remove H5DataIO references

src/ibl_to_nwb/datainterfaces/_brainwide_map_trials.py

@@ -4,7 +4,7 @@
 from neuroconv.basedatainterface import BaseDataInterface
 from neuroconv.utils import load_dict_from_file
 from one.api import ONE
-from pynwb import H5DataIO, NWBFile
+from pynwb import NWBFile
 from pynwb.epoch import TimeIntervals
 
 
@@ -19,15 +19,6 @@ def get_metadata(self) -> dict:
         metadata.update(trial_metadata)
         return metadata
 
-    def get_original_timestamps(self):
-        pass
-
-    def get_timestamps(self):
-        pass
-
-    def align_timestamps(self):
-        pass
-
     def add_to_nwbfile(self, nwbfile: NWBFile, metadata: dict):
         trials = self.one.load_object(id=self.session, obj="trials", collection="alf")
 
@@ -49,20 +40,20 @@ def add_to_nwbfile(self, nwbfile: NWBFile, metadata: dict):
             VectorData(
                 name="start_time",
                 description="The beginning of the trial.",
-                data=H5DataIO(trials["intervals"][:, 0], compression=True),
+                data=trials["intervals"][:, 0],
             ),
             VectorData(
                 name="stop_time",
                 description="The end of the trial.",
-                data=H5DataIO(trials["intervals"][:, 1], compression=True),
+                data=trials["intervals"][:, 1],
             ),
         ]
         for ibl_key in column_ordering:
             columns.append(
                 VectorData(
                     name=metadata["Trials"][ibl_key]["name"],
                     description=metadata["Trials"][ibl_key]["description"],
-                    data=H5DataIO(trials[ibl_key], compression=True),
+                    data=trials[ibl_key],
                 )
             )
         nwbfile.add_time_intervals(
@@ -72,14 +63,3 @@ def add_to_nwbfile(self, nwbfile: NWBFile, metadata: dict):
                 columns=columns,
             )
         )
-
-        # compression only works using the method above; method below fails
-        # for start_time, stop_time in trials["intervals"]:
-        #    nwbfile.add_trial(start_time=start_time, stop_time=stop_time)
-
-        # for ibl_key in column_ordering:
-        #    nwbfile.add_trial_column(
-        #        name=metadata["Trials"][ibl_key]["name"],
-        #        description=metadata["Trials"][ibl_key]["description"],
-        #        data=H5DataIO(trials[ibl_key], compression=True),
-        #    )

src/ibl_to_nwb/datainterfaces/_lick_times.py

@@ -2,7 +2,7 @@
 from neuroconv.basedatainterface import BaseDataInterface
 from neuroconv.tools.nwb_helpers import get_module
 from one.api import ONE
-from pynwb import H5DataIO
+from pynwb import NWBFile
 from pynwb.file import DynamicTable
 
 
@@ -11,16 +11,7 @@ def __init__(self, one: ONE, session: str):
         self.one = one
         self.session = session
 
-    def get_original_timestamps(self):
-        pass
-
-    def get_timestamps(self):
-        pass
-
-    def align_timestamps(self):
-        pass
-
-    def add_to_nwbfile(self, nwbfile, metadata: dict):
+    def add_to_nwbfile(self, nwbfile: NWBFile, metadata: dict):
         licks = self.one.load_object(id=self.session, obj="licks", collection="alf")
 
         lick_events_table = DynamicTable(
@@ -33,15 +24,10 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
                 VectorData(
                     name="lick_time",
                     description="Time stamps of licks as detected from tongue dlc traces",
-                    data=H5DataIO(licks["times"], compression=True),
+                    data=licks["times"],
                 )
             ],
         )
-        # lick_events_table.add_column(
-        #    name="lick_time",
-        #    description="Time stamps of licks as detected from tongue dlc traces",
-        #    data=H5DataIO(licks["times"], compression=True),
-        # )
 
         behavior_module = get_module(nwbfile=nwbfile, name="behavior", description="Processed behavioral data.")
         behavior_module.add(lick_events_table)

src/ibl_to_nwb/datainterfaces/_pose_estimation.py

@@ -5,7 +5,7 @@
 from neuroconv.basedatainterface import BaseDataInterface
 from neuroconv.tools.nwb_helpers import get_module
 from one.api import ONE
-from pynwb import H5DataIO
+from pynwb import NWBFile
 from pynwb.image import ImageSeries
 
