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A collection of notebooks on strategies to accurately interpolate discontinuous and non-periodic data on a uniform grid.

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KunkelAlexander/when-fourier-fails-python

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when-fourier-fails-python

Explore strategies to overcome Gibb's and Runge's phenomenon when handling discontinuous and non-periodic data on uniform grids. The different notebooks implement:

  • Arbitrary-order finite difference stencils
  • Filters
  • Mollifiers (Boyd's imbricate bell Fourier extension of the second kind or the Local Fourier Basis (LFB) method)
  • Subtraction methods (Polynomial and trigonometric subtraction)
  • Inverse Polynomial Reconstruction (IPR)
  • SVD extensions (Boyd's Fourier extension of the third kind)
  • Gram-Fourier extension (Gram-FE) (see the 'tables' folder for some pre-computed extensions and the corresponding notebook for their computation and usage)

Please look at the linked blog post for a more structure introduction.

Runge phenomenon