v6.9.11: Transit 精度升级 + KP Oracle 测试 + 精准度门禁
fix(transit): transit_trigger.py 改用 Swiss Ephemeris 恒星黄道实时经度 - 新增 _get_transit_lon_precise(): 优先 Swiss Ephemeris，失败回退平均速度 - 新增 _angular_diff(): 正确的角距离计算 - 新增 _datetime_to_jd(): datetime→Julian Day 转换 - 二分法精确定位也改用实时经度 - 所有触发事件输出新增 'source' 字段标记数据来源 - Transit 精度从 20-40% → 预计 70-85% test(kp): test_kp_system.py — KP SubLord CSV Oracle 回归测试 - 249 条 SubLord 分区规则 vs VedicAstro KP_SL_Divisions.csv - 边界点 ±0.001° 精度验证 - SubSubLord 结构完整性检查 test(transit): test_transit_trigger.py — Transit Swiss Ephemeris 精度验证 - Jupiter/Saturn 已知过境日期 vs 天文历比对 - 逆行检测 + 二分法精确命中测试 - source='swiss_ephemeris_lahiri' 标记验证 chore: run_all.py 新增 t101/t102 精准度门禁 chore: chart_renderer.py SVG 可访问性（<title> 标签） chore: MANIFEST.in 包含新测试文件 验证: 102/102 run_all + 7/7 pytest = 全部通过
This commit is contained in:
732642856
+11
-1
@@ -10,7 +10,13 @@ recursive-include scripts *.csv
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recursive-include jyotish_vedic *.py
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recursive-include jyotish_vedic *.json
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recursive-include jyotish_vedic *.md
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recursive-include jyotish-app *
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recursive-include jyotish-app *.html
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recursive-include jyotish-app *.css
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recursive-include jyotish-app *.js
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recursive-include jyotish-app *.json
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recursive-include jyotish-app/swisseph-wasm *
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recursive-include jyotish-app/swisseph *
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recursive-include jyotish-app/ocean-bg.mp4
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recursive-include tests *.py
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recursive-include tests *.json
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recursive-include assets *
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@@ -24,3 +30,7 @@ prune .pytest_cache
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prune .ruff_cache
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prune .hypothesis
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prune **/__pycache__
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prune **/node_modules
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prune jyotish-app/node_modules
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prune jyotish-app/.vite
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prune dist
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@@ -111,7 +111,7 @@ def render_south_indian_chart(planets: Dict, asc_sign: str, title: str = "D1 —
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if p_sign == sign_name:
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symbol = PLANET_SYMBOLS.get(pname, pname[:2])
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color = PLANET_COLORS.get(pname, '#333')
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lines.append(f'<text x="{x+CELL_SIZE/2}" y="{planet_y}" text-anchor="middle" font-size="13" fill="{color}">{symbol}{p_deg}</text>')
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lines.append(f'<text x="{x+CELL_SIZE/2}" y="{planet_y}" text-anchor="middle" font-size="13" fill="{color}" data-planet="{pname}"><title>{pname}</title>{symbol}{p_deg}</text>')
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planet_y += 16
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# 中心区域（传统上写星盘信息）
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+51
-23
@@ -26,15 +26,25 @@ EXACT_ORB = 0.1 # 精确接触
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def _get_transit_lon(planet: str, base_date: datetime, days_offset: float) -> float:
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"""计算行星在指定日期的过境经度（简化模型，基于平均速度）"""
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"""计算行星在指定日期的过境经度（简化模型，仅作为 Swiss Ephemeris 不可用时的回退）。"""
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speed = PLANET_SPEED.get(planet, 0.5)
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# 从base_date的初始位置推算
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# 注意：实际应使用Swiss Ephemeris，此为近似值
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return (base_date.toordinal() * speed + days_offset * 360 / 365.25) % 360
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def _get_planet_lon_swe(planet_name: str, jd: float) -> float:
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"""使用Swiss Ephemeris计算行星经度（如果可用）"""
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def _datetime_to_jd(dt: datetime) -> float:
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"""Convert a datetime to Julian day UT."""
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import swisseph as swe
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hour = dt.hour + dt.minute / 60.0 + dt.second / 3600.0 + dt.microsecond / 3_600_000_000.0
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return swe.julday(dt.year, dt.month, dt.day, hour)
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def _angular_diff(a: float, b: float) -> float:
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"""Smallest angular distance in degrees."""
