states.KalmanCentroid2D.state_entries
def state_entries(self, meas_field: str | None = None, init_cov_scale: float = 1.0) -> dict[str, State]Return ``(mean, cov)`` :class:`~unitrack.states.State` entries for ``Tracker``.
The mean entry holds a 4-D ``[x, y, vx, vy]`` state seeded from
``meas_field``; the cov entry holds a 4-by-4 covariance no-op'd
through predict/update because the mean entry's
:class:`KalmanLinear` / :class:`KalmanUpdate` already write the
covariance as a side effect.
Parameters
| Name | Type | Description |
|---|---|---|
| meas_field = None | str | Detection field that supplies the initial measurement. Defaults to :attr:`field`. |
| init_cov_scale = 1.0 | float | Scale applied to the identity matrix used to initialise the covariance. Default ``1.0``. |
Returns
dict — Two :class:`~unitrack.states.State` entries keyed by ``self.field`` and ``f"{self.field}_cov"``.
Source: unitrack/states/kalman/centroid.py:106