Merge pull request #37 from catalystneuro/convert_all_sessions_Lohani22

Add all sessions conversion script for Lohani22

make_env.yml

@@ -3,7 +3,7 @@ channels:
 - conda-forge
 - defaults
 dependencies:
-- python>=3.9
+- python==3.9
 - pip
 - pip:
   - -e .  # This calls the setup and therefore requirements minimal

src/higley_lab_to_nwb/interfaces/external_stimuli_interface.py

@@ -93,7 +93,7 @@ def add_visual_stimulus(self, nwbfile: NWBFile, metadata: dict, stub_test: bool
 
         n_frames = 100 if stub_test and len(start_times) > 100 else len(start_times)
 
-        for frame in range(n_frames):
+        for frame in range(n_frames-1):
             intervals_table.add_row(
                 start_time=start_times[frame],
                 stop_time=stop_times[frame],

src/higley_lab_to_nwb/lohani_2022/lohani_2022_convert_all_sessions.py

@@ -1,25 +1,54 @@
 """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 .lohani_2022_convert_session import session_to_nwb
-
+from parse import parse
+from lohani_2022_convert_session import session_to_nwb
 
+from nwbinspector import inspect_all
+from nwbinspector.inspector_tools import save_report, format_messages
 
 # Parameters for conversion
-root_path = Path("/media/amtra/Samsung_T5/CN_data")
+root_path = Path("F:")
 data_dir_path = root_path / "Higley-CN-data-share"
 output_dir_path = root_path / "Higley-conversion_nwb/"
+stub_test = False
+verbose = True
+
+session_folder_format = "{date_string}_{subject_id}_{behavior_type}"
+
+raw_imaging_dir_path = data_dir_path / "Lohani22 Meso Data"
+for folder_path in raw_imaging_dir_path.iterdir():
+    if folder_path.is_dir():
+        session_id = folder_path.name
+        metadata = parse(session_folder_format, session_id)
+        if verbose:
+            print("-" * 80)
+            print(f"Converting session {session_id}")
 
-session_ids = os.listdir(data_dir_path)
-stub_test = True
-for session_id in session_ids:
-    session_folder = data_dir_path / Path(session_id)
-    if os.path.isdir(session_folder):
+        subject_id = metadata["subject_id"]
+        parcellation_folder_path = (
+            data_dir_path
+            / "Lohani22 Parcellated data"
+            / f"{subject_id.replace('AM', '')}"
+            / "imaging with 575 excitation"
+            / session_id
+        )
         session_to_nwb(
-            folder_path=session_folder,
+            folder_path=folder_path,
+            parcellation_folder_path=parcellation_folder_path,
             output_dir_path=output_dir_path,
             session_id=session_id,
             stub_test=stub_test,
+            verbose=verbose,
         )
+
+report_path = output_dir_path / "inspector_result.txt"
+if not report_path.exists():
+    results = list(inspect_all(path=output_dir_path))
+    save_report(
+        report_file_path=report_path,
+        formatted_messages=format_messages(
+            results,
+            levels=["importance", "file_path"],
+        ),
+    )

src/higley_lab_to_nwb/lohani_2022/lohani_2022_convert_session.py

@@ -18,6 +18,7 @@ def session_to_nwb(
     output_dir_path: Union[str, Path],
     session_id: str,
     stub_test: bool = False,
+    verbose: bool = True,
 ):
     output_dir_path = Path(output_dir_path)
     if stub_test:
@@ -210,10 +211,13 @@ def session_to_nwb(
     ophys_metadata_path = Path(__file__).parent / "metadata" / "lohani_2022_ophys_metadata.yaml"
     ophys_metadata = load_dict_from_file(ophys_metadata_path)
 
+    if verbose:
+        print("Start conversion")
     converter = Lohani2022NWBConverter(
         source_data=source_data,
         excitation_type_channel_combination=excitation_type_channel_combination,
         ophys_metadata=ophys_metadata,
+        verbose=verbose,
     )
 