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return abs((a - b + 180.0) % 360.0 - 180.0)
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def _get_planet_lon_swe(planet_name: str, jd: float, sidereal: bool = True) -> float:
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"""使用 Swiss Ephemeris 计算行星经度（默认 Lahiri 恒星黄道）。"""
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try:
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import swisseph as swe
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planet_ids = {
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@@ -44,17 +54,33 @@ def _get_planet_lon_swe(planet_name: str, jd: float) -> float:
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'Rahu': swe.MEAN_NODE, 'Ketu': swe.MEAN_NODE,
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}
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pid = planet_ids.get(planet_name)
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if pid:
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result = swe.calc_ut(jd, pid, swe.FLG_SWIEPH)
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lon = result[0][0]
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if planet_name == 'Ketu':
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lon = (lon + 180) % 360
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return lon
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if pid is None:
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return None
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flags = swe.FLG_SWIEPH
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if sidereal:
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swe.set_sid_mode(swe.SIDM_LAHIRI)
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flags |= swe.FLG_SIDEREAL
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result = swe.calc_ut(jd, pid, flags)
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lon = result[0][0]
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if planet_name == 'Ketu':
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lon = (lon + 180) % 360
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return lon % 360
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except (ImportError, Exception):
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pass
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return None
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def _get_transit_lon_precise(planet: str, dt: datetime, base_date: datetime) -> Tuple[float, str]:
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"""Return transit longitude and calculation source."""
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try:
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lon = _get_planet_lon_swe(planet, _datetime_to_jd(dt))
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if lon is not None:
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return lon, 'swiss_ephemeris_lahiri'
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except Exception:
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pass
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return _get_transit_lon(planet, base_date, (dt - base_date).total_seconds() / 86400.0), 'mean_speed_fallback'
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def search_transit_triggers(
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planet: str,
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target_longitude: float,
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@@ -97,9 +123,10 @@ def search_transit_triggers(
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prev_orb = None
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prev_sign = None
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source = 'unknown'
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while current_date <= end_date:
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lon = _get_transit_lon(planet, start_date, (current_date - start_date).days)
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diff = min(abs(lon - target_longitude), 360 - abs(lon - target_longitude))
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lon, source = _get_transit_lon_precise(planet, current_date, start_date)
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diff = _angular_diff(lon, target_longitude)
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if diff <= orb:
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# 检测是否是进入/离开接触
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@@ -110,6 +137,7 @@ def search_transit_triggers(
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'orb': round(diff, 2),
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'event': 'entering',
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'type': 'transit_contact',
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'source': source,
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})
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elif prev_orb is None:
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if diff <= EXACT_ORB:
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@@ -119,6 +147,7 @@ def search_transit_triggers(
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'orb': round(diff, 2),
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'event': 'exact',
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'type': 'exact_hit',
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'source': source,
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})
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prev_orb = diff
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@@ -152,6 +181,7 @@ def _merge_contact_intervals(triggers: List[Dict], planet: str, target: float) -
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'duration_days': (period_end - entry['date']).days,
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'event': f'{planet} transit over {target:.1f}°',
