Provided below are a line of tutorials and guides that quickly highlight key modules, features, and resources. Great for new users of PyDMD.
| Name | Description | PyDMD used classes |
|---|---|---|
| Manual1 [.ipynb, .py] | The Basics of BOPDMD |
pydmd.BOPDMD |
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.
| Name | Description | PyDMD used classes |
|---|---|---|
| Tutorial1 [.ipynb, .py, .html] | Analyzing real, simple data sets with PyDMD | pydmd.DMD, pydmd.BOPDMD |
| Tutorial2 [.ipynb, .py, .html] | advanced features of standard DMD | pydmd.DMD |
| Tutorial3 [.ipynb, .py, .html] | multi-resolution DMD for transient phenomena | pydmd.MrDMD |
| Tutorial4 [.ipynb, .py, .html] | compress DMD for computation speedup | pydmd.CDMD |
| Tutorial5 [.ipynb, .py, .html] | forward-backward DMD for CFD model analysis | pydmd.FbDMD |
| Tutorial6 [.ipynb, .py, .html] | higher-order DMD applied to scalar time-series | pydmd.HODMD |
| Tutorial7 [.ipynb, .py, .html] | DMD with control | pydmd.DMDC |
| Tutorial8 [.ipynb, .py, .html] | comparison between DMD and optimal closed-form DMD | pydmd.OptDMD |
| Tutorial9 [.ipynb, .py, .html] | sparsity-promoting DMD | pydmd.SpDMD |
| Tutorial10 [.ipynb, .py, .html] | parametric DMD | pydmd.ParametricDMD |
| Tutorial11 [.ipynb, .py, .html] | Tikhonov regularization | pydmd.DMDBase |
| Tutorial12 [.ipynb, .py] | cDMD for background modeling | pydmd.CDMD |
| Tutorial13 [.ipynb, .py] | SubspaceDMD for locating eigenvalues of stochastic systems | pydmd.SubspaceDMD |
| Tutorial14 [.ipynb, .py, .html] | Comparison between Bagging-/ Optimized DMD and exact DMD | pydmd.BOPDMD |
| Tutorial15 [.ipynb, .py, .html] | Physics-informed DMD for manifold enforcement | pydmd.PiDMD |
| Tutorial16 [.ipynb, .py, .html] | Randomized DMD for greater computation speedup | pydmd.RDMD |
| Tutorial17 [.ipynb, .py, .html] | Extended DMD for nonlinear eigenfunction discovery | pydmd.EDMD |
| Tutorial18 [.ipynb, .py, .html] | LANDO for nonlinear system modeling | pydmd.LANDO |
| Tutorial19 [.ipynb, .py, .html] | HAVOK for modeling chaos with partial measurements | pydmd.HAVOK |
| Tutorial20a [.ipynb] | COSTS for decomposing toy data | pydmd.COSTS |
| Tutorial20b [.ipynb] | mrCOSTS for decomposing multi-scale physics of real, noisy data | pydmd.mrCOSTS |
We collect here also the resources for helping developers to contribute to PyDMD.
| Name | Description | PyDMD used classes |
|---|---|---|
| Tutorial1 [.ipynb, .py, .html] | implementing a new version of DMD | pydmd.DMDBase |
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!