Streaming Dynamic Mode Decomposition (sDMD)

This repository contains a Python implementation of Streaming Dynamic Mode Decomposition (sDMD) as described in the paper Liew, J. et al. - Streaming dynamic mode decomposition for short-term forecasting in wind farms. The algorithm is suited to performing DMD analysis on-the-fly.

The implementation draws from concepts from similar works by Hemani, M. et al. - Dynamic mode decomposition for large and streaming datasets, and Zhang, H. et al. - Online dynamic mode decomposition for time-varying systems

Citation

If sDMD played a role in your research, please cite it. This software can be cited as: Jaime Liew, 2021. jaimeliew1/Streaming-DMD: Version 1.0. doi:10.5281/zenodo.4646749

For LaTeX users:

  @software{jaime_liew_2021_4646750,
    author       = {Jaime Liew},
    title        = {Streaming-DMD},
    year         = 2021,
    publisher    = {Zenodo},
    version      = {v1.0},
    doi          = {10.5281/zenodo.4646749},
    url          = {https://doi.org/10.5281/zenodo.4646749}
  }

Installation

Users who want to run sDMD should download the source code and install the package using pip, as shown below.

git clone https://github.com/jaimeliew1/Streaming-DMD.git
pip install -e streaming_dmd