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A Python Implementation of Dynamic Mode Decomposition

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Python Implementation of Dynamic Mode Decomposition

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This python code illustrates how to apply Dynamic Mode Decomposition (DMD) to univariate time series forecasting tasks.

Two examples are provided here.

For the explanation of DMD, please refer to this HackMD notes: Dynamic Mode Decomposition.

The major reference is this arXiv article: On Dynamic Mode Decomposition: Theory and Applications.


Install dmd

Install from GitHub

pip install git+https://github.com/mukappalambda/dmd.git

Install from Source

git clone https://github.com/mukappalambda/dmd.git
poetry build
find dist -name "*-$(poetry version -s)-*.whl" | xargs -I{} pip install {}

Run Examples

cd examples
python dmd_example01.py
python dmd_example02.py

Uninstall dmd

pip uninstall dmd -y

History

  • Tweak the HackMD note more readable and add the Python code inside that note.

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