spectralbrain.compute_all_descriptors#

spectralbrain.compute_all_descriptors(decomp, *, hks_n_times=100, wks_n_energies=100, si_hks_n_freq=8, bates_order=2, bates_n_times=10, gaussian_curvature=None)[source]#

Compute all 8 spectral descriptors from one decomposition.

Efficient because the eigendecomposition (the expensive step) is shared. Each descriptor adds only O(N·k·T) work.

Parameters:

  • decomp (SpectralDecomposition)

  • hks_n_times (int)

  • wks_n_energies (int)

  • si_hks_n_freq (int)

  • bates_order (int)

  • bates_n_times (int)

  • gaussian_curvature (ndarray, optional) – For IBKS.

Returns:

dict of {str (ndarray}) – Keys: "shapedna", "hks", "si_hks", "wks", "gps", "bates_sp", "bks", "ibks".

Return type:

dict[str, ndarray[tuple[Any, …], dtype[floating]]]