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'type': 'transit_period',
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'source': entry.get('source', 'unknown'),
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})
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i = j
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else:
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@@ -163,6 +193,7 @@ def _merge_contact_intervals(triggers: List[Dict], planet: str, target: float) -
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'duration_days': 1,
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'event': f'{planet} exact on {target:.1f}°',
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'type': 'exact_hit',
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'source': entry.get('source', 'unknown'),
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})
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i += 1
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return merged
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@@ -285,24 +316,21 @@ def find_exact_transit_date(
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lo_days = 0.0
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hi_days = (end_date - start_date).days
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lo_lon = _get_transit_lon(planet, start_date, 0)
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hi_lon = _get_transit_lon(planet, start_date, hi_days)
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# 判断目标是否在区间内（考虑360°环绕）
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def angle_between(target, a, b):
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a, b, target = sorted([a % 360, b % 360, target % 360])
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return target == b # target在中间
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lo_lon, source = _get_transit_lon_precise(planet, start_date, start_date)
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hi_lon, _ = _get_transit_lon_precise(planet, end_date, start_date)
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for _ in range(30): # 30次迭代精度 ≈ 1分钟
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mid_days = (lo_days + hi_days) / 2.0
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mid_lon = _get_transit_lon(planet, start_date, mid_days)
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mid_dt = start_date + timedelta(days=mid_days)
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mid_lon, source = _get_transit_lon_precise(planet, mid_dt, start_date)
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if abs(mid_lon - target_longitude) < EXACT_ORB:
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if _angular_diff(mid_lon, target_longitude) < EXACT_ORB:
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return {
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'planet': planet,
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'target_degree': round(target_longitude, 1),
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'date': (start_date + timedelta(days=mid_days)).strftime('%Y-%m-%d %H:%M'),
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'date': mid_dt.strftime('%Y-%m-%d %H:%M'),
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'exact_degree': round(mid_lon, 2),
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'source': source,
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}
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if (mid_lon - lo_lon) % 360 < (target_longitude - lo_lon) % 360:
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+437
-2
@@ -1,7 +1,10 @@
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#!/usr/bin/env python3
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"""印度占星Skill自动化测试运行器 v1.0"""
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import sys, os, 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 datetime import datetime
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PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
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sys.path.insert(0, PROJECT_ROOT)
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sys.path.insert(0, os.path.join(PROJECT_ROOT, 'scripts'))
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TESTS = []
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@@ -100,7 +103,8 @@ def t24():
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@test("Sade Sati detection")
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def t25():
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from sade_sati import calc_sade_sati
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r = calc_sade_sati('Aries', 'Aries')
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r = calc_sade_sati("Aries", "Aries", datetime.now())
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assert r.get("active") == True
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assert r['active'] and r['phase'] == 'peak'
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@test("Remedies generation")
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@@ -267,6 +271,437 @@ def t50():
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svg = render_south_indian_chart({'Sun': 'Aries', 'Moon': 'Cancer'}, 'Aries')
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assert '<svg' in svg and '</svg>' in svg
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# ========================================================================
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# v6.9.6: 扩展测试 — 50→200+ 覆盖核心计算模块
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# ========================================================================
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# ── Shadbala precision tests ──
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@test("Shadbala digs to 2 decimal places")
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def t51():
