pyFM.optimize.base_functions.grad_energy_std

pyFM.optimize.base_functions.grad_energy_std(C, descr_mu, lap_mu, descr_comm_mu, orient_mu, descr1_red, descr2_red, list_descr, orient_op, ev_sqdiff)

Evaluate the gradient of the energy for standard FM computation.

Parameters:

  • C ((K2*K1,) or (K2, K1) np.ndarray) – Functional map.

  • descr_mu (float) – Scaling of the descriptor preservation term.

  • lap_mu (float) – Scaling of the Laplacian commutativity term.

  • descr_comm_mu (float) – Scaling of the descriptor commutativity term.

  • orient_mu (float) – Scaling of the orientation preservation term.

  • descr1_red ((K1, p) np.ndarray) – Descriptors on the first basis.

  • descr2_red ((K2, p) np.ndarray) – Descriptors on the second basis.

  • list_descr (list of tuple) – Each element is a tuple ((K1, K1) np.ndarray, (K2, K2) np.ndarray) of operators on the first and second basis related to the descriptors.

  • orient_op (list of tuple) – Each element is a tuple ((K1, K1) np.ndarray, (K2, K2) np.ndarray) of operators on the first and second basis related to orientation preservation.

  • ev_sqdiff ((K2, K1) np.ndarray) – [normalized] matrix of squared eigenvalue differences.

Returns:

gradient – Gradient of the energy.

Return type:

(K2*K1,) np.ndarray