The bfast package provides a highly-efficient parallel implementation for the Breaks For Additive Season and Trend (BFASTmonitor) proposed by Verbesselt et al. The implementation is based on OpenCL.

This project is a fork from diku-dk/bfast, that has been updated, to work with recent versions of Python and its dependencies, and to be used with the uv package manager.

See the documentation for details and examples.

This package uses uv for package management, which is a fast, reliable Python package installer and resolver.

If you don't have UV installed yet, you can install it with:

curl -LsSf https://astral.sh/uv/install.sh | sh

Or using pip:

pip install uv

Clone the repository and install the package in development mode:

# Clone the repository
git clone [email protected]:Lunyxis/bfast.git
cd bfast

# Create and activate a virtual environment using UV
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install the package in development mode
uv pip install -e .[dev]

# Install classic dependencies
uv pip install -e .

# Running tests
uv pip install pytest
pytest

uv pip install git+https://github.com/Lunyxis/bfast.git

TODO : update example usage, test, etc.

import bfast

# TODO Add example usage of the bfast package
# Example: Detecting structural changes in a time series

See the LICENSE file for details.