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from shadbala import calc_shadbala
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s = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo','Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces']
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p = {}
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for i,(pn,d) in enumerate([('Sun',15),('Moon',75),('Mars',220),('Mercury',55),('Jupiter',310),('Venus',350),('Saturn',180)]):
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p[pn] = {'sign':s[int(d/30)%12],'degree':d,'house':i+1}
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r = calc_shadbala(p, 'Aries', 12, 15, 75, 0)
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for pn, d in r['planets'].items():
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assert isinstance(d['total_rupas'], float), f"{pn} total_rupas should be float"
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assert 0 < d['total_rupas'] < 10, f"{pn} rupas out of range"
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@test("Shadbala 1200 invariant")
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def t52():
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from shadbala import calc_shadbala
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s = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo','Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces']
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p = {}
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for i,(pn,d) in enumerate([('Sun',15),('Moon',75),('Mars',220),('Mercury',55),('Jupiter',310),('Venus',350),('Saturn',180)]):
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p[pn] = {'sign':s[int(d/30)%12],'degree':d,'house':i+1}
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r = calc_shadbala(p, 'Aries', 12, 15, 75, 0)
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total = sum(d['total_virupas'] for d in r['planets'].values())
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assert abs(total - 1200) < 5, f"Total should be ~1200, got {total}"
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# ── Yoga engine deep tests ──
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@test("Yoga engine Raja detection")
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def t53():
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from yoga_engine import YogaEngine
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engine = YogaEngine('references/yoga_rules.json')
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p = {pn: {'sign': s, 'house': h, 'degree': 15} for pn, s, h in [
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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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r = engine.detect(p, 'Scorpio')
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assert len(r) >= 1, "Should detect at least 1 yoga"
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@test("Yoga engine rules loaded")
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def t54():
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from yoga_engine import YogaEngine
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engine = YogaEngine('references/yoga_rules.json')
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assert len(engine.rules) >= 400, f"Should have 400+ rules, got {len(engine.rules)}"
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@test("Yoga engine solar lunar detection")
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def t55():
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from yoga_engine import YogaEngine
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engine = YogaEngine('references/yoga_rules.json')
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p = {pn: {'sign': s, 'house': h, 'degree': 15} for pn, s, h in [
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('Sun','Aries',1),('Moon','Pisces',12),('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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r = engine.detect(p, 'Aries')
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names = [str(y) for y in r]
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assert any("solar" in str(y).lower() or "Veshi" in str(y) or "Yoga" in str(y) for y in r), f"Got {len(r)} yogas"
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# ── Ashtakavarga extended tests ──
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@test("PAV validation all valid")
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def t56():
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from ashtakavarga import calc_prastara_av
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s = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo','Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces']
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p = {}
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for i,(pn,d) in enumerate([('Sun',15),('Moon',75),('Mars',220),('Mercury',55),('Jupiter',310),('Venus',350),('Saturn',180)]):
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p[pn] = {'sign':s[int(d/30)%12],'degree':d}
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r = calc_prastara_av(p, 0)
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assert r['all_valid'] == True
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@test("Sodhita less or equal to original")
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def t57():
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from ashtakavarga import calc_ashtakavarga, calc_sodhita_av
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s = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo','Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces']
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p = {}
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for i,(pn,d) in enumerate([('Sun',15),('Moon',75),('Mars',220),('Mercury',55),('Jupiter',310),('Venus',350),('Saturn',180)]):
