Change dtype of Matrix to float

docs/tutorials/01_KalmanFilterTutorial.py

@@ -303,7 +303,7 @@
 # responsibility, a :class:`~.Predictor` takes a :class:`~.TransitionModel` as input and
 # an :class:`~.Updater` takes a :class:`~.MeasurementModel` as input. Note that for now we're using
 # the same models used to generate the ground truth and the simulated measurements. This won't
-# usually be possible and it's an interesting exercise to explore what happens when these
+# usually be possible, and it's an interesting exercise to explore what happens when these
 # parameters are mismatched.
 from stonesoup.predictor.kalman import KalmanPredictor
 predictor = KalmanPredictor(transition_model)

stonesoup/models/transition/nonlinear.py

@@ -3,7 +3,7 @@
 import numpy as np
 from scipy.linalg import block_diag
 
-from ...types.array import StateVector, StateVectors, Matrix
+from ...types.array import StateVector, StateVector
 from .base import TransitionModel
 from ..base import GaussianModel, TimeVariantModel
 from ...base import Property
@@ -95,8 +95,9 @@ def function(self, state, noise=False, **kwargs) -> StateVector:
         sv1 = state.state_vector
         turn_rate = sv1[4, :]
         # Avoid divide by zero in the function evaluation
-        if turn_rate[0] == 0:
-            turn_rate = Matrix([np.finfo(float).eps])
+        if turn_rate.dtype != float:
+            turn_rate = turn_rate.astype(float)
+        turn_rate[turn_rate == 0.] = np.finfo(float).eps
         dAngle = turn_rate * time_interval_sec
         cos_dAngle = np.cos(dAngle)
         sin_dAngle = np.sin(dAngle)