Installation

Installation#

Requirements#

  • Python: 3.8 or higher

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

Quick Install#

Install the latest stable release from PyPI:

pip install astro-brutus

Development Install#

Install the development version (v1.1.0) directly from GitHub:

pip install git+https://github.com/joshspeagle/brutus.git

Or clone for local development:

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

Windows Users#

Warning

Due to the healpy dependency (required for dust mapping), brutus does not work on native Windows. Windows users must use WSL (Windows Subsystem for Linux).

To install on Windows:

  1. Install WSL with Ubuntu or another Linux distribution

  2. Open a WSL terminal and follow the standard installation instructions above

Alternatively, use a Linux-based Docker container.

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 Files#

Warning

You must download data files before using brutus. The package will not work without them.

After installing brutus, download the required model data:

Data Download Checklist#

Function

Size

Purpose

Required?

fetch_grids()

~750 MB

Pre-computed stellar model grids for fast fitting

Yes

fetch_isos()

~250 MB

Isochrone tables for stellar populations

Yes

fetch_offsets()

<1 KB

Photometric calibration offsets for improved accuracy

Recommended

fetch_dustmaps()

~2 GB

3D dust maps (Bayestar) for extinction priors

Optional

Recommended setup:

from brutus.data import fetch_grids, fetch_isos, fetch_offsets

# Download stellar model grid (~750 MB)
grid_path = fetch_grids(grid='mist_v9')

# Download isochrone tables (~250 MB)
iso_path = fetch_isos(iso='MIST_1.2_vvcrit0.0')

# Download photometric offsets (recommended for fitting)
offset_path = fetch_offsets(grid='mist_v9')

With 3D dust maps (for extinction priors):

from brutus.data import fetch_dustmaps

# Download Bayestar dust maps (~2 GB)
dustmap_path = fetch_dustmaps(dustmap='bayestar19')

Photometric Offsets#

The photometric offsets correct for systematic differences between observed and model photometry. These are derived from well-characterized calibration stars and significantly improve fitting accuracy. While not strictly required, using offsets is strongly recommended for reliable results.

Files are cached in your user data directory and only downloaded once. Total disk space needed: ~1 GB minimum, ~3 GB with dust maps.

Testing the Installation#

To verify your installation works correctly:

import brutus
print(f"brutus version: {brutus.__version__}")

# Test core imports
from brutus.core import Isochrone, StarGrid
from brutus.analysis import BruteForce
print("Installation successful!")