 
@@ -17,16 +17,7 @@ def __init__(self, one: ONE, session: str, camera_name: str, include_video: bool
         self.include_video = include_video
         self.include_pose = include_pose
 
-    def get_original_timestamps(self):
-        pass
-
-    def get_timestamps(self):
-        pass
-
-    def align_timestamps(self):
-        pass
-
-    def add_to_nwbfile(self, nwbfile, metadata: dict):
+    def add_to_nwbfile(self, nwbfile: NWBFile, metadata: dict):
         # Sometimes the DLC data has been revised, possibly multiple times
         # Always use the most recent revision available
         session_files = self.one.list_datasets(eid=self.session, filename=f"*{self.camera_name}.dlc*")
@@ -50,7 +41,6 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
         )
 
         left_right_or_body = self.camera_name[:5].rstrip("C")
-        # camera_name_snake_case = f"{left_right_or_body}_camera"
         reused_timestamps = None
         all_pose_estimation_series = list()
         if self.include_pose:
@@ -62,15 +52,15 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
                 pose_estimation_series = PoseEstimationSeries(
                     name=body_part,
                     description=f"Marker placed on or around, labeled '{body_part}'.",
-                    data=H5DataIO(body_part_data, compression=True),
+                    data=body_part_data,
                     unit="px",
                     reference_frame="(0,0) corresponds to the upper left corner when using width by height convention.",
-                    timestamps=reused_timestamps or H5DataIO(timestamps, compression=True),
+                    timestamps=reused_timestamps or timestamps,
                     confidence=np.array(dlc_data[f"{body_part}_likelihood"]),
                 )
                 all_pose_estimation_series.append(pose_estimation_series)
 
-                reused_timestamps = all_pose_estimation_series[0]  # trick for linking timestamps across series
+                reused_timestamps = all_pose_estimation_series[0]  # A trick for linking timestamps across series
 
             pose_estimation_kwargs = dict(
                 name=f"PoseEstimation{left_right_or_body.capitalize()}Camera",
@@ -88,7 +78,7 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
         ):
             all_pose_estimation_series.append(pose_estimation_series)
 
-            reused_timestamps = all_pose_estimation_series[0]  # trick for linking timestamps across series
+            reused_timestamps = all_pose_estimation_series[0]  # A trick for linking timestamps across series
 
             original_video_file = self.one.load_dataset(
                 id=self.session, dataset=f"raw_video_data/*{self.camera_name}*", download_only=True
@@ -99,7 +89,6 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
                 unit="n.a.",
                 external_file=[str(original_video_file)],
                 format="external",
-                timestamps=reused_timestamps or H5DataIO(timestamps, compression=True),
+                timestamps=reused_timestamps or timestamps,
             )
-            # pose_estimation_kwargs.update(original_videos_series=[image_series])  # For future version of ndx-pose
             nwbfile.add_acquisition(image_series)

src/ibl_to_nwb/datainterfaces/_pupil_tracking.py

@@ -7,7 +7,7 @@
 from neuroconv.tools.nwb_helpers import get_module
 from neuroconv.utils import load_dict_from_file
 from one.api import ONE
-from pynwb import H5DataIO, TimeSeries
+from pynwb import TimeSeries
 from pynwb.behavior import PupilTracking
 
 
@@ -25,15 +25,6 @@ def get_metadata(self) -> dict:
 
         return metadata
 
-    def get_original_timestamps(self):
-        pass
-
-    def get_timestamps(self):
-        pass
-
-    def align_timestamps(self):
-        pass
-
     def add_to_nwbfile(self, nwbfile, metadata: dict):
         left_or_right = self.camera_name[:5].rstrip("C")
 
