states.enkf_state_entries
def enkf_state_entries(field: str, dim: int, meas_field: str | None = None, ensemble_size: int = 32, q: float = 0.01, r: float = 0.1, init_std: float = 0.3, seed: int = 0) -> dict[str, State]Build the ``(mean, ensemble)`` state entries for an Ensemble Kalman filter.
The mean entry holds the ensemble mean ``(dim,)`` used for matching; the
ensemble entry holds the ``(ensemble_size, dim)`` members, no-op'd
through predict/update because the mean entry's :class:`EnsembleProcess`
/ :class:`EnsembleUpdate` maintain them.
Parameters
| Name | Type | Description |
|---|---|---|
| field | str | Name of the mean field (and prefix for ``f"{field}_ensemble"``). |
| dim | int | Embedding dimensionality. |
| meas_field = None | str | Detection field supplying the measurement. Defaults to :paramref:`field`. |
| ensemble_size = 32 | int | Number of ensemble members. |
| q = 0.01 | float | Per-unit-time process-noise (inflation) scale. |
| r = 0.1 | float | Measurement-noise scale. |
| init_std = 0.3 | float | Standard deviation of the initial ensemble spread. |
| seed = 0 | int | Seed for the ensemble spawn generator. |
Returns
dict — Two :class:`~unitrack.states.State` entries keyed by ``field`` and ``f"{field}_ensemble"``.
Source: unitrack/states/kalman/ensemble.py:217