encode()

ROM.encode(states, lhs=None, inplace: bool = False, *, fit_transformer: bool = False, fit_basis: bool = False)

Map high-dimensional data to its low-dimensional representation.

Parameters:

states(n,) or (n, k) ndarray

State snapshots in the original state space.

lhs(n,) or (n, k) ndarray or None

Left-hand side regression data.

• If the model is time continuous, these are the time derivatives of the state snapshots.

• If the model is fully discrete, these are the “next states” corresponding to the state snapshots.

inplacebool

If True, modify the states and lhs in-place in the preprocessing transformation (if applicable).

Returns:

states_encoded(r,) or (r, k) ndarray

Low-dimensional representation of states in the latent reduced state space.

lhs_encoded(r,) or (r, k) ndarray

Low-dimensional representation of lhs in the latent reduced state space. Only returned if lhs is not None.