DMD

modulo_vki.modulo.ModuloVKI.DMD(self, SAVE_T_DMD: bool = True, F_S: float = 1.0, verbose: bool = True)

Compute the Dynamic Mode Decomposition (DMD) of the dataset.

This implementation follows the algorithm in Tu et al. (2014) [1], which is essentially the same as Penland (1996) [2]. For additional low-level details see v1 of Mendez et al. (2020) [3].

Parameters:

  • SAVE_T_DMD (bool, optional) – If True, save time-dependent DMD results to disk. Default is True.

  • F_S (float, optional) – Sampling frequency in Hz. Default is 1.0.

Returns:

  • Phi_D (numpy.ndarray) – Complex DMD modes.

  • Lambda_D (numpy.ndarray) – Complex eigenvalues of the reduced-order propagator.

  • freqs (numpy.ndarray) – Frequencies (Hz) associated with each DMD mode.

  • a0s (numpy.ndarray) – Initial amplitudes (coefficients) of the DMD modes.

References