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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 (BFASTmonitor) proposed by Verbesselt et al. The implementation is based on OpenCL.

Documentation

See the documentation 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 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.

Project details


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