732642856
f83db2fac1
- add external validation reports and open-source comparison references - integrate Jaimini arudha/graha pada, enhanced argala, and additional synastry kutas - update skill docs and capability matrices - add smoke tests for open-source integrations
258 lines
8.7 KiB
Python
258 lines
8.7 KiB
Python
"""
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Pytest fixtures for jyotishganit testing.
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Provides diverse birth data fixtures covering:
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- Different timezone offsets and locations
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- Various time periods (1900s, 2000s, present)
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- Geographic diversity (hemispheres, latitudes)
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- Edge cases for astrological calculations
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"""
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from datetime import datetime
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import pytest
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from jyotishganit.core.models import Person
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from jyotishganit.main import calculate_birth_chart
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# =============================================================================
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# GEOGRAPHIC AND TIMEZONE FIXTURES
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# =============================================================================
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@pytest.fixture
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def test_locations():
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"""Dictionary of diverse test locations with coordinates and timezones."""
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return {
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"mumbai": {"lat": 19.0760, "lon": 72.8777, "tz": 5.5}, # IST
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"delhi": {"lat": 28.6139, "lon": 77.2090, "tz": 5.5}, # IST
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"london": {"lat": 51.5074, "lon": -0.1278, "tz": 0.0}, # GMT/BST
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"nyc": {"lat": 40.7128, "lon": -74.0060, "tz": -4.0}, # EDT (simplified)
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"tokyo": {"lat": 35.6762, "lon": 139.6503, "tz": 9.0}, # JST
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"sydney": {"lat": -33.8688, "lon": 151.2093, "tz": 11.0}, # AEDT
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"capetown": {"lat": -33.9249, "lon": 18.4241, "tz": 2.0}, # SAST
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"anchorage": {"lat": 61.2181, "lon": -149.9003, "tz": -9.0}, # AKDT
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}
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# =============================================================================
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# BIRTH DATA FIXTURES - DIVERSE TIMEFRAMES
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# =============================================================================
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@pytest.fixture
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def birth_1900s():
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"""Early 20th century birth data."""
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return [
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# 1900: Start of 20th century
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Person(datetime(1900, 1, 1, 12, 0, 0), 19.0760, 72.8777, 5.5, "Mumbai1900"),
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# 1950s: Mid-century
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Person(datetime(1955, 6, 15, 6, 30, 0), 28.6139, 77.2090, 5.5, "Delhi1955"),
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# 1990s: Late century before millennium
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Person(datetime(1995, 12, 31, 23, 59, 0), 51.5074, -0.1278, 0.0, "London1995"),
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]
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@pytest.fixture
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def birth_2000s():
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"""21st century birth data."""
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return [
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# Y2K and early 2000s
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Person(datetime(2000, 1, 1, 0, 0, 1), 35.6762, 139.6503, 9.0, "Tokyo2000"),
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Person(datetime(2005, 7, 4, 13, 45, 0), 40.7128, -74.0060, -4.0, "NYC2005"),
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# Late 2000s to present
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Person(datetime(2010, 3, 21, 9, 15, 0), -33.8688, 151.2093, 10.0, "Sydney2010"),
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Person(
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datetime(2020, 5, 10, 16, 20, 0), -33.9249, 18.4241, 2.0, "CapeTown2020"
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),
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]
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@pytest.fixture
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def birth_edge_cases():
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"""Edge cases for astronomical calculations."""
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return [
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# High latitude (near poles)
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Person(
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datetime(2015, 12, 21, 12, 0, 0), -77.85, 166.67, 12.0, "Antarctica"
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), # McMurdo
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Person(
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datetime(2015, 6, 21, 12, 0, 0), 78.22, 15.63, 2.0, "Svalbard"
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), # Longyearbyen
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# Equinox/Solstice births
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Person(
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datetime(2021, 3, 20, 21, 37, 0), 40.7128, -74.0060, -4.0, "Equinox"
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), # Vernal
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Person(
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datetime(2021, 12, 21, 5, 59, 0), 40.7128, -74.0060, -5.0, "Solstice"
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), # Winter
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# Leap year edges
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Person(datetime(2020, 2, 29, 23, 59, 0), 51.5074, -0.1278, 0.0, "LeapYear"),
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Person(datetime(1900, 3, 1, 0, 0, 1), 51.5074, -0.1278, 0.0, "NonLeapCentury"),
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]
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@pytest.fixture
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def birth_timezone_variety():
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"""Birth data with fractional timezone offsets."""
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return [
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Person(
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datetime(2015, 8, 15, 10, 30, 0), 40.7128, -74.0060, -4.5, "ET_Minus45"
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), # EST with DST
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Person(
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datetime(2015, 8, 15, 15, 45, 0), 51.5074, -0.1278, 1.0, "LondonBST"
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), # BST
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Person(
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datetime(2015, 8, 15, 22, 15, 0), 19.0760, 72.8777, 5.5, "MumbaiIST"
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), # IST
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Person(
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datetime(2015, 8, 15, 8, 45, 0), 35.6762, 139.6503, 9.0, "TokyoJST"
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), # JST
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]
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# =============================================================================
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# PRE-COMPUTED CHART FIXTURES
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# =============================================================================
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@pytest.fixture
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def sample_vedic_chart_delhi():
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"""Pre-computed chart for Delhi, 1994 - useful for manual verification."""
