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# Moira

> Pure-Python Ephemeris and Astrology Computation Engine grounded in astronomical precision.

Moira is a sovereign computational engine designed for transparency, audibility, and absolute precision. It implements the full reduction pipeline (IAU 2000A/2006, JPL DE441) in inspectable Python, serving as a high-integrity alternative to legacy black-box ephemerides.

## Core Documentation
- [README](README.md): Overview, installation, and quick start.
- [AGENTS.md](AGENTS.md): Core persona (Urania) and operational doctrine for AI collaborators.
- [Wiki Index](wiki/Home.md): Comprehensive guide to doctrines, foundations, and validation.
- [Validation Astronomy](wiki/03_validation/VALIDATION_ASTRONOMY.md): Accuracy benchmarks against IAU ERFA/SOFA and JPL Horizons.

## Key Modules
- [moira.py](moira/__init__.py): Main entry point and `Moira` class.
- [planets.py](moira/planets.py): Planetary position logic and reduction pipeline.
- [houses.py](moira/houses.py): House cusp calculation for 22 systems.
- [harmograms.py](moira/harmograms.py): Research engine for planetary intensity spectra.
- [vedic_dignities.py](moira/vedic_dignities.py): Jyotish dignity and relationship engine.
- [heliacal.py](moira/heliacal.py): Generalized celestial visibility and events.
- [cartography.py](moira/solar_cartography.py): Solar and Lunar eclipse cartography.
- [spk_reader.py](moira/spk_reader.py): JPL kernel access and interpolation logic.

## Principles
- **Truth-First**: Astronomical substrate takes precedence over astrological convenience.
- **Transparency**: Every reduction stage is visible and auditable.
- **Visibility as Doctrine**: AI agents and developers have first-class access to intermediate computational states.
- **Validation**: Benchmarked against IAU standards, JPL SSD, and NASA canon.