2p only conversion

src/higley_lab_to_nwb/benisty_2024/benisty_2024_convert_session.py → src/higley_lab_to_nwb/benisty_2024/benisty_2024_convert_2p_only_session.py

@@ -4,8 +4,9 @@
 from typing import Union
 from neuroconv.utils import load_dict_from_file, dict_deep_update
 from higley_lab_to_nwb.benisty_2024 import Benisty2024NWBConverter
+from higley_lab_to_nwb.lohani_2022.interfaces.lohani_2022_spike2signals_interface import get_streams
 import os
-
+import glob
 
 def _get_sampling_frequency_and_image_size(folder_path: Union[str, Path]):
     from roiextractors.extractors.tiffimagingextractors.scanimagetiff_utils import (
@@ -27,7 +28,6 @@ def _get_sampling_frequency_and_image_size(folder_path: Union[str, Path]):
     image_size = [_num_rows, _num_columns]
     return parsed_metadata["sampling_frequency"], image_size
 
-
 def session_to_nwb(
     folder_path: Union[str, Path], output_dir_path: Union[str, Path], session_id: str, stub_test: bool = False
 ):
@@ -42,6 +42,45 @@ def session_to_nwb(
     source_data = dict()
     conversion_options = dict()
 
+    search_pattern = "_".join(session_id.split("_")[:2])
+
+    # Add Analog signals from Spike2
+    file_path = glob.glob(os.path.join(folder_path, f"{search_pattern}*.smrx"))[0]
+    stream_ids, stream_names = get_streams(file_path=file_path)
+
+    # Define each smrx signal name
+    TTLsignals_name_map = {
+        stream_ids[stream_names == "galvo"][0]: "TTLSignal2PExcitation",
+        stream_ids[stream_names == "pupilcam"][0]: "TTLSignalPupilCamera",
+    }
+    behavioral_name_map = {
+        stream_ids[stream_names == "wheel"][0]: "WheelSignal",
+    }
+
+    source_data.update(
+        dict(
+            Spike2Signals=dict(
+                file_path=file_path,
+                ttl_stream_ids_to_names_map=TTLsignals_name_map,
+                behavioral_stream_ids_to_names_map=behavioral_name_map,
+            )
+        )
+    )
+    conversion_options.update(dict(Spike2Signals=dict(stub_test=stub_test)))
+
+    if "vis_stim" in session_id:
+        csv_file_path = glob.glob(os.path.join(folder_path, f"{search_pattern}*.csv"))[0]
+        source_data.update(
+            dict(
+                VisualStimulusInterface=dict(
+                    spike2_file_path=file_path,
+                    csv_file_path=csv_file_path,
+                    stream_id=stream_ids[stream_names == "Vis"][0],
+                )
+            )
+        )
+        conversion_options.update(dict(VisualStimulusInterface=dict(stub_test=stub_test)))
+
     # Add 2p Imaging
     imaging_path = folder_path / "tiff"
     source_data.update(dict(TwoPhotonImaging=dict(folder_path=str(imaging_path), file_pattern="*.tif")))
@@ -84,14 +123,28 @@ def session_to_nwb(
         )
     )
 
+    # Add Behavioral Video Recording
+    avi_files = glob.glob(os.path.join(folder_path, f"{search_pattern}*.avi"))
+    video_file_path = avi_files[0]
+    source_data.update(dict(Video=dict(file_paths=[video_file_path], verbose=False)))
+    conversion_options.update(dict(Video=dict(stub_test=stub_test)))
+
+    # Add Facemap outpt
+    # mat_files = glob.glob(os.path.join(folder_path, f"{search_pattern}*_proc.mat"))
+    # mat_file_path = mat_files[0]
+    # source_data.update(
+    #     dict(
+    #         FacemapInterface=dict(mat_file_path=str(mat_file_path), video_file_path=str(video_file_path), verbose=False)
+    #     )
+    # )
+
     # Add ophys metadata
-    ophys_metadata_path = Path(__file__).parent / "metadata" / "benisty_2024_ophys_metadata.yaml"
+    ophys_metadata_path = Path(__file__).parent / "metadata" / "benisty_2024_ophys_2p_only_metadata.yaml"
     ophys_metadata = load_dict_from_file(ophys_metadata_path)
 
     converter = Benisty2024NWBConverter(source_data=source_data, ophys_metadata=ophys_metadata)
 
