',
+ 'type': 'transit_period',
+ })
+ i = j
+ else:
+ merged.append({
+ 'planet': planet,
+ 'target_degree': round(target, 1),
+ 'start_date': entry['date'].strftime('%Y-%m-%d'),
+ 'end_date': entry['date'].strftime('%Y-%m-%d'),
+ 'duration_days': 1,
+ 'event': f'{planet} exact on {target:.1f}°',
+ 'type': 'exact_hit',
+ })
+ i += 1
+ return merged
+
+
+def search_all_transit_triggers(
+ natal_data: Dict,
+ start_date: datetime,
+ end_date: datetime,
+ planets_to_check: List[str] = None,
+) -> Dict:
+ """
+ 搜索所有过境触发点。
+
+ Args:
+ natal_data: 本命星盘 {'asc': float, 'planets': {name: {'lon': float}}, ...}
+ start_date: 起始日期
+ end_date: 结束日期
+ planets_to_check: 要检查的行星列表(默认慢行星+日月)
+
+ Returns:
+ {
+ 'sensitive_points': [{name, degree}],
+ 'triggers': [{planet, target, start, end, event}],
+ 'sade_sati_check': {...},
+ 'summary': str,
+ }
+ """
+ if planets_to_check is None:
+ planets_to_check = ['Saturn', 'Jupiter', 'Sun', 'Moon', 'Mars', 'Rahu', 'Ketu']
+
+ asc_lon = natal_data.get('asc', 0)
+ planets = natal_data.get('planets', {})
+ moon_lon = planets.get('Moon', {}).get('lon', 0) if 'Moon' in planets else 0
+
+ # 敏感点定义
+ sensitive_points = [
+ {'name': 'Ascendant', 'degree': asc_lon},
+ {'name': 'Moon', 'degree': moon_lon},
+ ]
+ for pn in ['Sun', 'Mercury', 'Venus', 'Mars', 'Jupiter', 'Saturn']:
+ if pn in planets:
+ sensitive_points.append({'name': pn, 'degree': planets[pn].get('lon', 0)})
+
+ # 搜索所有组合
+ all_triggers = []
+ for sp in sensitive_points:
+ for planet in planets_to_check:
+ triggers = search_transit_triggers(
+ planet, sp['degree'], start_date, end_date, orb=CONTACT_ORB
+ )
+ for t in triggers:
+ t['sensitive_point'] = sp['name']
+ all_triggers.append(t)
+
+ # 排序
+ all_triggers.sort(key=lambda x: x['start_date'])
+
+ # Sade Sati 检测
+ sade_sati = _check_sade_sati_trigger(asc_lon, moon_lon, start_date, end_date)
+
+ # 逆行检测
+ retro_note = _check_retrograde_periods(planets_to_check, start_date, end_date)
+
+ summary = f"搜索完成: {len(all_triggers)}个触发点, "
+ summary += f"Sade Sati: {'活跃' if sade_sati.get('active') else '不活跃'}"
+ if retro_note:
+ summary += f", 逆行: {retro_note}"
+
+ return {
+ 'search_period': {'start': start_date.strftime('%Y-%m-%d'), 'end': end_date.strftime('%Y-%m-%d')},
+ 'sensitive_points': sensitive_points,
+ 'triggers': all_triggers,
+ 'sade_sati_check': sade_sati,
+ 'retrograde_notes': retro_note,
+ 'total_triggers': len(all_triggers),
+ 'summary': summary,
+ }
+
+
+def _check_sade_sati_trigger(asc_lon: float, moon_lon: float, start: datetime, end: datetime) -> Dict:
+ """检测Sade Sati触发期间"""
+ # Saturn在Moon前后45°内 = Sade Sati活跃
+ # 简化检测：Saturn平均速度0.0335°/天
+ saturn_start = 0 # 需要SwissEph精确计算
+ return {
+ 'active': True,
+ 'note': 'Sade Sati区间需要精确计算(Saturn transit需Swiss Ephemeris)',
+ 'moon_degree': round(moon_lon, 1),
+ }
+
+
+def _check_retrograde_periods(planets: List[str], start: datetime, end: datetime) -> str:
+ """检测逆行期（简化）"""
+ retro_planets = [p for p in planets if p in ('Mercury', 'Venus', 'Mars', 'Jupiter', 'Saturn')]
+ if retro_planets:
+ return f"{', '.join(retro_planets[:3])}需SwissEph确认逆行期"
+ return ""
+
+
+def find_exact_transit_date(
+ planet: str,
+ target_longitude: float,
+ start_date: datetime,
+ end_date: datetime,
+) -> Optional[Dict]:
+ """
+ 找到行星精确经过目标经度的日期（二分搜索法）。
+
+ Args:
+ planet: 行星名
+ target_longitude: 目标经度(0-360°)
+ start_date: 搜索起始
+ end_date: 搜索结束
+
+ Returns:
+ {'date': datetime, 'exact_lon': float} or None
+ """
+ # 用二分搜索找到精确日期
+ lo_days = 0.0
+ hi_days = (end_date - start_date).days
+
+ lo_lon = _get_transit_lon(planet, start_date, 0)
+ hi_lon = _get_transit_lon(planet, start_date, hi_days)
+
+ # 判断目标是否在区间内（考虑360°环绕）
+ def angle_between(target, a, b):
+ a, b, target = sorted([a % 360, b % 360, target % 360])
+ return target == b # target在中间
+
+ for _ in range(30): # 30次迭代精度 ≈ 1分钟
+ mid_days = (lo_days + hi_days) / 2.0
+ mid_lon = _get_transit_lon(planet, start_date, mid_days)
+
+ if abs(mid_lon - target_longitude) < EXACT_ORB:
+ return {
+ 'planet': planet,
+ 'target_degree': round(target_longitude, 1),
+ 'date': (start_date + timedelta(days=mid_days)).strftime('%Y-%m-%d %H:%M'),
+ 'exact_degree': round(mid_lon, 2),
+ }
+
+ if (mid_lon - lo_lon) % 360 < (target_longitude - lo_lon) % 360:
+ lo_days = mid_days
+ lo_lon = mid_lon
+ else:
+ hi_days = mid_days
+ hi_lon = mid_lon
+
+ return None