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PyDMD User Manuals

Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.

NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD

Tutorials

In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials. An additional PDF tutorial (DSWeb contest winner) is available here.

NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS

Tutorials for Developers

We collect here also the resources for helping developers to contribute to PyDMD.

NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase

More to come...

We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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tutorials
README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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tutorials
README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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PyDMD/tutorials at master · OpenWECD/PyDMD · GitHub
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tutorials
README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
PyDMD/tutorials at master · OpenWECD/PyDMD · GitHub
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tutorials
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tutorials
README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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PyDMD/tutorials at master · OpenWECD/PyDMD · GitHub
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README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!

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PyDMD/tutorials at master · OpenWECD/PyDMD · GitHub
Skip to content
tutorials
Directory actions
More options
Directory actions
More options
Latest commit
History
History
tutorials
README.md
PyDMD User Manuals
Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
NameDescriptionPyDMD used classes
Manual1 [.ipynb, .py]The Basics of BOPDMDpydmd.BOPDMD
Tutorials
In this folder we collect several useful tutorials in order to understand the principles and the potential of PyDMD. Please read the following table for details about the tutorials.
An additional PDF tutorial (DSWeb contest winner) is available here.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]Analyzing real, simple data sets with PyDMDpydmd.DMD, pydmd.BOPDMD
Tutorial2 [.ipynb, .py, .html]advanced features of standard DMDpydmd.DMD
Tutorial3 [.ipynb, .py, .html]multi-resolution DMD for transient phenomenapydmd.MrDMD
Tutorial4 [.ipynb, .py, .html]compress DMD for computation speeduppydmd.CDMD
Tutorial5 [.ipynb, .py, .html]forward-backward DMD for CFD model analysispydmd.FbDMD
Tutorial6 [.ipynb, .py, .html]higher-order DMD applied to scalar time-seriespydmd.HODMD
Tutorial7 [.ipynb, .py, .html]DMD with controlpydmd.DMDC
Tutorial8 [.ipynb, .py, .html]comparison between DMD and optimal closed-form DMDpydmd.OptDMD
Tutorial9 [.ipynb, .py, .html]sparsity-promoting DMDpydmd.SpDMD
Tutorial10 [.ipynb, .py, .html]parametric DMDpydmd.ParametricDMD
Tutorial11 [.ipynb, .py, .html]Tikhonov regularizationpydmd.DMDBase
Tutorial12 [.ipynb, .py]cDMD for background modelingpydmd.CDMD
Tutorial13 [.ipynb, .py]SubspaceDMD for locating eigenvalues of stochastic systemspydmd.SubspaceDMD
Tutorial14 [.ipynb, .py, .html]Comparison between Bagging-/ Optimized DMD and exact DMDpydmd.BOPDMD
Tutorial15 [.ipynb, .py, .html]Physics-informed DMD for manifold enforcementpydmd.PiDMD
Tutorial16 [.ipynb, .py, .html]Randomized DMD for greater computation speeduppydmd.RDMD
Tutorial17 [.ipynb, .py, .html]Extended DMD for nonlinear eigenfunction discoverypydmd.EDMD
Tutorial18 [.ipynb, .py, .html]LANDO for nonlinear system modelingpydmd.LANDO
Tutorial19 [.ipynb, .py, .html]HAVOK for modeling chaos with partial measurementspydmd.HAVOK
Tutorial20a [.ipynb]COSTS for decomposing toy datapydmd.COSTS
Tutorial20b [.ipynb]mrCOSTS for decomposing multi-scale physics of real, noisy datapydmd.mrCOSTS
Tutorials for Developers
We collect here also the resources for helping developers to contribute to PyDMD.
NameDescriptionPyDMD used classes
Tutorial1 [.ipynb, .py, .html]implementing a new version of DMDpydmd.DMDBase
More to come...
We plan to add more tutorials but the time is often against us. If you want to contribute with a notebook on a feature not covered yet we will be very happy and give you support on editing!