===== bfast

The bfast package provides a highly-efficient parallel implementation for the Breaks For Additive Season and Trend (BFASTmonitor) <http://bfast.r-forge.r-project.org>_ proposed by Verbesselt et al. The implementation is based on OpenCL <https://www.khronos.org/opencl>_.

============= Documentation

See the documentation <http://bfast.readthedocs.org>_ for details and examples.

============ Dependencies

The bfast package has been tested under Python 3.*. The required Python dependencies are:

• numpy==1.16.3
• pandas==0.24.2
• pyopencl==2018.2.5
• scikit-learn==0.20.3
• scipy==1.2.1
• matplotlib==2.2.2
• wget==3.2
• Sphinx==2.2.0
• sphinx-bootstrap-theme==0.7.1

Further, OpenCL <https://www.khronos.org/opencl>_ needs to be available.

========== Quickstart

The package can easily be installed via pip via::

pip install bfast

To install the package from the sources, first get the current stable release via::

git clone https://github.com/gieseke/bfast.git

Afterwards, on Linux systems, you can install the package locally for the current user via::

python setup.py install --user

========== Disclaimer

The source code is published under the GNU General Public License (GPLv3). The authors are not responsible for any implications that stem from the use of this software.