Merge pull request #1071 from dstl/consistent_measurement_label_for_p…

…lotters

Update Plotter Labels

docs/examples/dataassociation/Comparing_EHM_JPDA_example.py

@@ -383,11 +383,11 @@
 plotter.plot_ground_truths(groundtruths, [0, 2])
 plotter.plot_measurements(detections_set, [0, 2])
 plotter.plot_tracks(JPDA_tracks, [0, 2], line= dict(color='orange'),
-                    track_label='JPDA tracks')
+                    label='JPDA tracks')
 plotter.plot_tracks(EHM1_tracks, [0, 2], line= dict(color='green', dash='dot'),
-                    track_label='EHM1 tracks')
+                    label='EHM1 tracks')
 plotter.plot_tracks(EHM2_tracks, [0, 2], line= dict(color='red', dash='dot'),
-                    track_label='EHM2 tracks')
+                    label='EHM2 tracks')
 plotter.fig
 
 # %%

docs/examples/dataassociation/One_to_One_Associator.py

@@ -58,11 +58,11 @@
 
 plotter = Plotterly()
 plotter.plot_tracks(tracks=[Track(state) for state in states_from_a],
-                    mapping=[0, 1], track_label="Source A",
+                    mapping=[0, 1], label="Source A",
                     mode="markers", marker=dict(symbol="cross", color=next(colours_iter)))
 
 plotter.plot_tracks(tracks=[Track(state) for state in states_from_b],
-                    mapping=[0, 1], track_label="Source B",
+                    mapping=[0, 1], label="Source B",
                     mode="markers", marker=dict(symbol="circle", color=next(colours_iter)))
 
 plotter.fig
@@ -109,17 +109,17 @@
     track = Track(state_from_a, init_metadata=dict(source="a", association=idx))
     plotter.plot_tracks(track,
                         mapping=[0, 1], mode="markers",
-                        track_label=f"{state_names[state_from_a]}, Association {idx}",
+                        label=f"{state_names[state_from_a]}, Association {idx}",
                         marker=dict(symbol="cross", color=colour))
 
     track = Track(state_from_b, init_metadata=dict(source="b", association=idx))
     plotter.plot_tracks(track, mapping=[0, 1], mode="markers",
-                        track_label=f"{state_names[state_from_b]}, Association {idx}",
+                        label=f"{state_names[state_from_b]}, Association {idx}",
                         marker=dict(symbol="circle", color=colour))
 
     track = Track([state_from_a, state_from_b], init_metadata=dict(association=idx))
     plotter.plot_tracks(track, mapping=[0, 1], mode="lines",
-                        track_label=f"Association {idx}",
+                        label=f"Association {idx}",
                         line=dict(color=colour))
 
     dist_between_states = Euclidean()(state_from_a, state_from_b)
@@ -134,7 +134,7 @@
     colour = next(colours_iter)
     track = Track(state, init_metadata=dict(source="a", association=None))
     plotter.plot_tracks(track, mapping=[0, 1],
-                        track_label=f"{state_names[state]}, No Association",
+                        label=f"{state_names[state]}, No Association",
                         mode="markers", marker=dict(symbol="cross", color=colour))
 
 for state in unassociated_states_b:
@@ -143,7 +143,7 @@
     colour = next(colours_iter)
     track = Track(state, init_metadata=dict(source="b", association=None))
     plotter.plot_tracks(track, mapping=[0, 1],
-                        track_label=f"{state_names[state]}, No Association",
+                        label=f"{state_names[state]}, No Association",
                         mode="markers", marker=dict(symbol="circle", color=colour))
 
 # %%
@@ -215,11 +215,11 @@
 
 colour = next(colours_iter)
 for track in tracks_a:
-    plotter.plot_tracks(track, mapping=[0, 1], track_label=track.id, marker=dict(color=colour))
+    plotter.plot_tracks(track, mapping=[0, 1], label=track.id, marker=dict(color=colour))
 
 colour = next(colours_iter)
 for track in tracks_b:
-    plotter.plot_tracks(track, mapping=[0, 1], track_label=track.id, marker=dict(color=colour))
+    plotter.plot_tracks(track, mapping=[0, 1], label=track.id, marker=dict(color=colour))
 
