Merge pull request #17 from catalystneuro/add_suite2p

Add suite2p interface

src/higley_lab_to_nwb/benisty_2024/benisty_2024_convert_session.py

@@ -5,7 +5,6 @@
 from neuroconv.utils import load_dict_from_file, dict_deep_update
 from higley_lab_to_nwb.benisty_2024 import Benisty2024NWBConverter
 import os
-import glob
 
 
 def session_to_nwb(
@@ -17,21 +16,30 @@ def session_to_nwb(
         output_dir_path = output_dir_path / "nwb_stub"
     output_dir_path.mkdir(parents=True, exist_ok=True)
 
-    nwbfile_path = output_dir_path / f"{session_id}_new.nwb"
+    nwbfile_path = output_dir_path / f"{session_id}.nwb"
 
     source_data = dict()
     conversion_options = dict()
 
-    search_pattern = "_".join(session_id.split("_")[:2])
+    # Add 2p Imaging
+    imaging_path = folder_path / "tiff"    
+    source_data.update(dict(TwoPhotonImagingGreenChannel=dict(folder_path=str(imaging_path), file_pattern="*.tif")))
+    conversion_options.update(dict(TwoPhotonImagingGreenChannel=dict(stub_test=stub_test)))
 
-    converter = Benisty2024NWBConverter(
-        source_data=source_data,
-    )
+    # Add Segmentation
+    suite2p_path = folder_path / "suite2p"
+    source_data.update(dict(SegmentationGreenChannel=dict(folder_path=suite2p_path)))
+    conversion_options.update(dict(SegmentationGreenChannel=dict(stub_test=stub_test)))
+
+    # Add ophys metadata
+    ophys_metadata_path = Path(__file__).parent / "metadata" / "benisty_2024_ophys_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()
-    date = read_session_start_time(folder_path=folder_path)
-    metadata["NWBFile"]["session_start_time"] = date
     subject_id = session_id.split("_")[1]
     metadata["Subject"].update(subject_id=subject_id)
     metadata["NWBFile"].update(session_id=session_id)
@@ -41,11 +49,6 @@ def session_to_nwb(
     editable_metadata = load_dict_from_file(editable_metadata_path)
     metadata = dict_deep_update(metadata, editable_metadata)
 
-    # Add ophys metadata
-    ophys_metadata_path = Path(__file__).parent / "metadata" / "benisty_2024_ophys_metadata.yaml"
-    ophys_metadata = load_dict_from_file(ophys_metadata_path)
-    metadata = dict_deep_update(metadata, ophys_metadata)
-
     # Run conversion
     converter.run_conversion(
         metadata=metadata, nwbfile_path=nwbfile_path, conversion_options=conversion_options, overwrite=True
@@ -60,7 +63,7 @@ def session_to_nwb(
     output_dir_path = root_path / "Higley-conversion_nwb/"
     stub_test = True
     session_ids = os.listdir(data_dir_path)
-    session_id = "11222019_grabAM06_vis_stim"
+    session_id = "04072021_am2psi_05_spont"
     folder_path = data_dir_path / Path(session_id)
     session_to_nwb(
         folder_path=folder_path,

src/higley_lab_to_nwb/benisty_2024/benisty_2024_nwbconverter.py

@@ -1,12 +1,29 @@
 """Primary NWBConverter class for this dataset."""
 
-from typing import Dict, List
+from typing import Dict
 from neuroconv import NWBConverter
-
-
+from neuroconv.datainterfaces import ScanImageMultiFileImagingInterface, Suite2pSegmentationInterface
+from neuroconv.utils import DeepDict
 
 class Benisty2024NWBConverter(NWBConverter):
     """Primary conversion class."""
 
     data_interface_classes = dict(
-    )
+        TwoPhotonImagingGreenChannel=ScanImageMultiFileImagingInterface,
+        SegmentationGreenChannel=Suite2pSegmentationInterface,
+    )
+    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
+
+    def get_metadata(self) -> DeepDict:
+        metadata = super().get_metadata()
+        segmentation_metadata = self.data_interface_objects["SegmentationGreenChannel"].get_metadata()
+        for segmentation_metadata_ind in range(len(segmentation_metadata["Ophys"]["ImageSegmentation"]["plane_segmentations"])):
+            metadata["Ophys"]["ImageSegmentation"]["plane_segmentations"][segmentation_metadata_ind]["imaging_plane"] = self.ophys_metadata["Ophys"]["ImagingPlane"][0]["name"]
+
+        metadata["Ophys"]["Device"] = self.ophys_metadata["Ophys"]["Device"]
+        metadata["Ophys"]["TwoPhotonSeries"] = self.ophys_metadata["Ophys"]["TwoPhotonSeries"]
+        metadata["Ophys"]["ImagingPlane"] = self.ophys_metadata["Ophys"]["ImagingPlane"]
+
+        return metadata

src/higley_lab_to_nwb/benisty_2024/metadata/benisty_2024_ophys_metadata.yaml

@@ -1,4 +1,21 @@
 Ophys:
   Device:
-  OnePhotonSeries:
-  ImagingPlane:
+    - name: TwoPhotonMicroscope
+      description: MOM microscope (Sutter Instruments) coupled to a 16x, 0.8 NA objective (Nikon). Excitation was driven by a Titanium-Sapphire Laser (Mai-Tai eHP DeepSee, Spectra-Physics).
+      manufacturer: Sutter Instruments
+  TwoPhotonSeries:
+    - name: TwoPhotonSeriesGreenChannel
+      description: Imaging data from Green channel recorded with 2p microscope. Images were acquired at 512x512 resolution at 30 Hz using a galvo-resonant scan system controlled by ScanImage software (Vidrio).
+      imaging_plane: ImagingPlaneGreenChannel
+      unit: n.a.
+  ImagingPlane:
+    - name: ImagingPlaneGreenChannel
+      description: Imaging plane for the Green channel recorded with 2p microscope.
+      excitation_lambda: 920.0  # in nm
+      location: Whole Brain
+      device: TwoPhotonMicroscope
+      optical_channel:
+        - name: Green
+          description: Emitted light was collected through a 525/50 filter and a gallium arsenide phosphide photomultiplier tube (Hamamatsu).
+          emission_lambda: 525.0
+      indicator: GCaMP6s