Installation¶

Prerequisites¶

Python 3.10 or later
pip package manager

Stable release¶

Install the core package from PyPI:

pip install aurora-glm

This installs Aurora-GLM with NumPy and SciPy – sufficient for all GLM, GAM, and Gaussian GAMM workflows.

Optional dependencies¶

Aurora-GLM supports multiple computational backends and additional features through optional dependencies:

Extra	Install command	Provides
PyTorch GPU	`pip install aurora-glm[torch]`	GPU acceleration via CUDA (up to 141x speedup)
JAX	`pip install aurora-glm[jax]`	JAX arrays and JIT compilation
Bayesian	`pip install aurora-glm[bayesian]`	Bayesian inference module
Development	`pip install aurora-glm[dev]`	pytest, ruff, mypy
Everything	`pip install aurora-glm[all]`	All of the above

From source¶

To install the latest development version:

git clone https://github.com/Matcraft94/Aurora-GLM.git
cd Aurora-GLM
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

For GPU support, add the torch extra:

pip install -e ".[torch]"

Verifying the installation¶

import aurora
print(aurora.__version__)   # 1.0.0

# Quick smoke test
import numpy as np
from aurora.models.glm import fit_glm

X = np.random.randn(100, 3)
y = X @ [1.5, -0.8, 0.3] + 0.5 + np.random.randn(100)
result = fit_glm(X, y, family="gaussian")
print(result.converged_)    # True

See Quickstart for a full walkthrough.