Work Description
Title: Challenges in Dynamic Mode Decomposition -- figures Open Access Deposited
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(2021). Challenges in Dynamic Mode Decomposition -- figures [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/nzq9-4715
Relationships
Files (Count: 13; Size: 112 KB)
Thumbnailthumbnail-column | Title | Original Upload | Last Modified | File Size | Access | Actions |
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plot_stats.py | 2021-08-30 | 2021-08-30 | 15 KB | Open Access |
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dmd.py | 2021-08-30 | 2021-08-30 | 6.91 KB | Open Access |
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generator.py | 2021-08-30 | 2021-08-30 | 4.63 KB | Open Access |
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plot_util.py | 2021-08-30 | 2021-08-30 | 9.67 KB | Open Access |
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plot_test.py | 2021-08-30 | 2021-08-30 | 2.91 KB | Open Access |
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plot_appendix.py | 2021-08-30 | 2021-08-30 | 9.4 KB | Open Access |
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plot_eigDensity.py | 2021-08-30 | 2021-08-30 | 8.5 KB | Open Access |
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optimalDMD.py | 2021-08-30 | 2021-08-30 | 2.89 KB | Open Access |
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variableProj.py | 2021-08-30 | 2021-08-30 | 9.21 KB | Open Access |
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LICENSE | 2021-08-30 | 2021-08-30 | 34.3 KB | Open Access |
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README.txt | 2021-08-30 | 2021-08-30 | 2.19 KB | Open Access |
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runAll.sh | 2021-08-30 | 2021-08-30 | 86 Bytes | Open Access |
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opt-dmd-diff | 2021-08-30 | 2021-08-30 | 6.46 KB | Open Access |
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The code in this folder reproduces the key figures from "Challenges in Dynamic Mode Decomposition" by Z. Wu, S. L. Brunton, and S. Revzen.
# Running the project
Run everything. It takes around 12min to run on intel core i7 vPro 8th Gen.
./runAll.sh
A single eigenvalue density plot.
python3 plot_test.py
Eigenvalue density contour plots (figure 2,4,6).
python3 plot_eigDensity.py
Eigenvalue stats plot (figure 3, 5, 7, 8)
python3 plot_stats.py
Eigenvalue density contour plot in appendix (figure 9-14)
python3 plot_appendix.py
# Dependency
python >=3.6.9
numpy >=1.19.5
scipy >=1.5.4
matplotlib >=3.3.4
Some of the plotting code in plot_util.py goes back to 2008, and was developed
as part of Revzen's thesis. This older code was released under the GPL 3.0
licence.
variableProj.py and optimalDMD.py are from py-optDMD (https://github.com/kunert/py-optDMD) and governed by copyright and license of that work.
Work on this code was primarily funded by ARO MURI W911NF-17-1-0306
"From Data-Driven Operator Theoretic Schemes to Prediction, Inference,
and Control of Systems", and government usage rights are reserved as per that
funding agreement.
All other usage is governed by the GPL 3.0 license as specified below.
This code is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, version 3 of the License.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see .
# Bugfix for upstream issues
variableProj.py and optimalDMD.py are from py-optDMD (https://github.com/kunert/py-optDMD)
We have addressed the issue https://github.com/kunert/py-optDMD/issues/1#issue-777534962.
We have changed the code syntax to compile in python3 environment.
The result now matches the MATLAB version of optDMD within numerical accuracy for our examples.
The changes made from upper steam repo kunert/py-optDMD are in opt-dmd-diff