encode()#
- ParametricROM.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 thestates
andlhs
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 iflhs
is notNone
.