Merge pull request #694 from dstl/optimised_SM_edits

Fix OptimizeBruteSensorManager

stonesoup/sensormanager/optimise.py

@@ -67,9 +67,10 @@ class OptimizeBruteSensorManager(_OptimizeSensorManager):
         doc="Number of grid points to search along axis. See Ns in "
             ":func:`~.scipy.optimize.brute`. "
             "Default is 10.")
-    full_output: bool = Property(default=False,
-                                 doc="If True, returns the evaluation grid and the objective "
-                                     "function's values on it.")
+    generate_full_output: bool = Property(default=False,
+                                          doc="If True, returns the evaluation grid "
+                                              "and the objective "
+                                              "function's values on it.")
     finish: bool = Property(default=False,
                             doc="A polishing function can be applied to the result of brute "
                                 "force minimisation. If True this is set as "
@@ -94,15 +95,34 @@ def _optimiser(self, optimise_func, all_action_generators):
         result = brute(optimise_func,
                        ranges=ranges,
                        Ns=self.n_grid_points,
-                       full_output=self.full_output,
+                       full_output=self.generate_full_output,
                        finish=self.finish_func,
                        disp=self.disp)
 
-        if self.full_output:
+        if self.generate_full_output:
+            self.full_output = result
             result = result[0]
 
         return np.atleast_1d(result)
 
+    def get_full_output(self):
+        """
+        Returns the output generated when `generate_full_output=True` for the most recent
+        time step.
+        This returns the evaluation grid and reward function's values on it, as generated by the
+        :meth:`optimize.brute` method.
+        See
+        `Scipy documentation
+        <https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.brute.html#scipy.optimize.brute>`_
+        for full details.
+
+        Returns
+        -------
+        full_output: tuple
+        """
+        if self.full_output:
+            return self.full_output
+
 
 class OptimizeBasinHoppingSensorManager(_OptimizeSensorManager):
     """

stonesoup/sensormanager/tests/test_sensormanager.py

@@ -51,7 +51,7 @@ def test_random_choose_actions():
                 assert isinstance(actions[0], ChangeDwellAction)
 
 
-def test_brute_force_choose_actions():
+def test_uncertainty_based_managers():
     time_start = datetime.now()
 
     tracks = [Track(states=[
@@ -114,18 +114,34 @@ def test_brute_force_choose_actions():
             max_range=np.inf,
         )}
 
-        for sensor_set in [sensorsA, sensorsB, sensorsC]:
+        sensorsD = {RadarRotatingBearingRange(
+            position_mapping=(0, 2),
+            noise_covar=np.array([[np.radians(0.5) ** 2, 0],
+                                  [0, 0.75 ** 2]]),
+            position=np.array([[0], [0]]),
+            ndim_state=4,
+            rpm=60,
+            fov_angle=np.radians(30),
+            dwell_centre=StateVector([0.0]),
+            max_range=np.inf,
+        )}
+
+        for sensor_set in [sensorsA, sensorsB, sensorsC, sensorsD]:
             for sensor in sensor_set:
                 sensor.timestamp = time_start
 
         sensor_managerA = BruteForceSensorManager(sensorsA, reward_function)
         sensor_managerB = OptimizeBruteSensorManager(sensorsB, reward_function)
         sensor_managerC = OptimizeBasinHoppingSensorManager(sensorsC,
                                                             reward_function)
+        sensor_managerD = OptimizeBruteSensorManager(sensorsD, reward_function,
+                                                     generate_full_output=True,
+                                                     finish=True)
 
         sensor_managers = [sensor_managerA,
                            sensor_managerB,
-                           sensor_managerC]
+                           sensor_managerC,
+                           sensor_managerD]
 
         timesteps = []
         for t in range(3):
@@ -159,3 +175,5 @@ def test_brute_force_choose_actions():
 
     assert all_dwell_centres[0][0] == all_dwell_centres[1][0] == all_dwell_centres[2][0]
     assert all_dwell_centres[0][1] == all_dwell_centres[1][1] == all_dwell_centres[2][1]
+
+    assert isinstance(sensor_managerD.get_full_output(), tuple)