Detect if ptp is enabled based on rec header

rec_to_nwb/processing/builder/nwb_file_builder.py

@@ -357,10 +357,29 @@ def __init__(
             else:
                 self.analog_originator = AnalogOriginator(self.datasets, self.metadata)
 
+        ptp_enabled = self._detect_ptp_from_header()
+
         self.position_originator = PositionOriginator(
-            self.datasets, self.metadata, self.dataset_names
+            self.datasets, self.metadata, self.dataset_names, ptp_enabled
         )
 
+    def _detect_ptp_from_header(self):
+        mconf = self.header.tree.find("ModuleConfiguration")
+        ptp_enabled = False
+        for smconf in mconf.findall("SingleModuleConfiguration"):
+            if (
+                smconf.get("moduleName") == "cameraModule"
+                or smconf.get("moduleName") == "./cameraModule"
+            ):
+                for arg in smconf.findall("Argument"):
+                    ptp_enabled = "-ptpEnabled" in arg.attrib.values()
+                    if ptp_enabled:
+                        break
+                if ptp_enabled:
+                    break
+        logger.info("PTP enabled: " + str(ptp_enabled))
+        return ptp_enabled
+
     def __extract_datasets(self, animal_name, date):
         self.data_scanner.extract_data_from_date_folder(date)
         self.datasets = [

rec_to_nwb/processing/builder/originators/position_originator.py

@@ -26,13 +26,16 @@
 
 class PositionOriginator:
     @beartype
-    def __init__(self, datasets: list, metadata: dict, dataset_names: list):
+    def __init__(
+        self, datasets: list, metadata: dict, dataset_names: list, ptp_enabled: bool
+    ):
         self.datasets = datasets
         self.dataset_names = dataset_names
         self.metadata = metadata
         self.pm_creator = ProcessingModule(
             "behavior", "Contains all behavior-related data"
         )
+        self.ptp_enabled = ptp_enabled
 
     @beartype
     def make(self, nwb_content: NWBFile):
@@ -51,7 +54,7 @@ def make(self, nwb_content: NWBFile):
                     os.path.join(pos_path, "*.pos_online.dat")
                 )
                 position_df = self.get_position_with_corrected_timestamps(
-                    position_tracking_path[0]
+                    position_tracking_path[0], self.ptp_enabled
                 )
                 position.create_spatial_series(
                     name=f"series_{dataset_ind}",
@@ -67,7 +70,7 @@ def make(self, nwb_content: NWBFile):
                     os.path.join(pos_path, "*.pos_cameraHWFrameCount.dat")
                 )
                 video_df = self.get_corrected_timestamps_without_position(
-                    video_file_path[0]
+                    video_file_path[0], self.ptp_enabled
                 )
                 position.create_spatial_series(
                     name=f"series_{dataset_ind}",
@@ -87,7 +90,7 @@ def make(self, nwb_content: NWBFile):
         nwb_content.processing["behavior"].add(position)
 
     @staticmethod
-    def get_position_with_corrected_timestamps(position_tracking_path):
+    def get_position_with_corrected_timestamps(position_tracking_path, ptp_enabled):
         logger.info(os.path.split(position_tracking_path)[-1])
 
         # Get position tracking information
@@ -123,10 +126,6 @@ def get_position_with_corrected_timestamps(position_tracking_path):
         # Get the timestamps from the neural data
         mcu_neural_timestamps = get_mcu_neural_timestamps(position_tracking_path)
 
-        # Determine whether the precision time protocol is being used
-        # which gives accurate timestamps associated with each video frame.
-        ptp_enabled = detect_ptp(mcu_neural_timestamps, video_info.HWTimestamp)
-
         # Get the camera time from the DIOs
         dio_camera_ticks = find_camera_dio_channel(position_tracking_path, video_info)
         is_valid_tick = np.isin(dio_camera_ticks, mcu_neural_timestamps.index)
@@ -226,7 +225,7 @@ def get_position_with_corrected_timestamps(position_tracking_path):
             )
 
     @staticmethod
-    def get_corrected_timestamps_without_position(hw_frame_count_path):
+    def get_corrected_timestamps_without_position(hw_frame_count_path, ptp_enabled):
         video_info = readTrodesExtractedDataFile(hw_frame_count_path)
         video_info = pd.DataFrame(video_info["data"]).set_index("PosTimestamp")
         # On AVT cameras, HWFrame counts wraps to 0 above this value.
@@ -242,10 +241,6 @@ def get_corrected_timestamps_without_position(hw_frame_count_path):
         # Get the timestamps from the neural data
         mcu_neural_timestamps = get_mcu_neural_timestamps(hw_frame_count_path)
 
-        # Determine whether the precision time protocol is being used
-        # which gives accurate timestamps associated with each video frame.
-        ptp_enabled = detect_ptp(mcu_neural_timestamps, video_info.HWTimestamp)
-
         # Get the camera time from the DIOs
         try:
             dio_camera_ticks = find_camera_dio_channel(hw_frame_count_path, video_info)