golden-float 0.1.0

Phi-structured floating-point formats for ML and scientific computing

GoldenFloat Python Bindings

Phi-structured floating-point formats for machine learning and scientific computing.

Installation

pip install golden-float

Quick Start

import numpy as np
from golden_float import gf16, gf32

# Create GoldenFloat values
phi = gf16(1.618)
pi = gf32(3.14159)

# Convert to float
print(phi.to_float())  # 1.618

# Arithmetic
result = phi + phi

# NumPy array support (with dtype registration)
arr = np.array([1.0, 1.618, 2.718], dtype=gf16)

Format Reference

Format	Bits	Use Case	Memory vs f32
GF4	4	Ultra-compact quantization	12.5%
GF8	8	Minimal precision	25%
GF12	12	Embedded ML	37.5%
GF16	16	Primary format (replaces bfloat16)	50%
GF20	20	Balanced	62.5%
GF24	24	High precision	75%
GF32	32	Full precision (same size as f32)	100%

License

MIT