Enhance data handling in SignalProvider and improve plotting behavior in MatplotlibViewerCanvas in case of signal with only one datapoint (#91)

Author: GiulioRomualdi

robot_log_visualizer/file_reader/signal_provider.py

@@ -126,8 +126,8 @@ def __populate_numerical_data(self, file_object):
                 continue
             if "data" in value.keys():
                 data[key] = {}
-                data[key]["data"] = np.squeeze(np.array(value["data"]))
-                data[key]["timestamps"] = np.squeeze(np.array(value["timestamps"]))
+                data[key]["data"] = np.atleast_1d(np.squeeze(np.array(value["data"])))
+                data[key]["timestamps"] = np.atleast_1d(np.squeeze(np.array(value["timestamps"])))
 
                 # if the initial or end time has been updated we can also update the entire timestamps dataset
                 if data[key]["timestamps"][0] < self.initial_time:

robot_log_visualizer/plotter/matplotlib_viewer_canvas.py

@@ -201,13 +201,23 @@ def update_plots(self, paths, legends):
 
                 timestamps = data["timestamps"] - self.signal_provider.initial_time
 
-                (self.active_paths[path_string],) = self.axes.plot(
-                    timestamps,
-                    datapoints,
-                    label=legend_string,
-                    picker=True,
-                    color=next(self.color_palette),
-                )
+                if timestamps.size > 1:
+                    (self.active_paths[path_string],) = self.axes.plot(
+                        timestamps,
+                        datapoints,
+                        label=legend_string,
+                        picker=True,
+                        color=next(self.color_palette),
+                    )
+                else:
+                    (self.active_paths[path_string],) = self.axes.plot(
+                        timestamps,
+                        datapoints,
+                        label=legend_string,
+                        picker=True,
+                        color=next(self.color_palette),
+                        marker="o",
+                    )
 
         paths_to_be_canceled = []
         for active_path in self.active_paths.keys():