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birth = datetime(1994, 10, 23, 10, 20, 0) # Nashik coordinates from test_ganita.py
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return calculate_birth_chart(birth, 19.9993, 73.7900, 5.5)
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@pytest.fixture
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def sample_vedic_chart_london():
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"""Pre-computed chart for London."""
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birth = datetime(1985, 5, 15, 14, 30, 0)
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return calculate_birth_chart(birth, 51.5074, -0.1278, 1.0) # BST equivalent
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@pytest.fixture
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def sample_vedic_chart_nyc():
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"""Pre-computed chart for NYC."""
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birth = datetime(2007, 9, 11, 8, 46, 0) # 9/11
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return calculate_birth_chart(birth, 40.7128, -74.0060, -4.0) # EDT
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# =============================================================================
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# EXPECTED VALUES FOR MANUAL VERIFICATION
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# =============================================================================
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@pytest.fixture
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def expected_ashtakavarga_benchmarks():
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"""Expected Ashtakavarga bindu values for validation against classical texts."""
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return {
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"sun_bav_total": 48, # Sun should sum to 48 bindus across retrograde path
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"moon_bav_total": 49, # Moon should sum to 49 bindus
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"mars_bav_total": 39, # Mars should sum to 39 bindus
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"mercury_bav_total": 54, # Mercury should sum to 54 bindus
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"jupiter_bav_total": 56, # Jupiter should sum to 56 bindus
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"venus_bav_total": 52, # Venus should sum to 52 bindus
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"saturn_bav_total": 39, # Saturn should sum to 39 bindus
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}
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@pytest.fixture
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def expected_shadbala_ranges():
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"""Expected ranges for planetary strength validations."""
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return {
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"minimum_shadbala": 200.0, # Theoretical minimum shadbala
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"maximum_shadbala": 600.0, # Theoretical maximum shadbala
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"exalted_sun_range": (450.0, 500.0), # Sun in Leo
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"exalted_moon_range": (450.0, 500.0), # Moon in Taurus
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"debilitated_sun_range": (180.0, 220.0), # Sun in Aquarius
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"debilitated_moon_range": (200.0, 250.0), # Moon in Scorpio
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}
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@pytest.fixture
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def expected_dasha_start_ages():
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"""Expected Vimshottari dasha start ages for common charts."""
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return {
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"sun_dasha_start_age": (0, 6),
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"moon_dasha_start_age": (0, 10),
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"mars_dasha_start_age": (28, 38),
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"mercury_dasha_start_age": (0, 17),
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"jupiter_dasha_start_age": (16, 26),
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"venus_dasha_start_age": (0, 20),
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"saturn_dasha_start_age": (43, 49),
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}
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# =============================================================================
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# PARAMETRIC FIXTURES
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# =============================================================================
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@pytest.fixture(
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params=[
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# Indian locations (IST +5.5)
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("Mumbai", 19.0760, 72.8777, 5.5),
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("Delhi", 28.6139, 77.2090, 5.5),
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("Chennai", 13.0827, 80.2707, 5.5),
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("Kolkata", 22.5726, 88.3639, 5.5),
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("Bangalore", 12.9716, 77.5946, 5.5),
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]
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)
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def indian_location(request):
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"""Parametric fixture for Indian cities."""
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name, lat, lon, tz = request.param
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return {"name": name, "lat": lat, "lon": lon, "tz": tz}
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@pytest.fixture(
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params=[
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# Western locations
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("London", 51.5074, -0.1278, 0.0),
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("New York", 40.7128, -74.0060, -5.0),
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("Los Angeles", 34.0522, -118.2437, -8.0),
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("Berlin", 52.5200, 13.4050, 1.0),
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("Paris", 48.8566, 2.3522, 1.0),
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("Rome", 41.9028, 12.4964, 1.0),
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("Moscow", 55.7558, 37.6173, 3.0),
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]
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)
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def western_location(request):
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"""Parametric fixture for Western cities."""
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name, lat, lon, tz = request.param
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return {"name": name, "lat": lat, "lon": lon, "tz": tz}
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@pytest.fixture(
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params=[
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# Eastern/Pacific locations
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("Tokyo", 35.6762, 139.6503, 9.0),
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("Sydney", -33.8688, 151.2093, 11.0),
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("Shanghai", 31.2304, 121.4737, 8.0),
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("Seoul", 37.5665, 126.9780, 9.0),
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("Bangkok", 13.7563, 100.5018, 7.0),
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]
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)
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def asian_pacific_location(request):
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"""Parametric fixture for Asian/Pacific cities."""
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name, lat, lon, tz = request.param
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return {"name": name, "lat": lat, "lon": lon, "tz": tz}
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@pytest.fixture(
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params=[
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datetime(1900, 1, 1),
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datetime(1950, 6, 15),
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datetime(1975, 12, 25),
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datetime(2000, 1, 1),
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datetime(2005, 7, 4),
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datetime(2010, 3, 21),
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datetime(2015, 8, 15),
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datetime(2020, 5, 10),
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datetime(2023, 12, 31),
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]
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)
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def historical_birth_year(request):
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"""Parametric fixture for various birth years."""
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birth_date = request.param
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return birth_date.replace(hour=12, minute=0, second=0) # Standardize time
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