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@briandesilva briandesilva released this 30 Aug 01:06
· 1177 commits to master since this release
v1.2.0
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This release implements the SINDyDerivative class, which allows one to use differentiation methods from the derivative package. This will enable the application of SINDy to much noisier datasets.

Note that PySINDy now requires the derivative package.

derivative includes the following numerical differentiation techniques:

  • Spectral derivatives (via the FFT)
  • Spline-based derivatives
  • Finite differences of arbitrary order
  • Polynomial least-squares (Savitzky-Golay)
  • Total variation regularized derivative (the method recommended in the original SINDy paper)

This release also contains some improvements to the documentation:

  • Example using SINDyDerivative in the Feature Overview notebook
  • A new notebook comparing all the differentiation options available in PySINDy
  • An example showing how to optimize parameters of derivative objects with cross-validation
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