Metadata-Version: 2.4
Name: rapidgeo
Version: 0.2.5
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Rust
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: numpy>=1.19.0 ; extra == 'numpy'
Provides-Extra: numpy
Summary: Fast geographic and planar distance calculations with Python bindings
Keywords: distance,geodesic,haversine,vincenty,geometry,gis
Home-Page: https://github.com/gaker/rapidgeo
Author: gaker
License: MIT OR Apache-2.0
Requires-Python: >=3.8
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Homepage, https://github.com/gaker/rapidgeo
Project-URL: Repository, https://github.com/gaker/rapidgeo
Project-URL: Documentation, https://rapidgeo.readthedocs.io/
Project-URL: Issues, https://github.com/gaker/rapidgeo/issues

# rapidgeo

[![PyPI](https://img.shields.io/pypi/v/rapidgeo.svg)](https://pypi.org/project/rapidgeo/)
[![Documentation](https://img.shields.io/badge/docs-rapidgeo-blue.svg)](https://rapidgeo.readthedocs.io/)
[![License](https://img.shields.io/badge/license-MIT%20OR%20Apache--2.0-blue.svg)](LICENSE)

Geographic calculations for Python: distance calculations, polyline encoding/decoding, line simplification, and curve similarity measures.

## Installation

```bash
pip install rapidgeo          # Base package
pip install rapidgeo[numpy]   # With NumPy support
```

## Quick Start

```python
from rapidgeo import LngLat
from rapidgeo.distance.geo import haversine

# Create coordinates (longitude, latitude) - multiple formats supported
sf = LngLat.new_deg(-122.4194, 37.7749)   # LngLat object
nyc = (-74.0060, 40.7128)                  # Tuple (lng, lat)
la = [-118.2437, 34.0522]                  # List [lng, lat]

# Calculate distance
distance = haversine(sf, nyc)
print(f"Distance: {distance / 1000:.1f} km")  # ~4,130 km
```

## What it does

**Distance Calculations:**
- Haversine: Spherical Earth approximation, good for most uses
- Vincenty: Ellipsoidal Earth model for higher precision
- Euclidean: Flat plane calculations
- Batch operations for multiple points
- NumPy array support for vectorized operations

**Polyline Encoding/Decoding:**
- Google Polyline Algorithm implementation
- Compress coordinate sequences to text strings
- Configurable precision levels

**Line Simplification:**
- Douglas-Peucker algorithm
- Reduce point count while preserving shape
- Configurable distance tolerance

**Curve Similarity:**
- Fréchet distance: Compare trajectories (point order matters)
- Hausdorff distance: Compare shapes (point order doesn't matter)  
- Useful for GPS track analysis and route comparison

## Coordinate System

All coordinates use **longitude, latitude** ordering (lng, lat):

```python
# Correct
point = LngLat.new_deg(-122.4194, 37.7749)  # lng first, lat second

# Common mistake
# point = LngLat.new_deg(37.7749, -122.4194)  # lat, lng - WRONG
```

## Usage Examples

**Compare GPS Tracks:**
```python
from rapidgeo.similarity.frechet import discrete_frechet

# Two similar walking routes
route_a = [LngLat.new_deg(-122.419, 37.775), LngLat.new_deg(-122.418, 37.776)]
route_b = [LngLat.new_deg(-122.419, 37.775), LngLat.new_deg(-122.417, 37.777)]

similarity = discrete_frechet(route_a, route_b)
print(f"Routes differ by {similarity:.1f} meters")
```

**Simplify GPS Tracks:**
```python
from rapidgeo.simplify import douglas_peucker

# Reduce GPS track complexity
detailed_track = [LngLat.new_deg(-122.4, 37.7), LngLat.new_deg(-122.39, 37.71), ...]
simplified = douglas_peucker(detailed_track, tolerance=10.0)  # 10m tolerance
print(f"Reduced from {len(detailed_track)} to {len(simplified)} points")
```

**Encode/Decode Polylines:**
```python
from rapidgeo.polyline import encode, decode

# Compress GPS data - supports multiple coordinate formats
points = [
    LngLat.new_deg(-122.4, 37.7),  # LngLat objects
    (-122.3, 37.8),                 # Tuples
    [-122.2, 37.9],                 # Lists
]
encoded = encode(points, precision=5)
decoded = decode(encoded, precision=5)
```

**NumPy Batch Operations:**
```python
import numpy as np
from rapidgeo.numpy import pairwise_haversine, path_length_haversine

# High-performance vectorized operations
lng = np.array([-122.4, -122.3, -122.2])
lat = np.array([37.7, 37.8, 37.9])

# Calculate distances between consecutive points
distances = pairwise_haversine(lng, lat)

# Total path length
total_distance = path_length_haversine(lng, lat)
print(f"Total: {total_distance / 1000:.1f} km")
```

## License

Licensed under either of [Apache License, Version 2.0](LICENSE-APACHE) or [MIT License](LICENSE-MIT) at your option.