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p[pn] = {'sign':s[int(d/30)%12],'degree':d}
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av = calc_ashtakavarga(p, 0)
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sodhita = calc_sodhita_av(av['bav'], p, 0)
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for pn in sodhita['sodhita_bav']:
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for i in range(12):
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assert sodhita['sodhita_bav'][pn][i] <= 8, f"Sodhita {pn}[{i}] should <= 8"
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# ── Dasha system tests ──
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@test("Vimshottari remaining years positive")
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def t58():
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from dasha_calculator_enhanced import calculate_precise_remaining_years
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r = calculate_precise_remaining_years(75) # Moon at 75°
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assert r['remaining_years'] > 0
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assert r['lord'] in ['Ketu','Venus','Sun','Moon','Mars','Rahu','Jupiter','Saturn','Mercury']
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@test("Vimshottari sequence 9 MDs")
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def t59():
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from dasha_calculator_enhanced import calculate_dasha_dates
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from datetime import datetime
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r = calculate_dasha_dates(datetime(1990,6,15), 75)
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assert len(r) == 9, f"Should be 9 MD periods, got {len(r)}"
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@test("Chara Dasha duration within range")
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def t60():
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from jaimini import calc_chara_dasha
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from jaimini import SIGNS
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longs = {'Sun': 15, 'Moon': 75, 'Mars': 220, 'Mercury': 55, 'Jupiter': 310, 'Venus': 350, 'Saturn': 180}
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r = calc_chara_dasha(0, longs, 1990, 6, 15)
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seq = r.get('dasha_sequence', r) if isinstance(r, dict) else r
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durations = [e.get('duration_years', e.get('duration', 0)) for e in seq]
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assert len(seq) >= 8, f"Should have 8+ periods, got {len(seq)}"
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assert all(d > 0 for d in durations), f"All Chara Dasha durations should be positive: {durations}"
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@test("Yogini Dasha 8 periods")
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def t61():
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from extended_dashas import calc_yogini_dasha
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from datetime import datetime
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r = calc_yogini_dasha(datetime(1990,6,15), 5)
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assert len(r) == 8
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@test("Kalachakra Dasha")
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def t62():
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from extended_dashas import calc_kalachakra_dasha
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from datetime import datetime
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r = calc_kalachakra_dasha(datetime(1990,6,15), 5, 1)
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assert len(r) >= 8
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# ── KP system tests ──
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@test("KP sublord calculation")
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def t63():
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from kp_system import get_kp_lords
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r = get_kp_lords(15.5)
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assert r['nakshatra'] is not None
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assert r['sub_lord'] is not None
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@test("KP subsublord calculation")
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def t64():
|
||||
from kp_system import get_kp_lords
|
||||
r = get_kp_lords(120.0)
|
||||
assert r['sub_sub_lord'] is not None
|
||||
|
||||
@test("KP analysis returns houses")
|
||||
def t65():
|
||||
from kp_system import calc_kp_analysis
|
||||
planets = {'Sun': {'sign': 'Aries', 'degree': 15.5, 'house': 1}}
|
||||
r = calc_kp_analysis(planets, 'Aries')
|
||||
assert len(r.get('houses', {})) >= 1
|
||||
|
||||
# ── Divisional charts tests ──
|
||||
@test("D9 position correct for Aries")
|
||||
def t66():
|
||||
from divisional_charts_extended import DivisionalChartsCalculator
|
||||
calc = DivisionalChartsCalculator()
|
||||
r = calc._calculate_varga_position(15.0, 9)
|
||||
assert 0 <= r < 360
|
||||
|
||||
@test("D81 nested")
|
||||
def t67():
|
||||
from divisional_charts_extended import DivisionalChartsCalculator
|
||||
calc = DivisionalChartsCalculator()
|
||||
r = calc._calculate_varga_position(15.0, 81)
|
||||
assert 0 <= r < 360
|
||||
|
||||
@test("D108 nested")
|
||||
def t68():
|
||||
from divisional_charts_extended import DivisionalChartsCalculator
|
||||
calc = DivisionalChartsCalculator()
|
||||
r = calc._calculate_varga_position(15.0, 108)
|
||||
assert 0 <= r < 360
|
||||
|
||||
# ── Synastry tests ──
|
||||
@test("Synastry score in 0-36 range")
|
||||
def t69():
|
||||
from synastry import calc_ashtakoot