 plotter.fig
 
@@ -272,15 +272,15 @@
     print('Associated together', [track.id for track in assoc.objects])
     colour = next(colours_iter)
     for track in assoc.objects:
-        plotter.plot_tracks(track, mapping=[0, 1], track_label=track.id,
+        plotter.plot_tracks(track, mapping=[0, 1], label=track.id,
                             marker=dict(color=colour))
 
 print("Not Associated in A: ", [track.id for track in unassociated_a])
 print("Not Associated in B: ", [track.id for track in unassociated_b])
 
 for track in [*unassociated_a, *unassociated_b]:
     colour = next(colours_iter)
-    plotter.plot_tracks(track, mapping=[0, 1], track_label=track.id, marker=dict(color=colour))
+    plotter.plot_tracks(track, mapping=[0, 1], label=track.id, marker=dict(color=colour))
 
 plotter.fig
 

docs/examples/dataassociation/mht_example.py

@@ -238,7 +238,7 @@
 
     tracks.add(track)
 
-plotter.plot_tracks(tracks, [0, 2], track_label="Tracks", line=dict(color="Green"))
+plotter.plot_tracks(tracks, [0, 2], label="Tracks", line=dict(color="Green"))
 plotter.fig
 
 # %%

docs/examples/eot/extended_object_tracking_example.py

@@ -349,7 +349,7 @@
     tracks.update(current_tracks)
 
 plotter.plot_measurements(centroid_detections, [0, 2], marker=dict(color='red'),
-                          measurements_label='Cluster centroids')
+                          label='Cluster centroids')
 plotter.plot_tracks(tracks, [0, 2])
 plotter.fig
 

docs/examples/filters/Multi_Tracker_Example.py

@@ -365,13 +365,13 @@
 
 # %%
 # Finally, we plot the results:
-plotter.plot_tracks(tracks_EKF, [0, 2], track_label="EKF", line=dict(color="orange"),
+plotter.plot_tracks(tracks_EKF, [0, 2], label="EKF", line=dict(color="orange"),
                     uncertainty=False)
-plotter.plot_tracks(tracks_UKF, [0, 2], track_label="UKF", line=dict(color="blue"),
+plotter.plot_tracks(tracks_UKF, [0, 2], label="UKF", line=dict(color="blue"),
                     uncertainty=False)
-plotter.plot_tracks(tracks_PF, [0, 2], track_label="PF", line=dict(color="brown"),
+plotter.plot_tracks(tracks_PF, [0, 2], label="PF", line=dict(color="brown"),
                     uncertainty=False)
-plotter.plot_tracks(tracks_ESIF, [0, 2], track_label="ESIF", line=dict(color="green"),
+plotter.plot_tracks(tracks_ESIF, [0, 2], label="ESIF", line=dict(color="green"),
                     uncertainty=False)
 plotter.fig
 

docs/examples/filters/bearing_only_example.py

@@ -230,7 +230,7 @@
 plotter = AnimationPlotter(legend_kwargs=dict(loc='upper left'))
 plotter.plot_ground_truths(groundtruth_paths, (0,2))
 plotter.plot_tracks(kalman_tracks, (0,2))
-plotter.plot_ground_truths(platform, (0,2), truths_label="Sensor Platform")
+plotter.plot_ground_truths(platform, (0,2), label="Sensor Platform")
 plotter.run()
 
 # %%

docs/examples/oosm/KalmanFilterOOSMExample.py

@@ -155,12 +155,12 @@
 plotter = AnimatedPlotterly(timesteps=time_steps)
 plotter.plot_ground_truths(truth, [0, 2])
 plotter.plot_measurements(measurements1, [0, 2], marker=dict(color='blue'),
-                          measurements_label='Detections with no lag')
+                          label='Detections with no lag')
 plotter.plot_measurements(measurements2, [0, 2], marker=dict(color='orange'),
-                          measurements_label='Detections with lag')
+                          label='Detections with lag')
 plotter.plot_sensors([sensor1_platform, sensor2_platform],
                      marker=dict(color='black', symbol='129', size=15),
-                     sensor_label='Fixed Platforms')
+                     label='Fixed Platforms')
 plotter.fig
 
 # %%
@@ -297,10 +297,10 @@
 # However, it is interesting to see a 1-to-1 comparison between the three trackers, even if the
 # Tracker 2 track is not, visually, lagging behind.
 