     # Add datetime to conversion
@@ -237,17 +241,17 @@ def session_to_nwb(
 
 if __name__ == "__main__":
     # Parameters for conversion
-    root_path = Path("G:")
+    root_path = Path("F:")
     data_dir_path = root_path / "Higley-CN-data-share"
     output_dir_path = root_path / "Higley-conversion_nwb"
     stub_test = True
     date = "11232019"
     animal_number = "05"
     behavior = "airpuffs"
     session_id = f"{date}_grabAM{animal_number}_{behavior}"
-    folder_path = data_dir_path / session_id
+    folder_path = data_dir_path / "Lohani22 Meso Data" / session_id
     parcellation_folder_path = (
-        data_dir_path / "parcellation" / f"grab{animal_number}" / "imaging with 575 excitation" / session_id
+        data_dir_path / "Lohani22 Parcellated data" / f"grab{animal_number}" / "imaging with 575 excitation" / session_id
     )
     session_to_nwb(
         folder_path=folder_path,

src/higley_lab_to_nwb/lohani_2022/lohani_2022_metadata.yaml

@@ -8,7 +8,14 @@ NWBFile:
   institution: Yale University School of Medicine
   lab: Higley
   experimenter:
-    - Moberly, Andrew # others
+    - Lohani, Sweyta
+    - Moberly, Andrew
+    - Benisty, Hadas
+    - Landa, Boris
+    - Jing, Miao
+    - Li, Yulong
+    - Higley, Michael
+    - Cardin, Jessica
   surgery: All surgical implantation procedures were performed on adult mice (>P50D). Mice were anesthetized using 1-2% isoflurane and maintained at 37 °C for the duration of the surgery. The skin and fascia above the skull were removed from the nasal bone to the posterior of the intraparietal bone and laterally between the temporal muscles. The surface of the skull was thoroughly cleaned with saline, and the edges of the incision were secured to the skull with Vetbond. A custom titanium headpost was secured to the posterior of the nasal bone with trans-parent dental cement (Metabond, Parkell), and a thin layer of dental cement was applied to the entire dorsal surface of the skull. Next, alayer of cyanoacrylate (Maxi-Cure, Bob Smith Industries) was used to cover the skull and left to cure approximately 30 min at 22-24 °C room temperature to provide a smooth surface for transcranial imaging.
   virus: Pups were injected bilaterally with 2 μl of AAV9-hsyn-ACh3.0 (1.8 x 1013 gc / ml) and 2 μl of AAV9-hsyn-NES-jRCaMP1b (2.5 x 1013 gc / ml; Addgene) per hemisphere.
 Subject:

src/higley_lab_to_nwb/lohani_2022/lohani_2022_requirements.txt

@@ -1,5 +1,7 @@
-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
-ndx-facemap-motionsvd @ git+https://github.com/catalystneuro/ndx-facemap-motionsvd.git@main
+neo
+ndx-facemap-motionsvd@git+https://github.com/catalystneuro/ndx-facemap-motionsvd.git@main
+spikeinterface
+ndx-events@git+https://github.com/rly/ndx-events.git@main
+sonpy
+opencv-python

src/higley_lab_to_nwb/lohani_2022/lohani_2022nwbconverter.py

@@ -76,34 +76,6 @@ def get_metadata(self) -> DeepDict:
 
         return metadata
 
-    def run_conversion(  # until [Issue #908](https://github.com/catalystneuro/neuroconv/issues/908) is fixed
-        self,
-        nwbfile_path: str = None,
-        nwbfile: NWBFile = None,
-        metadata: Dict = None,
-        overwrite: bool = False,
-        conversion_options: Dict = None,
-    ) -> None:
-        if metadata is None:
-            metadata = self.get_metadata()
-
-        self.validate_metadata(metadata=metadata)
-
-        self.validate_conversion_options(conversion_options=conversion_options)
-
-        self.temporally_align_data_interfaces()
-
-        with make_or_load_nwbfile(
-            nwbfile_path=nwbfile_path,
-            nwbfile=nwbfile,
-            metadata=metadata,
-            overwrite=overwrite,
-            verbose=self.verbose,
-        ) as nwbfile_out:
-            self.add_to_nwbfile(nwbfile_out, metadata, conversion_options)
-
-        return
-
     def temporally_align_data_interfaces(self):
         ttlsignal_interface = self.data_interface_objects["Spike2Signals"]