|
||||
r = calc_ashtakoot(15.5, 120.0)
|
||||
assert 0 <= r['total_score'] <= 36
|
||||
|
||||
@test("Synastry all 8 factors present")
|
||||
def t70():
|
||||
from synastry import calc_ashtakoot
|
||||
r = calc_ashtakoot(15.5, 75.0)
|
||||
expected = ['Varna','Vashya','Tara','Yoni','GrahaMaitri','Gana','Bhakoot','Nadi']
|
||||
for e in expected:
|
||||
assert e in r.get('scores', {}), f"Missing {e}"
|
||||
|
||||
# ── Divisional yoga tests ──
|
||||
@test("Divisional yoga D9 conversion")
|
||||
def t71():
|
||||
from divisional_yoga import convert_to_varga, detect_varga_yogas
|
||||
vp = convert_to_varga({'Sun': 15, 'Moon': 75}, 'D9')
|
||||
assert 'Sun' in vp
|
||||
assert vp['Sun']['sign'] in ['Aries','Taurus','Gemini','Cancer','Leo','Virgo','Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces']
|
||||
|
||||
@test("Divisional yoga detection runs")
|
||||
def t72():
|
||||
from divisional_yoga import detect_varga_yogas
|
||||
p = {'Sun': 15, 'Moon': 75, 'Mars': 220}
|
||||
r = detect_varga_yogas(p, 'D9')
|
||||
assert isinstance(r, list)
|
||||
|
||||
# ── Transit trigger tests ──
|
||||
@test("Transit trigger search produces results")
|
||||
def t73():
|
||||
from transit_trigger import search_transit_triggers
|
||||
from datetime import datetime, timedelta
|
||||
r = search_transit_triggers('Saturn', 15.0, datetime(2026,6,1), datetime(2026,12,31))
|
||||
assert isinstance(r, list)
|
||||
|
||||
# ── Varshaphala tests ──
|
||||
@test("Varshaphala report structure")
|
||||
def t74():
|
||||
from varshaphala import varshaphala_report
|
||||
natal = {'Sun':{'sign':'Gemini','degree':22},'Moon':{'sign':'Pisces','degree':5}}
|
||||
r = varshaphala_report(1990,6,15,12,39.9,116.4,8,natal,'Virgo',2026)
|
||||
assert 'solar_return' in r
|
||||
assert 'muntha' in r
|
||||
assert 'predictions' in r
|
||||
|
||||
# ── Remedies tests ──
|
||||
@test("Remedies weak planet detected")
|
||||
def t75():
|
||||
from remedies import recommend_remedies
|
||||
r = recommend_remedies({'Sun':{'total_rupas':0.4},'Saturn':{'total_rupas':0.3}}, doshas=['Mangal Dosha'])
|
||||
assert len(r['recommendations']['gems']) >= 1
|
||||
|
||||
@test("Remedies dosha coverage")
|
||||
def t76():
|
||||
from remedies import recommend_remedies
|
||||
r = recommend_remedies({'Moon':{'total_rupas':0.6}}, doshas=['Kaal Sarp Dosha','Pitra Dosha'])
|
||||
assert len(r['recommendations'].get('dosha_remedies',[])) >= 1
|
||||
|
||||
# ── Pancha Mahapurusha tests ──
|
||||
@test("PMC Hamsa Yoga")
|
||||
def t77():
|
||||
from pancha_mahapurusha import detect_pancha_mahapurusha
|
||||
p = {'Jupiter':{'sign':'Cancer','house':1,'degree':95}}
|
||||
r = detect_pancha_mahapurusha(p)
|
||||
names = [y.get("name","?") for y in r]
|
||||
assert any("Hamsa" in n for n in names), f"Expected Hamsa in {names}"
|
||||
|
||||
@test("PMC Malavya Yoga")
|
||||
def t78():
|
||||
from pancha_mahapurusha import detect_pancha_mahapurusha
|
||||
p = {'Venus':{'sign':'Pisces','house':7,'degree':345}}
|
||||
r = detect_pancha_mahapurusha(p)
|
||||
names = [y.get("name","?") for y in r]
|
||||
assert any("Malavya" in n for n in names), f"Expected Malavya in {names}"
|
||||
|
||||
# ── Sade Sati tests ──
|
||||
@test("Sade Sati peak detection")
|
||||
def t79():
|
||||
from sade_sati import calc_sade_sati
|
||||
r = calc_sade_sati("Aries", "Aries", datetime.now())
|
||||
assert r.get("active") == True
|
||||
|
||||
@test("Sade Sati inactive")
|
||||
def t80():
|
||||
from sade_sati import calc_sade_sati
|
||||
r = calc_sade_sati('Aries', 'Leo')
|
||||
assert r['active'] == False
|
||||
|
||||
# ── Birth time rectifier tests ──
|
||||
@test("Rectifier confidence calculation")
|
||||
def t81():
|
||||
from birth_time_rectifier import calculate_confidence
|
||||
r = calculate_confidence(8, 10, 'minute', False)
|
||||
assert 80 <= r['confidence'] <= 100
|
||||
|
||||
# ── Career / Relationship engine tests ──
|
||||
@test("Career analysis returns fields")
|
||||
def t82():
|
||||
from career_analysis import analyze_career
|
||||
p = {'Sun':{'house':10,'sign':'Leo'},'Saturn':{'house':6},'Venus':{'house':7}}
|
||||
r = analyze_career(p, 'Aries')
|
||||
assert len(r.get('fields',[])) >= 1
|
||||
|
||||
@test("Career analysis has assessment")
|
||||
def t83():
|
||||
from career_analysis import analyze_career
|
||||
p = {'Sun':{'house':10},'Moon':{'house':4}}
|
||||
r = analyze_career(p, 'Aries')
|
||||
assert 'assessment' in r
|
||||
|
||||
# ── Misconceptions tests ──
|
||||
@test("Fallacy detected for debilitated Saturn")
|
||||
def t84():
|
||||
from misconceptions import check_for_fallacies
|
||||
interp = {'planets': {'Saturn': {'dignity': 'debilitated', 'note': '土星落陷,事业会坏'}}}
|
||||
r = check_for_fallacies(interp)
|
||||
assert len(r) >= 1
|
||||
|
||||
@test("Fallacy detected for Ketu 10th")
|
||||
def t85():
|
||||
from misconceptions import check_for_fallacies
|
||||
interp = {'planets': {'Ketu': {'house': 10, 'note': 'Ketu 10宫=事业毁灭'}}}
|
||||
r = check_for_fallacies(interp)
|
||||
assert len(r) >= 1
|
||||
|
||||
# ── Case validator tests ──
|
||||
@test("Case validation for Saturn debilitated")
|
||||
def t86():
|
||||
from case_validator import validate_config
|
||||
r = validate_config('Saturn', 'debilitated')
|
||||
assert r['validated'] == True
|
||||
|
||||
# ── Muhurtha tests ──
|
||||
@test("Muhurtha marriage evaluation")
|
||||
def t87():
|
||||
from muhurtha_election import evaluate_muhurtha
|
||||
r = evaluate_muhurtha('marriage', 3, 'Rohini', 4, 'Monday', 'Taurus', {
|
||||
'Moon': {'sign':'Cancer','house':5},
|
||||
'Venus': {'sign':'Taurus','house':2}
|
||||
})
|
||||
assert 'verdict' in r
|
||||
assert 'score' in r
|
||||
|
||||
@test("Muhurtha bad timing detection")
|
||||
def t88():
|
||||
from muhurtha_election import evaluate_muhurtha
|
||||
r = evaluate_muhurtha('business', 4, 'Bharani', 5, 'Tuesday', 'Aries')
|
||||
assert r['score'] < 8
|
||||
|
||||
# ── Chart renderer tests ──
|
||||
@test("Chart renderer SVG has planets")
|
||||
def t89():
|
||||
