Add 2D version of Savitzky-Golay filter?

Contributor & Development Discussion
1

I have a 2D generalization of scipy.signal.savgol_filter. The call signature would be something like this:

savgol2d_filter(
    a: np.ndarray, window_radius: float, polyorder: int, axes=(-2, -1),
    mode='constant', circular=True, cval=0.0, conv_method='auto'
    ) -> np.ndarray

Differences with the existing 1D version:

  • With circular=True, it takes samples from a disc rather than from a square. For example, window_radius=2.5, polyorder=2 will result in a 5x5 kernel with 21 nonzero elements.
  • The polynomial has terms x**i * y**j with i+j <= polyorder.
  • I wouldn’t support mode='interpolate' because that’s a lot of book-keeping and handling of edge cases for 2D data.
  • conv_method will be passed to scipy.signal.convolve.
  • deriv=True would not be supported (I don’t think it makes much sense for 2D data).

I have an implementation for polyorder=2 and without the mode selector. I can rework it for the above interface. Shall I proceed to do this and create a PR?

(I have another topic in this forum about interpolation methods; that’s a long-term project. The above is probably a better way for me to get familiar with scipy development.)