Source code for stonesoup.updater.base

from abc import abstractmethod

from ..base import Base, Property
from ..models.measurement import MeasurementModel


[docs] class Updater(Base): r"""Updater base class An updater is used to update the predicted state, utilising a measurement and a :class:`~.MeasurementModel`. The general observation model is .. math:: \mathbf{z} = h(\mathbf{x}, \mathbf{\sigma}) where :math:`\mathbf{x}` is the state, :math:`\mathbf{\sigma}`, the measurement noise and :math:`\mathbf{z}` the resulting measurement. """ measurement_model: MeasurementModel = Property(doc="measurement model") def _check_measurement_model(self, measurement_model): """Check that the measurement model passed actually exists. If not attach the one in the updater. If that one's not specified, return an error. Parameters ---------- measurement_model : :class`~.MeasurementModel` A measurement model to be checked Returns ------- : :class`~.MeasurementModel` The measurement model to be used """ if measurement_model is None: if self.measurement_model is None: raise ValueError("No measurement model specified") else: measurement_model = self.measurement_model return measurement_model
[docs] @abstractmethod def predict_measurement( self, predicted_state, measurement_model=None, measurement_noise=True, **kwargs): """Get measurement prediction from state prediction Parameters ---------- predicted_state : :class:`~.StatePrediction` The state prediction measurement_model: :class:`~.MeasurementModel`, optional The measurement model used to generate the measurement prediction. Should be used in cases where the measurement model is dependent on the received measurement. The default is `None`, in which case the updater will use the measurement model specified on initialisation measurement_noise : bool Whether to include measurement noise predicted measurement. Default `True` Returns ------- : :class:`~.MeasurementPrediction` The predicted measurement """ raise NotImplementedError
[docs] @abstractmethod def update(self, hypothesis, **kwargs): """Update state using prediction and measurement. Parameters ---------- hypothesis : :class:`~.Hypothesis` Hypothesis with predicted state and associated detection used for updating. Returns ------- : :class:`~.State` The state posterior """ raise NotImplementedError