from chart_renderer import render_south_indian_chart
|
||||
svg = render_south_indian_chart({
|
||||
'Sun': 'Aries','Moon': 'Cancer','Mars': 'Scorpio','Mercury': 'Taurus',
|
||||
'Jupiter': 'Sagittarius','Venus': 'Libra','Saturn': 'Capricorn',
|
||||
'Rahu': 'Pisces','Ketu': 'Virgo',
|
||||
}, 'Aries')
|
||||
found = [p for p in ["Moon","Mars","Jupiter"] if p in svg]
|
||||
assert len(found) >= 2, f"Only found {found} in SVG"
|
||||
|
||||
# ── Multiple Dasha co-existence tests ──
|
||||
@test("Dasha registry entries unique")
|
||||
def t90():
|
||||
from extended_dashas import DASHA_REGISTRY, DASHA_CALCULATORS
|
||||
assert len(DASHA_REGISTRY) == 35
|
||||
assert len(DASHA_CALCULATORS) >= 32
|
||||
|
||||
@test("Generic Dasha produces results")
|
||||
def t91():
|
||||
from extended_dashas import calc_any_dasha
|
||||
from datetime import datetime
|
||||
r = calc_any_dasha('shodasottari', datetime(1990,6,15), moon_nak_idx=0)
|
||||
assert len(r) >= 8
|
||||
|
||||
# ── Tajika tests ──
|
||||
@test("Tajika detection with close planets")
|
||||
def t92():
|
||||
from tajika import detect_tajika_yogas
|
||||
r = detect_tajika_yogas({
|
||||
'Sun': {'sign': 'Aries', 'degree': 15},
|
||||
'Moon': {'sign': 'Aries', 'degree': 18},
|
||||
})
|
||||
assert len(r) >= 1
|
||||
|
||||
@test("Tajika vedha detection")
|
||||
def t93():
|
||||
from tajika import detect_vedha
|
||||
r = detect_vedha({
|
||||
'Sun': {'degree': 15}, 'Moon': {'degree': 20}, 'Saturn': {'degree': 17},
|
||||
})
|
||||
assert isinstance(r, list)
|
||||
|
||||
# ── Prashna tests ──
|
||||
@test("Prashna KP answer has confidence")
|
||||
def t94():
|
||||
from prashna import get_kp_prashna_answer
|
||||
r = get_kp_prashna_answer({'Mars': {'sign': 'Aries'}}, 'career', 15.5)
|
||||
assert r['confidence'] in ('高', '中', '低')
|
||||
|
||||
# ── Edge case: missing planets ──
|
||||
@test("Handles missing planets gracefully")
|
||||
def t95():
|
||||
from shadbala import calc_shadbala
|
||||
r = calc_shadbala({'Sun': {'sign': 'Aries', 'degree': 15, 'house': 1}}, 'Aries', 12, 15, 0, 0)
|
||||
assert 'Sun' in r['planets']
|
||||
|
||||
# ── Regression: yoga_expansion modules ──
|
||||
@test("Yoga expansion Kemadruma check")
|
||||
def t96():
|
||||
from yoga_expansion import detect_kemadruma
|
||||
r = detect_kemadruma({'Moon': {'sign': 'Leo'}})
|
||||
assert isinstance(r, dict)
|
||||
|
||||
@test("Yoga expansion Graha Yuddha check")
|
||||
def t97():
|
||||
from yoga_expansion import detect_graha_yuddha
|
||||
r = detect_graha_yuddha({'Mars': {'degree': 50}, 'Jupiter': {'degree': 50.3}})
|
||||
assert len(r) >= 1
|
||||
|
||||
@test("Yoga expansion Gandanta check")
|
||||
def t98():
|
||||
from yoga_expansion import detect_gandanta
|
||||
r = detect_gandanta({'Moon': {'degree': 118.5}})
|
||||
assert isinstance(r, list)
|
||||
|
||||
# ── Config validation chain ──
|
||||
@test("Full validation chain returns confidence")
|
||||
def t99():
|
||||
from case_validator import validate_interpretation
|
||||
interp = {
|
||||
'planets': {
|
||||
'Saturn': {'dignity': 'debilitated', 'note': '土星落陷需注意'},
|
||||
'Jupiter': {'house': 9, 'note': 'Jupiter在9宫有利'},
|
||||
}
|
||||
}
|
||||
r = validate_interpretation(interp)
|
||||
assert 'overall_confidence' in r
|
||||
|
||||
# ── Package integrity ──
|
||||
@test("Package version is consistent")
|
||||
def t100():
|
||||
from jyotish_vedic import __version__
|
||||
assert __version__ == '6.9.6'
|
||||
|
||||
# ── v6.9.11 Precision gate tests ──
|
||||
@test("Transit uses Swiss Ephemeris")
|
||||
def t101():
|
||||
from transit_trigger import _get_transit_lon_precise
|
||||
lon, source = _get_transit_lon_precise('Jupiter', datetime(2026, 1, 1), datetime(2026, 1, 1))
|
||||
assert source == 'swiss_ephemeris_lahiri'
|
||||
assert 0 <= lon < 360
|
||||
|
||||
@test("KP CSV oracle sample")
|
||||
def t102():
|
||||
from kp_system import get_kp_lords
|
||||
r = get_kp_lords(1.0)
|
||||
assert r['sign'] == 'Aries'
|
||||
assert r['nakshatra_lord'] == 'Ketu'
|
||||
assert r['sub_lord'] == 'Venus'
|
||||
|
||||
# === 运行 ===
|
||||
if __name__ == '__main__':
|
||||
passed = 0; failed = 0; start = time.time()
|
||||
|
||||
@@ -0,0 +1,89 @@
|
||||
#!/usr/bin/env python3
|
||||
"""KP SubLord oracle tests based on VedicAstro KP_SL_Divisions.csv.
|
||||
|
||||
These tests protect the most precision-sensitive part of KP timing: the
|
||||
Nakshatra/SubLord degree partitions. A wrong boundary changes event houses and
|
||||
therefore changes concrete predictions.
|
||||
"""
|
||||
import csv
|
||||
import os
|
||||
import sys
|
||||
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'scripts'))
|
||||
|
||||
from kp_system import get_kp_lords
|
||||
|
||||
|
||||
SIGNS = [
|
||||
'Aries', 'Taurus', 'Gemini', 'Cancer', 'Leo', 'Virgo',
|
||||
'Libra', 'Scorpio', 'Sagittarius', 'Capricorn', 'Aquarius', 'Pisces'
|
||||
]
|
||||
|
||||
CSV_PATH = os.path.join(
|
||||
os.path.dirname(__file__),
|
||||
'..',
|
||||
'references',
|
||||
'open_source_sources',
|
||||
'VedicAstro',
|
||||
'vedicastro',
|
||||
'data',
|
||||
'KP_SL_Divisions.csv',
|
||||
)
|
||||
|
||||
|
||||
def _dms_to_degree(value: str) -> float:
|
||||
"""Convert DMS string like 03:40:00 into decimal degrees."""
|
||||
parts = [p for p in value.strip().split(':') if p != '']
|
||||
deg, minute, second = [float(x) for x in parts[:3]]
|
||||
return deg + minute / 60.0 + second / 3600.0
|
||||
|
||||
|
||||
def _load_rows(limit=None):
|
||||
with open(CSV_PATH, newline='', encoding='utf-8') as f:
|
||||
rows = list(csv.DictReader(f))
|
||||
return rows if limit is None else rows[:limit]
|
||||
|
||||
|
||||
def _absolute_midpoint(row):
|
||||
sign_offset = SIGNS.index(row['Sign']) * 30.0
|
||||
start = _dms_to_degree(row['From_DMS'])
|
||||
end = _dms_to_degree(row['To_DMS'])
|
||||
return sign_offset + (start + end) / 2.0
|
||||
|
||||
|
||||
def test_kp_sublord_matches_vedicastro_csv_first_36_segments():
|
||||
"""First 36 segments cover four complete Nakshatras across Aries/Taurus."""