-plotter.plot_tracks(track1, [0, 2], track_label='Tracker 1')
-plotter.plot_tracks(track2, [0, 2], track_label='Tracker 2',
+plotter.plot_tracks(track1, [0, 2], label='Tracker 1')
+plotter.plot_tracks(track2, [0, 2], label='Tracker 2',
                     line=dict(color='red'))
-plotter.plot_tracks(track3, [0, 2], track_label='Tracker 3',
+plotter.plot_tracks(track3, [0, 2], label='Tracker 3',
                     line=dict(color='green'))
 plotter.fig
 

docs/examples/oosm/PF_OOSM_example.py

@@ -302,9 +302,9 @@
 plotter.plot_ground_truths(truths, [0, 2])
 
 plotter.plot_measurements(scans_detections, [0, 2])
-plotter.plot_tracks(track, [0, 2], track_label='Track dealing with OOSM',
+plotter.plot_tracks(track, [0, 2], label='Track dealing with OOSM',
                     line=dict(color='blue'))
-plotter.plot_tracks(track2, [0, 2], track_label='Track ignoring OOSM')
+plotter.plot_tracks(track2, [0, 2], label='Track ignoring OOSM')
 plotter.fig
 
 # %%

docs/examples/oosm/example_oosm_algorithm.py

@@ -339,11 +339,11 @@
 from stonesoup.plotter import AnimatedPlotterly
 plotter = AnimatedPlotterly(timesteps=timestamps)
 plotter.plot_ground_truths(truths, [0, 2])
-plotter.plot_measurements(scan_s1, [0, 2], measurements_label='scan1', measurement_model=sensor_1_mm)
-plotter.plot_measurements(scan_s2, [0, 2], measurements_label='scan2', measurement_model=sensor_1_mm)
-plotter.plot_tracks(oosm_tracks, [0, 2], track_label='OOSM Tracks',
+plotter.plot_measurements(scan_s1, [0, 2], label='scan1', measurement_model=sensor_1_mm)
+plotter.plot_measurements(scan_s2, [0, 2], label='scan2', measurement_model=sensor_1_mm)
+plotter.plot_tracks(oosm_tracks, [0, 2], label='OOSM Tracks',
                     line= dict(color='orange'))
-plotter.plot_tracks(noOsm_tracks, [0, 2], track_label='no-OOSM Tracks',
+plotter.plot_tracks(noOsm_tracks, [0, 2], label='no-OOSM Tracks',
                     line= dict(color='red'))
 plotter.fig
 

docs/examples/oosm/example_simple_oosm.py

@@ -201,9 +201,9 @@
 
 plotter = AnimatedPlotterly(timesteps=timestamps)
 plotter.plot_ground_truths(truths, [0, 2])
-plotter.plot_measurements(scans_detections, [0, 2], measurements_label='Detections',
+plotter.plot_measurements(scans_detections, [0, 2], label='Detections',
                           measurement_model=measurement_model)
-plotter.plot_tracks(track_lag, [0, 2], line= dict(color='grey'), track_label='Track with lag')
+plotter.plot_tracks(track_lag, [0, 2], line= dict(color='grey'), label='Track with lag')
 plotter.fig
 
 # %%
@@ -262,7 +262,7 @@
 # Plotting the final track
 # ------------------------
 
-plotter.plot_tracks(track, [0, 2], line= dict(color='blue'), track_label='Track with OOSM treated')
+plotter.plot_tracks(track, [0, 2], line= dict(color='blue'), label='Track with OOSM treated')
 plotter.fig
 
 # %%

docs/examples/plotting/Polar_Plotting.py

@@ -85,8 +85,8 @@
 # :class:`~.Plotterly` plotting class:
 plotter_xy = Plotterly(title="Bird's Eye View of Targets")
 mapping = [0, 2]
-plotter_xy.plot_ground_truths(target_1, mapping=[0, 2], truths_label="Target 1")
-plotter_xy.plot_ground_truths(target_2, mapping=[0, 2], truths_label="Target 2")
+plotter_xy.plot_ground_truths(target_1, mapping=[0, 2], label="Target 1")
+plotter_xy.plot_ground_truths(target_2, mapping=[0, 2], label="Target 2")
 plotter_xy.fig
 
