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Technical Documentation
Complete reference for the Geometric Flow Cathedral optimization pipeline, including API specifications, configuration guides, and implementation details.
01 Overview
The Geometric Flow Cathedral implements a novel approach to traffic optimization by integrating geometric constraints into machine learning pipelines. The system leverages:
- √14 Ratchet Decay: A decay factor derived from the square root of 14, applied to prevent overfitting and ensure smooth convergence.
- 24-Fold Geometric Filtering: Temporal filtering based on prime spoke hours (1, 5, 7, 11, 13, 17, 19, 23) to capture cyclical traffic patterns.
- 19.1° Phase Correction: Standing wave phase offset at 46.875Hz for sensor data synchronization.
02 Installation
bash
# Clone the repository
git clone https://github.com/google/geometric-flow-cathedral.git
cd geometric-flow-cathedral
# Install dependencies
pip install -r requirements.txt
# Configure environment variables
cp .env.example .env
# Initialize the pipeline
python -m gfc init03 Configuration
| Parameter | Type | Default | Description |
|---|---|---|---|
| RATchet_DECAY | float | 0.267 | 1 - 1/√14 decay factor |
| PHASE_OFFSET | float | 19.1 | Phase correction in degrees |
| PRIME_SPOKES | list | [1,5,7,11,13,17,19,23] | Active temporal filtering hours |
| CONSTRAINT_BLEND | float | 0.5 | Geometric constraint weight (0-1) |
04 API Reference
POST /api/v1/optimize
StableSubmit traffic data for real-time geometric optimization.
{
"sensor_data": {
"flow_rate": 120.5,
"timestamp": "2024-01-15T14:30:00Z",
"location_id": "intersection_42"
},
"constraints": {
"apply_ratchet": true,
"phase_correction": 19.1
}
}