Explicitly convert to numpy uint32 type where appropriate.

`dtype=int` converts to the C `long` data type. On 64b Linux, that defaults to
`int64_t`. On Windows however, even 64b, it is `int32_t`.

Using `dtype=int` on Windows will raise an OverflowError when trying to convert
uint32_t 0xFFFFFFFF values.

python/fusion_engine_client/analysis/data_loader.py

@@ -67,7 +67,7 @@ def to_numpy(self, remove_nan_times: bool = True):
 
             if do_conversion:
                 self.__dict__.update(self.message_class.to_numpy(self.messages))
-                self.messages_bytes = np.array(self.messages_bytes, dtype=int)
+                self.messages_bytes = np.array(self.messages_bytes, dtype=np.uint64)
                 self.message_index = np.array(self.message_index, dtype=int)
 
                 if remove_nan_times and 'p1_time' in self.__dict__:

python/fusion_engine_client/messages/measurements.py

@@ -592,10 +592,10 @@ def __str__(self):
     @classmethod
     def to_numpy(cls, messages):
         result = {
-            'front_left_wheel_ticks': np.array([m.front_left_wheel_ticks for m in messages], dtype=int),
-            'front_right_wheel_ticks': np.array([m.front_right_wheel_ticks for m in messages], dtype=int),
-            'rear_left_wheel_ticks': np.array([m.rear_left_wheel_ticks for m in messages], dtype=int),
-            'rear_right_wheel_ticks': np.array([m.rear_right_wheel_ticks for m in messages], dtype=int),
+            'front_left_wheel_ticks': np.array([m.front_left_wheel_ticks for m in messages], dtype=np.uint32),
+            'front_right_wheel_ticks': np.array([m.front_right_wheel_ticks for m in messages], dtype=np.uint32),
+            'rear_left_wheel_ticks': np.array([m.rear_left_wheel_ticks for m in messages], dtype=np.uint32),
+            'rear_right_wheel_ticks': np.array([m.rear_right_wheel_ticks for m in messages], dtype=np.uint32),
             'gear': np.array([m.gear for m in messages], dtype=int),
         }
         result.update(MeasurementDetails.to_numpy([m.details for m in messages]))
@@ -690,7 +690,7 @@ def __str__(self):
     @classmethod
     def to_numpy(cls, messages):
         result = {
-            'tick_count': np.array([m.tick_count for m in messages], dtype=int),
+            'tick_count': np.array([m.tick_count for m in messages], dtype=np.uint32),
             'gear': np.array([m.gear for m in messages], dtype=int),
         }
         result.update(MeasurementDetails.to_numpy([m.details for m in messages]))
@@ -1003,7 +1003,7 @@ def calcsize(cls) -> int:
     def to_numpy(cls, messages: Sequence['HeadingOutput']):
         result = {
             'solution_type': np.array([int(m.solution_type) for m in messages], dtype=int),
-            'flags': np.array([int(m.flags) for m in messages], dtype=int),
+            'flags': np.array([int(m.flags) for m in messages], dtype=np.uint32),
             'ypr_deg': np.array([m.ypr_deg for m in messages]).T,
             'heading_true_north_deg': np.array([m.heading_true_north_deg for m in messages], dtype=float).T,
         }
@@ -1122,7 +1122,7 @@ def calcsize(cls) -> int:
     def to_numpy(cls, messages: Sequence['RawHeadingOutput']):
         result = {
             'solution_type': np.array([int(m.solution_type) for m in messages], dtype=int),
-            'flags': np.array([int(m.flags) for m in messages], dtype=int),
+            'flags': np.array([int(m.flags) for m in messages], dtype=np.uint32),
             'relative_position_enu_m': np.array([m.relative_position_enu_m for m in messages]).T,
             'position_std_enu_m': np.array([m.position_std_enu_m for m in messages]).T,
             'heading_true_north_deg': np.array([float(m.heading_true_north_deg) for m in messages]),

python/fusion_engine_client/messages/solution.py

@@ -387,7 +387,7 @@ def to_numpy(cls, messages):
             'num_svs': np.array([int(m.num_svs) for m in messages], dtype=int),
             'corrections_age_sec': np.array([m.corrections_age_sec for m in messages]),
             'baseline_distance_m': np.array([m.baseline_distance_m for m in messages]),
-            'reference_station_id': np.array([int(m.reference_station_id) for m in messages], dtype=int),
+            'reference_station_id': np.array([int(m.reference_station_id) for m in messages], dtype=np.uint32),
             'gdop': np.array([m.gdop for m in messages]),
             'pdop': np.array([m.pdop for m in messages]),
             'hdop': np.array([m.hdop for m in messages]),