 # %%
@@ -130,9 +130,9 @@
                               yaxis=dict(title=dict(text="Bearing (Radians)"))
                               )
 plotter_az_t_cart.plot_ground_truths({angular_ground_truth_1},
-                                     mapping=mapping, truths_label="Target 1")
+                                     mapping=mapping, label="Target 1")
 plotter_az_t_cart.plot_ground_truths({angular_ground_truth_2},
-                                     mapping=mapping, truths_label="Target 2")
+                                     mapping=mapping, label="Target 2")
 plotter_az_t_cart.plot_measurements(detections, mapping=mapping, convert_measurements=False)
 plotter_az_t_cart.fig
 
@@ -154,8 +154,8 @@
 # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 mapping = [0]
 plotter_az_t = PolarPlotterly(title="Azimuth Angle (Degrees) vs Time (s)")
-plotter_az_t.plot_ground_truths({angular_ground_truth_1}, mapping=mapping, truths_label="Target 1")
-plotter_az_t.plot_ground_truths({angular_ground_truth_2}, mapping=mapping, truths_label="Target 2")
+plotter_az_t.plot_ground_truths({angular_ground_truth_1}, mapping=mapping, label="Target 1")
+plotter_az_t.plot_ground_truths({angular_ground_truth_2}, mapping=mapping, label="Target 2")
 plotter_az_t.plot_measurements(detections, mapping=mapping, convert_measurements=False)
 plotter_az_t.fig
 
@@ -175,8 +175,8 @@
 # sphinx_gallery_thumbnail_number = 4
 plotter_az_r = PolarPlotterly(title="Azimuth Angle (Degrees) vs Range (m)")
 mapping = [0, 1]
-plotter_az_r.plot_ground_truths({angular_ground_truth_1}, mapping=mapping, truths_label="Target 1")
-plotter_az_r.plot_ground_truths({angular_ground_truth_2}, mapping=mapping, truths_label="Target 2")
+plotter_az_r.plot_ground_truths({angular_ground_truth_1}, mapping=mapping, label="Target 1")
+plotter_az_r.plot_ground_truths({angular_ground_truth_2}, mapping=mapping, label="Target 2")
 plotter_az_r.plot_measurements(detections, mapping=mapping, convert_measurements=False)
 plotter_az_r.fig
 

docs/examples/sensorfusion/Example_data_fusion_from_sensors.py

@@ -459,19 +459,19 @@
 
 plotter = Plotterly()
 plotter.plot_measurements(s1_detections, [0, 2],
-                          measurements_label='Radar 1 measurements'),
+                          label='Radar 1 measurements'),
 plotter.plot_measurements(s2_detections, [0, 2],
-                          measurements_label='Radar 2 measurements')
-plotter.plot_tracks(ukf_tracks, [0, 2], line=dict(color='green'), track_label='UKF tracks')
-plotter.plot_tracks(ekf_tracks, [0, 2], line=dict(color='blue'), track_label='EKF tracks')
+                          label='Radar 2 measurements')
+plotter.plot_tracks(ukf_tracks, [0, 2], line=dict(color='green'), label='UKF tracks')
+plotter.plot_tracks(ekf_tracks, [0, 2], line=dict(color='blue'), label='EKF tracks')
 plotter.plot_tracks(pf_tracks, [0, 2], particle=False, line=dict(color='red'),
-                    track_label='PF tracks')
+                    label='PF tracks')
 plotter.plot_ground_truths(truths, [0, 2])
 plotter.plot_sensors(sensor1_platform, [0, 1], marker=dict(color='black', symbol='129', size=15),
-                     sensor_label='Fixed Platform')
+                     label='Fixed Platform')
 plotter.plot_ground_truths(sensor2_platform, [0, 2], marker=dict(color='orange', symbol='cross',
                                                                  size=25),
-                           truths_label='Moving Platform')
+                           label='Moving Platform')
 plotter.fig
 