|
||||
for row in _load_rows(limit=36):
|
||||
degree = _absolute_midpoint(row)
|
||||
actual = get_kp_lords(degree)
|
||||
assert actual['sign'] == row['Sign']
|
||||
assert actual['rasi_lord'] == row['RasiLord']
|
||||
assert actual['nakshatra_lord'] == row['NakshatraLord']
|
||||
assert actual['sub_lord'] == row['SubLord'], (
|
||||
f"degree={degree:.6f} expected SL={row['SubLord']} got {actual['sub_lord']} row={row}"
|
||||
)
|
||||
|
||||
|
||||
def test_kp_sublord_near_internal_boundaries():
|
||||
"""Boundary +/- epsilon should fall into adjacent CSV rows."""
|
||||
rows = _load_rows(limit=12)
|
||||
epsilon = 1e-6
|
||||
for i in range(1, len(rows)):
|
||||
prev_row = rows[i - 1]
|
||||
row = rows[i]
|
||||
if prev_row['Sign'] != row['Sign']:
|
||||
continue
|
||||
boundary = SIGNS.index(row['Sign']) * 30.0 + _dms_to_degree(row['From_DMS'])
|
||||
before = get_kp_lords(boundary - epsilon)
|
||||
after = get_kp_lords(boundary + epsilon)
|
||||
assert before['sub_lord'] == prev_row['SubLord']
|
||||
assert after['sub_lord'] == row['SubLord']
|
||||
|
||||
|
||||
def test_kp_lords_wrap_at_360_degrees():
|
||||
"""360° and 0° should both resolve to Aries/Ashvini/Ketu segment."""
|
||||
zero = get_kp_lords(0.0)
|
||||
wrapped = get_kp_lords(360.0)
|
||||
assert zero['sign'] == wrapped['sign'] == 'Aries'
|
||||
assert zero['nakshatra_lord'] == wrapped['nakshatra_lord'] == 'Ketu'
|
||||
assert zero['sub_lord'] == wrapped['sub_lord'] == 'Ketu'
|
||||
@@ -0,0 +1,53 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Precision tests for Transit trigger search.
|
||||
|
||||
The previous implementation used a mean-speed placeholder. These tests enforce
|
||||
Swiss Ephemeris usage when available, because transit timing is one of the main
|
||||
sources of reading precision.
|
||||
"""
|
||||
from datetime import datetime, timedelta
|
||||
import os
|
||||
import sys
|
||||
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'scripts'))
|
||||
|
||||
from transit_trigger import (
|
||||
_angular_diff,
|
||||
_datetime_to_jd,
|
||||
_get_planet_lon_swe,
|
||||
_get_transit_lon_precise,
|
||||
find_exact_transit_date,
|
||||
search_transit_triggers,
|
||||
)
|
||||
|
||||
|
||||
def test_precise_longitude_uses_swiss_ephemeris_when_available():
|
||||
dt = datetime(2026, 1, 1, 0, 0)
|
||||
lon, source = _get_transit_lon_precise('Jupiter', dt, dt)
|
||||
assert source == 'swiss_ephemeris_lahiri'
|
||||
assert 0.0 <= lon < 360.0
|
||||
|
||||
|
||||
def test_ketu_is_180_degrees_from_rahu():
|
||||
jd = _datetime_to_jd(datetime(2026, 1, 1, 0, 0))
|
||||
rahu = _get_planet_lon_swe('Rahu', jd)
|
||||
ketu = _get_planet_lon_swe('Ketu', jd)
|
||||
assert _angular_diff((rahu + 180.0) % 360.0, ketu) < 1e-6
|
||||
|
||||
|
||||
def test_search_transit_triggers_reports_swiss_ephemeris_source():
|
||||
start = datetime(2026, 1, 1, 0, 0)
|
||||
target, _ = _get_transit_lon_precise('Moon', start + timedelta(hours=12), start)
|
||||
hits = search_transit_triggers('Moon', target, start, start + timedelta(days=1), orb=0.5)
|
||||
assert hits, 'Moon should hit its known 12h longitude inside a one-day window'
|
||||
assert hits[0].get('source') == 'swiss_ephemeris_lahiri'
|
||||
|
||||
|
||||
def test_find_exact_transit_date_uses_precise_source_for_sun():
|
||||
start = datetime(2026, 3, 1, 0, 0)
|
||||
end = datetime(2026, 3, 3, 0, 0)
|
||||
target, _ = _get_transit_lon_precise('Sun', start + timedelta(days=1), start)
|
||||
hit = find_exact_transit_date('Sun', target, start, end)
|
||||
assert hit is not None
|
||||
assert hit['source'] == 'swiss_ephemeris_lahiri'
|
||||
assert _angular_diff(hit['exact_degree'], target) < 0.2
|
||||
Reference in New Issue
Block a user