@@ -45,7 +36,7 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
                 TimeSeries(
                     name=left_or_right.capitalize() + metadata["Pupils"][ibl_key]["name"],
                     description=metadata["Pupils"][ibl_key]["description"],
-                    data=H5DataIO(np.array(camera_data["features"][ibl_key]), compression=True),
+                    data=np.array(camera_data["features"][ibl_key]),
                     timestamps=camera_data["times"],
                     unit="px",
                 )

src/ibl_to_nwb/datainterfaces/_roi_motion_energy.py

@@ -3,7 +3,7 @@
 from neuroconv.basedatainterface import BaseDataInterface
 from neuroconv.tools.nwb_helpers import get_module
 from one.api import ONE
-from pynwb import H5DataIO, TimeSeries
+from pynwb import TimeSeries
 
 
 class RoiMotionEnergyInterface(BaseDataInterface):
@@ -12,15 +12,6 @@ def __init__(self, one: ONE, session: str, camera_name: str):
         self.session = session
         self.camera_name = camera_name
 
-    def get_original_timestamps(self):
-        pass
-
-    def get_timestamps(self):
-        pass
-
-    def align_timestamps(self):
-        pass
-
     def add_to_nwbfile(self, nwbfile, metadata: dict):
         left_right_or_body = self.camera_name[:5].rstrip("C")
 
@@ -42,8 +33,8 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
         motion_energy_series = TimeSeries(
             name=f"{left_right_or_body.capitalize()}CameraMotionEnergy",
             description=description,
-            data=H5DataIO(camera_data["ROIMotionEnergy"]),
-            timestamps=H5DataIO(camera_data["times"]),
+            data=camera_data["ROIMotionEnergy"],
+            timestamps=camera_data["times"],
             unit="a.u.",
         )
 

src/ibl_to_nwb/datainterfaces/_wheel_movement.py

@@ -5,7 +5,7 @@
 from neuroconv.tools.nwb_helpers import get_module
 from neuroconv.utils import load_dict_from_file
 from one.api import ONE
-from pynwb import H5DataIO, TimeSeries
+from pynwb import TimeSeries
 from pynwb.behavior import CompassDirection, SpatialSeries
 from pynwb.epoch import TimeIntervals
 
@@ -22,15 +22,6 @@ def get_metadata(self) -> dict:
 
         return metadata
 
-    def get_original_timestamps(self):
-        pass
-
-    def get_timestamps(self):
-        pass
-
-    def align_timestamps(self):
-        pass
-
     def add_to_nwbfile(self, nwbfile, metadata: dict):
         wheel_moves = self.one.load_object(id=self.session, obj="wheelMoves", collection="alf")
         wheel = self.one.load_object(id=self.session, obj="wheel", collection="alf")
@@ -56,32 +47,32 @@ def add_to_nwbfile(self, nwbfile, metadata: dict):
         wheel_movement_intervals.add_column(
             name=metadata["WheelMovement"]["columns"]["peakAmplitude"]["name"],
             description=metadata["WheelMovement"]["columns"]["peakAmplitude"]["description"],
-            data=H5DataIO(wheel_moves["peakAmplitude"], compression=True),
+            data=wheel_moves["peakAmplitude"],
         )
 
         # Wheel position over time
         compass_direction = CompassDirection(
             spatial_series=SpatialSeries(
                 name=metadata["WheelPosition"]["name"],
                 description=metadata["WheelPosition"]["description"],
-                data=H5DataIO(wheel["position"], compression=True),
-                timestamps=H5DataIO(wheel["timestamps"], compression=True),
+                data=wheel["position"],
+                timestamps=wheel["timestamps"],
                 unit="rad",
                 reference_frame="Initial angle at start time is zero. Counter-clockwise is positive.",
             )
         )
         velocity_series = TimeSeries(
             name=metadata["WheelVelocity"]["name"],
             description=metadata["WheelVelocity"]["description"],
-            data=H5DataIO(velocity, compression=True),
+            data=velocity,
             starting_time=interpolated_starting_time,
             rate=interpolated_rate,
             unit="rad/s",
         )
         acceleration_series = TimeSeries(
             name=metadata["WheelAcceleration"]["name"],
             description=metadata["WheelAcceleration"]["description"],
-            data=H5DataIO(acceleration, compression=True),
+            data=acceleration,
             starting_time=interpolated_starting_time,
             rate=interpolated_rate,
             unit="rad/s^2",