Comments (3)
I am thinking about this ( and also see #56 ). Currently my target is to write up the docs, get some additional optimisation / identification routines for SINDY running and then get to the delays.
The implementation of HAVOK ( at least what is in the examples, there is a different PR open for this #53 ) is rather experimental.
To answer your questions:
-
Not yet
-
Maybe you can try
sparse_regression
defined here. There is also an iip version which gives you the matrix given DX and Theta, which should be the delay stuff)
Hope this helps.
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Hi, this helped a lot. I think that the best way to go forward with this would be usign sparse_regression
and manually creating an ODE system, which isn't that hard if you are using v_{r+1} as a forcing function since you can just use some interpolation package, but doing actual online prediction using HAVOK where v_{r+1} is being estimated by convolving with left singular vectors is likely more involved. I look forward to seeing what features get added to this package.
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I'll close this for now :)
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Related Issues (20)
- Linear Time Continuous System Documentation Example Errors in ODESystem Creation HOT 1
- indirect dependency RegularizationTools has GPL license HOT 4
- Unable to reconstruct system from result HOT 3
- Typo in naming STLSQ in documentation
- Basic Usage example fails HOT 1
- Understanding controls HOT 3
- Using DataDrivenSolution for forward modelling HOT 12
- How to get error estimate? HOT 1
- SymbolicUtils v1 upgrade
- Unable to recover the dynamic and predict, when DataDrivenSolution's problem is Discrete DataDrivenProblem HOT 1
- Result printing of Quick Demonstration in README.md is not reproduced HOT 1
- STLSQ method results in different models from pySINDy? HOT 4
- References for underlying methids
- Using DataDrivenDataset for DMD and SR
- Improve docstrings
- DataDrivenProblem takes a very long time HOT 2
- Model discovery using Sparse Regression on a UDE model
- Problem with dimension
- DimensionMismatch error - Symbolic Regression failing for sparse hyperparameters
- Switch from AbstractDifferentiation to DifferentiationInterface? HOT 3
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