Ultra-lightweight spatial mathematics library with optimized negative number support
Project description
spatialmath
Lightweight spatial math library (NumPy only): 3D cube matrix conversion driven by spatial structure
An ultra-lightweight spatial math library with optimized negative number support. Ideal for edge computing, embedded systems, and educational use cases.
Core Features
- Extreme Performance: Core code is only 385 lines
- Minimal Dependencies: Only relies on NumPy (≥1.21.0)
- Optimized Negative Numbers: Optimized encoding logic with <5% extra overhead
- Production-Ready: Complete type hints and comprehensive unit tests
- Edge Computing Optimization: Manual cache management for memory-sensitive environments
- Version Compatibility: Supports Python 3.8+ (compatible with older Python versions)
Installation
From Source (Recommended)
git clone https://github.com/HhMaozy/spatialmath.git
cd spatialmath
# Import directly without additional installation
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