A Python library for Breaks For Additive Season and Trend (BFAST) that resorts to parallel computing for accelerating the computations.
Project description
bfast
The bfast package provides a highly-efficient parallel implementation for the Breaks For Additive Season and Trend (BFAST) proposed by Verbesselt et al. The implementation is based on OpenCL.
Documentation
Will be released soon.
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
Further, 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
On Debian/Ubuntu systems, the package can be installed globally for all users via:
python setup.py build sudo python setup.py install
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.