     # Add datetime to conversion
-
     metadata = converter.get_metadata()
     subject_id = session_id.split("_")[1]
     metadata["Subject"].update(subject_id=subject_id)

src/higley_lab_to_nwb/benisty_2024/benisty_2024_convert_all_sessions.py

@@ -1,9 +1,8 @@
 """Primary script to run to convert an entire session for of data using the NWBConverter."""
 
 from pathlib import Path
-from typing import Union
 import os
-from .benisty_2024_convert_session import session_to_nwb
+from .benisty_2024_convert_2p_only_session import session_to_nwb
 
 
 

src/higley_lab_to_nwb/benisty_2024/benisty_2024_nwbconverter.py

@@ -5,6 +5,12 @@
 from neuroconv.utils import DeepDict
 
 from neuroconv.datainterfaces import ScanImageMultiFileImagingInterface, Suite2pSegmentationInterface
+from higley_lab_to_nwb.lohani_2022.interfaces import (
+    Lohani2022Spike2SignalsInterface,
+    Lohani2022VisualStimulusInterface,
+)
+from neuroconv.datainterfaces import VideoInterface, FacemapInterface
+
 from .interfaces import Benisty2024CidanSegmentationInterface
 from higley_lab_to_nwb.lohani_2022.interfaces import Lohani2022Spike2SignalsInterface
 class Benisty2024NWBConverter(NWBConverter):
@@ -13,13 +19,16 @@ class Benisty2024NWBConverter(NWBConverter):
     data_interface_classes = dict(
         TwoPhotonImaging=ScanImageMultiFileImagingInterface,
         Suite2pSegmentation=Suite2pSegmentationInterface,
-        CIDANSegmentation=Benisty2024CidanSegmentationInterface,
         Spike2Signals=Lohani2022Spike2SignalsInterface,
+        CIDANSegmentation=Benisty2024CidanSegmentationInterface,
+        Video=VideoInterface,
+        FacemapInterface=FacemapInterface,
+        VisualStimulusInterface=Lohani2022VisualStimulusInterface,
     )
 
-    def __init__(self, source_data: Dict[str, dict],ophys_metadata: Dict[str, dict],  verbose: bool = True):
+    def __init__(self, source_data: Dict[str, dict], ophys_metadata: Dict[str, dict], verbose: bool = True):
         super().__init__(source_data, verbose)
-        self.ophys_metadata=ophys_metadata
+        self.ophys_metadata = ophys_metadata
 
     def get_metadata(self) -> DeepDict:
         metadata = super().get_metadata()
@@ -38,7 +47,7 @@ def get_metadata(self) -> DeepDict:
         metadata["Ophys"]["ImagingPlane"] = self.ophys_metadata["Ophys"]["ImagingPlane"]
 
         return metadata
-    
+
     def temporally_align_data_interfaces(self):
         ttlsignal_interface = self.data_interface_objects["Spike2Signals"]
         # Synch imaging
@@ -54,4 +63,20 @@ def temporally_align_data_interfaces(self):
         )
         ttl_times = ttlsignal_interface.get_event_times_from_ttl(stream_id=stream_id)
         imaging_interface.set_aligned_starting_time(ttl_times[0])
-        segmentation_interface.set_aligned_starting_time(ttl_times[0])
+        segmentation_interface.set_aligned_starting_time(ttl_times[0])
+
+        # Synch behaviour
+        video_interface = self.data_interface_objects["Video"]
+        # facemap_interface = self.data_interface_objects["FacemapInterface"]
+        video_interface._timestamps = video_interface.get_timestamps()
+        stream_id = next(
+            (
+                stream_id
+                for stream_id, stream_name in ttlsignal_interface.ttl_stream_ids_to_names_map.items()
+                if stream_name == "TTLSignalPupilCamera"
+            ),
+            None,
+        )
+        ttl_times = ttlsignal_interface.get_event_times_from_ttl(stream_id=stream_id)
+        video_interface.set_aligned_starting_time(ttl_times[0])
+        # facemap_interface.set_aligned_starting_time(ttl_times[0])

src/higley_lab_to_nwb/benisty_2024/benisty_2024_requirements.txt

@@ -1,4 +1,5 @@
 nwb-conversion-tools==0.11.1   # Example of specific pinned dependecy
 some-extra-package==1.11.3  # Example of another extra package that's necessary for the current conversion
 roiextractors
-neuroconv @ git+https://github.com/catalystneuro/neuroconv.git@facemap
+neuroconv @ git+https://github.com/catalystneuro/neuroconv.git@facemap
+ndx-facemap-motionsvd @ git+https://github.com/catalystneuro/ndx-facemap-motionsvd.git@main