brutus

Et tu, Brute?

brutus is a Pure Python package for "brute force" Bayesian inference to derive distances, reddenings, and stellar properties from photometry. The package is designed to be highly modular and user-friendly, with comprehensive support for modeling individual stars, star clusters, and 3-D dust mapping.

Comprehensive documentation can be found at brutus.readthedocs.io.

Please contact Josh Speagle (j.speagle@utoronto.ca) with any questions.

Installation

The most recent stable release can be installed via pip by running

pip install astro-brutus

Key Features

🌟 Individual Star Modeling: Fit distances, reddenings, and stellar properties for individual stars using Bayesian inference (with either pre-computed stellar grids or evolutionary mass tracks)

🌟 Cluster Analysis: Model stellar clusters with consistent ages, metallicities, and distances (with isochrones)

🌟 3D Dust Mapping: Integrate with 3D dust maps and model extinction along lines of sight

Detailed Installation

Requirements

• Python: 3.8 or higher
• Operating System: Linux, macOS, or Windows with WSL (see Windows note below)

Quick Install

For most users, install the most recent stable release from PyPI:

pip install astro-brutus

Development Install

For development or to get the latest features:

git clone https://github.com/joshspeagle/brutus.git
cd brutus
pip install -e ".[dev]"

Windows Users - Important Note

⚠️ Windows Compatibility: Due to the healpy dependency (required for interacting with dust maps), brutus does not work reliably on native Windows. Windows users should install and run brutus in WSL (Windows Subsystem for Linux).

Conda Installation

If you use conda, you can install from conda-forge:

conda install -c conda-forge astro-brutus

Dependencies

Core dependencies that will be automatically installed:

• numpy (≥1.19) - Numerical computing
• scipy (≥1.6) - Scientific computing
• matplotlib (≥3.3) - Plotting
• h5py (≥3.0) - HDF5 file support
• healpy (≥1.14) - HEALPix utilities for incorporating dust maps
• numba (≥0.53) - Just-in-time compilation for performance
• pooch (≥1.4) - Data downloading and management
• tqdm (≥4.50) - Progress bars and live tracking

Data

Brutus requires stellar evolution models and other data files to function. These can be downloaded automatically using built-in utilities:

from brutus import fetch_grids, fetch_isos, fetch_dustmaps

# Download MIST stellar evolution grids
fetch_grids()

# Download MIST isochrones
fetch_isos()

# Download 3D dust maps
fetch_dustmaps()

Alternately, you can download them manually from the Harvard Dataverse.

Contributing

We welcome contributions! Please see the contribution guide for guidelines.

Development Setup

git clone https://github.com/joshspeagle/brutus.git
cd brutus
pip install -e ".[dev]"

Running Tests

# Basic tests
pytest

# With coverage
pytest --cov=brutus

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

• Author: Joshua S. Speagle
• Email: j.speagle@utoronto.ca
• GitHub: https://github.com/joshspeagle/brutus
• Issues: https://github.com/joshspeagle/brutus/issues

Acknowledgments

brutus by default uses MIST stellar evolution models and Bayestar dust maps via the [https://dustmaps.readthedocs.io/en/latest/](dustmaps package). We thank the developers of these initiatives and codebases for making their data and/or code publicly available.