Merge pull request #589 from ekhunter123/simple_initiator_measmodel

Make measurement model optional in measurement-based initiators

Author: sdhiscocks

stonesoup/initiator/simple.py

@@ -25,7 +25,10 @@ class SinglePointInitiator(GaussianInitiator):
     """
 
     prior_state: GaussianState = Property(doc="Prior state information")
-    measurement_model: MeasurementModel = Property(doc="Measurement model")
+    measurement_model: MeasurementModel = Property(
+        default=None,
+        doc="Measurement model. Can be left as None if all detections have a "
+            "valid measurement model.")
 
     def initiate(self, detections, timestamp, **kwargs):
         """Initiates tracks given unassociated measurements
@@ -64,6 +67,8 @@ class SimpleMeasurementInitiator(GaussianInitiator):
 
     This initiator utilises the :class:`~.MeasurementModel` matrix to convert
     :class:`~.Detection` state vector and model covariance into state space.
+    It either takes the :class:`~.MeasurementModel` from the given detection
+    or uses the :attr:`measurement_model`.
 
     Utilises the ReversibleModel inverse function to convert
     non-linear spherical co-ordinates into Cartesian x/y co-ordinates
@@ -77,7 +82,10 @@ class SimpleMeasurementInitiator(GaussianInitiator):
     decompositions.
     """
     prior_state: GaussianState = Property(doc="Prior state information")
-    measurement_model: MeasurementModel = Property(doc="Measurement model")
+    measurement_model: MeasurementModel = Property(
+        default=None,
+        doc="Measurement model. Can be left as None if all detections have a "
+            "valid measurement model.")
     skip_non_reversible: bool = Property(default=False)
     diag_load: float = Property(default=0.0, doc="Positive float value for diagonal loading")
 
@@ -94,7 +102,10 @@ def initiate(self, detections, timestamp, **kwargs):
             if detection.measurement_model is not None:
                 measurement_model = detection.measurement_model
             else:
-                measurement_model = self.measurement_model
+                if self.measurement_model is None:
+                    raise ValueError("No measurement model specified")
+                else:
+                    measurement_model = self.measurement_model
 
             if isinstance(measurement_model, LinearModel):
                 model_matrix = measurement_model.matrix()
@@ -155,12 +166,15 @@ class MultiMeasurementInitiator(GaussianInitiator):
     Does cause slight delay in initiation to tracker."""
 
     prior_state: GaussianState = Property(doc="Prior state information")
-    measurement_model: MeasurementModel = Property(doc="Measurement model")
     deleter: Deleter = Property(doc="Deleter used to delete the track.")
     data_associator: DataAssociator = Property(
         doc="Association algorithm to pair predictions to detections.")
     updater: Updater = Property(
         doc="Updater used to update the track object to the new state.")
+    measurement_model: MeasurementModel = Property(
+        default=None,
+        doc="Measurement model. Can be left as None if all detections have a "
+            "valid measurement model.")
     min_points: int = Property(
         default=2, doc="Minimum number of track points required to confirm a track.")
     updates_only: bool = Property(

stonesoup/initiator/tests/test_simple.py

@@ -16,7 +16,7 @@
 from ...hypothesiser.distance import DistanceHypothesiser
 from ...dataassociator.neighbour import NearestNeighbour
 from ...measures import Mahalanobis
-from ...types.detection import Detection
+from ...types.detection import Detection, TrueDetection
 from ...types.hypothesis import SingleHypothesis
 from ...types.prediction import Prediction
 from ...types.state import GaussianState
@@ -294,7 +294,8 @@ def test_multi_measurement(updates_only):
 
     measurement_initiator = MultiMeasurementInitiator(
         GaussianState([[0], [0], [0], [0]], np.diag([0, 15, 0, 15])),
-        measurement_model, deleter, data_associator, updater, updates_only=updates_only)
+        deleter, data_associator, updater,
+        measurement_model=measurement_model, updates_only=updates_only)
 
     timestamp = datetime.datetime.now()
     first_detections = {Detection(np.array([[5], [2]]), timestamp),
@@ -318,6 +319,25 @@ def test_multi_measurement(updates_only):
     assert len(measurement_initiator.holding_tracks) == 0
 
 
+@pytest.mark.parametrize("initiator", [
+    SinglePointInitiator(
+        GaussianState(np.array([[0]]), np.array([[100]]))
+    ),
+    SimpleMeasurementInitiator(
+        GaussianState(np.array([[0]]), np.array([[100]]))
+    ),
+], ids=['SinglePoint', 'LinearMeasurement'])
+def test_measurement_model(initiator):
+    timestamp = datetime.datetime.now()
+    dummy_detection = TrueDetection(np.array([0, 0]), timestamp)
+    # The SinglePointInitiator will raise an error when the ExtendedKalmanUpdater
+    # is called and neither the detection nor the initiator has a measurement
+    # model. The SimpleMeasurementInitiator will raise an error in the if/else
+    # blocks.
+    with pytest.raises(ValueError):
+        _ = initiator.initiate({dummy_detection}, timestamp)
+
+
 @pytest.mark.parametrize("gaussian_initiator", [
     SinglePointInitiator(
         GaussianState(np.array([[0]]), np.array([[100]])),