 # %%

docs/examples/trackfusion/Track2Track_Fusion_Example.py

@@ -629,17 +629,17 @@
     plotter.plot_ground_truths(truths, [0, 2],
                                color='black')
     plotter.plot_measurements(s1_detections, [0, 2], color='orange', marker='*',
-                              measurements_label='Measurements - Airborne Radar')
+                              label='Measurements - Airborne Radar')
     plotter.plot_measurements(s2_detections, [0, 2], color='blue', marker='*',
-                              measurements_label='Measurements - Ground Radar')
+                              label='Measurements - Ground Radar')
     plotter.plot_tracks(jpda_tracks, [0, 2], color='red',
-                        track_label='Tracks - Airborne Radar (JPDAF)')
+                        label='Tracks - Airborne Radar (JPDAF)')
     plotter.plot_tracks(gmlcc_tracks, [0, 2], color='purple',
-                        track_label='Tracks - Ground Radar (GM-LCC)')
+                        label='Tracks - Ground Radar (GM-LCC)')
     plotter.plot_tracks(meas_fusion_tracks, [0, 2], color='green',
-                        track_label='Tracks - Measurement Fusion (GM-PHD)')
+                        label='Tracks - Measurement Fusion (GM-PHD)')
     plotter.plot_tracks(track_fusion_tracks, [0, 2], color='pink',
-                        track_label='Tracks - Covariance Intersection (GM-PHD)')
+                        label='Tracks - Covariance Intersection (GM-PHD)')
 
     # Format the legend a bit. Set the position outside of the plot, and
     # swap the order of the clutter and ground radar measurements

docs/examples/trackfusion/track_fusion_example.py

@@ -185,9 +185,9 @@
 # Plot the detections from the two radars
 plotter = Plotterly()
 plotter.plot_measurements(s1_detections, [0, 2], marker=dict(color='red'),
-                          measurements_label='Sensor 1 measurements')
+                          label='Sensor 1 measurements')
 plotter.plot_measurements(s2_detections, [0, 2], marker=dict(color='blue'),
-                          measurements_label='Sensor 2 measurements')
+                          label='Sensor 2 measurements')
 plotter.plot_sensors({sensor1_platform, sensor2_platform}, [0, 1],
                      marker=dict(color='black', symbol='1', size=10))
 plotter.plot_ground_truths(truths, [0, 2])
@@ -431,12 +431,12 @@
 # Let's visualise the various tracks and detections in the cases
 # using the Kalman and particle filters.
 
-plotter.plot_tracks(PF_track1, [0, 2], line=dict(color="orange"), track_label='PF partial track 1')
-plotter.plot_tracks(PF_track2, [0, 2], line=dict(color="gold"), track_label='PF partial track 2')
-plotter.plot_tracks(PF_fused_track, [0, 2], line=dict(color="red"), track_label='PF fused track')
-plotter.plot_tracks(KF_fused_track, [0, 2], line=dict(color="blue"), track_label='KF fused track')
-plotter.plot_tracks(KF_track1, [0, 2], line=dict(color="cyan"), track_label='KF partial track 1')
-plotter.plot_tracks(KF_track2, [0, 2], line=dict(color="skyblue"), track_label='KF partial track 2')
+plotter.plot_tracks(PF_track1, [0, 2], line=dict(color="orange"), label='PF partial track 1')
+plotter.plot_tracks(PF_track2, [0, 2], line=dict(color="gold"), label='PF partial track 2')
+plotter.plot_tracks(PF_fused_track, [0, 2], line=dict(color="red"), label='PF fused track')
+plotter.plot_tracks(KF_fused_track, [0, 2], line=dict(color="blue"), label='KF fused track')
+plotter.plot_tracks(KF_track1, [0, 2], line=dict(color="cyan"), label='KF partial track 1')
+plotter.plot_tracks(KF_track2, [0, 2], line=dict(color="skyblue"), label='KF partial track 2')
 
 plotter.fig
 

docs/tutorials/filters/AKKF.py

@@ -429,7 +429,7 @@
 
 plotter = Plotter()
 plotter.plot_ground_truths(truth, [0, 2], linewidth=3.0, color='black')
-plotter.plot_tracks(track, [0, 2], track_label='AKKF - quadratic', color='royalblue')
+plotter.plot_tracks(track, [0, 2], label='AKKF - quadratic', color='royalblue')
 plotter.fig
 
 # %%

docs/tutorials/filters/ASDFilter.py

@@ -189,9 +189,9 @@
 asd_states = sorted(asd_states, key=attrgetter('timestamp'))
 
 plotter.plot_tracks({track2}, [0, 2], uncertainty=True, line=dict(color='green'),
-                    track_label="Equivalent track without ASD")
+                    label="Equivalent track without ASD")
 plotter.plot_tracks({Track(asd_states)}, [0, 2], line=dict(color='red'),
-                    track_label="ASD Track")
+                    label="ASD Track")
 plotter.fig
 
 # %%