# Initial state estimation¶

class rtctools.optimization.initial_state_estimation_mixin.InitialStateEstimationMixin(**kwargs)[source]

Before any other goals are evaluated, first, the deviation between initial state measurements and their respective model states is minimized in the least squares sense (1DVAR, priority -2). Secondly, the distance between pairs of states is minimized, again in the least squares sense, so that “smooth” initial guesses are provided for states without measurements (priority -1).

Note

There are types of problems where, in addition to minimizing differences between states and measurements, it is advisable to perform a steady-state initialization using additional initial-time model equations. For hydraulic models, for instance, it is often helpful to require that the time-derivative of the flow variables vanishes at the initial time.

initial_state_measurements() → List[Union[Tuple[str, str], Tuple[str, str, float]]][source]

List of pairs (state, measurement_id) or triples (state, measurement_id, max_deviation), relating states to measurement time series IDs.

The default maximum deviation is 1.0.

initial_state_smoothing_pairs() → List[Union[Tuple[str, str], Tuple[str, str, float]]][source]

List of pairs (state1, state2) or triples (state1, state2, max_deviation), relating states the distance of which is to be minimized.

The default maximum deviation is 1.0.