Merge branch 'main' into deprecate_spikeglx_file_path

CHANGELOG.md

@@ -29,15 +29,16 @@
 ## Improvements
 * Use mixing tests for ecephy's mocks [PR #1136](https://github.com/catalystneuro/neuroconv/pull/1136)
 * Use pytest format for dandi tests to avoid window permission error on teardown [PR #1151](https://github.com/catalystneuro/neuroconv/pull/1151)
+* Added many docstrings for public functions [PR #1063](https://github.com/catalystneuro/neuroconv/pull/1063)
 
 # v0.6.5 (November 1, 2024)
 
-## Deprecations
-
 ## Bug Fixes
 * Fixed formatwise installation from pipy [PR #1118](https://github.com/catalystneuro/neuroconv/pull/1118)
 * Fixed dailies [PR #1113](https://github.com/catalystneuro/neuroconv/pull/1113)
 
+## Deprecations
+
 ## Features
 * Using in-house `GenericDataChunkIterator` [PR #1068](https://github.com/catalystneuro/neuroconv/pull/1068)
 * Data interfaces now perform source (argument inputs) validation with the json schema  [PR #1020](https://github.com/catalystneuro/neuroconv/pull/1020)

pyproject.toml

@@ -356,7 +356,7 @@ doctest_optionflags = "ELLIPSIS"
 
 [tool.black]
 line-length = 120
-target-version = ['py38', 'py39', 'py310']
+target-version = ['py39', 'py310']
 include = '\.pyi?$'
 extend-exclude = '''
 /(

src/neuroconv/basedatainterface.py

@@ -36,7 +36,14 @@ class BaseDataInterface(ABC):
 
     @classmethod
     def get_source_schema(cls) -> dict:
-        """Infer the JSON schema for the source_data from the method signature (annotation typing)."""
+        """
+        Infer the JSON schema for the source_data from the method signature (annotation typing).
+
+        Returns
+        -------
+        dict
+            The JSON schema for the source_data.
+        """
         return get_json_schema_from_method_signature(cls, exclude=["source_data"])
 
     @classmethod

src/neuroconv/datainterfaces/behavior/lightningpose/lightningposeconverter.py

@@ -111,6 +111,28 @@ def add_to_nwbfile(
         starting_frames_labeled_videos: Optional[list[int]] = None,
         stub_test: bool = False,
     ):
+        """
+        Add behavior and pose estimation data, including original and labeled videos, to the specified NWBFile.
+
+        Parameters
+        ----------
+        nwbfile : NWBFile
+            The NWBFile object to which the data will be added.
+        metadata : dict
+            Metadata dictionary containing information about the behavior and videos.
+        reference_frame : str, optional
+            Description of the reference frame for pose estimation, by default None.
+        confidence_definition : str, optional
+            Definition for the confidence levels in pose estimation, by default None.
+        external_mode : bool, optional
+            If True, the videos will be referenced externally rather than embedded within the NWB file, by default True.
+        starting_frames_original_videos : list of int, optional
+            List of starting frames for the original videos, by default None.
+        starting_frames_labeled_videos : list of int, optional
+            List of starting frames for the labeled videos, by default None.
+        stub_test : bool, optional
+            If True, only a subset of the data will be added for testing purposes, by default False.
+        """
         original_video_interface = self.data_interface_objects["OriginalVideo"]
 
         original_video_metadata = next(
@@ -172,6 +194,33 @@ def run_conversion(
         starting_frames_labeled_videos: Optional[list] = None,
         stub_test: bool = False,
     ) -> None:
+        """
+        Run the full conversion process, adding behavior, video, and pose estimation data to an NWB file.
+
+        Parameters
+        ----------
+        nwbfile_path : FilePath, optional
+            The file path where the NWB file will be saved. If None, the file is handled in memory.
+        nwbfile : NWBFile, optional
+            An in-memory NWBFile object. If None, a new NWBFile object will be created.
+        metadata : dict, optional
+            Metadata dictionary for describing the NWB file contents. If None, it is auto-generated.
+        overwrite : bool, optional
+            If True, overwrites the NWB file at `nwbfile_path` if it exists. If False, appends to the file, by default False.
+        reference_frame : str, optional
+            Description of the reference frame for pose estimation, by default None.
+        confidence_definition : str, optional
+            Definition for confidence levels in pose estimation, by default None.
+        external_mode : bool, optional
+            If True, the videos will be referenced externally rather than embedded within the NWB file, by default True.
+        starting_frames_original_videos : list of int, optional
+            List of starting frames for the original videos, by default None.
+        starting_frames_labeled_videos : list of int, optional
+            List of starting frames for the labeled videos, by default None.
+        stub_test : bool, optional
+            If True, only a subset of the data will be added for testing purposes, by default False.
+
+        """
         if metadata is None:
             metadata = self.get_metadata()
 

src/neuroconv/datainterfaces/behavior/medpc/medpcdatainterface.py

@@ -187,6 +187,7 @@ def add_to_nwbfile(
         nwbfile: NWBFile,
         metadata: dict,
     ) -> None:
+
         ndx_events = get_package(package_name="ndx_events", installation_instructions="pip install ndx-events")
         medpc_name_to_info_dict = metadata["MedPC"].get("medpc_name_to_info_dict", None)
         assert medpc_name_to_info_dict is not None, "medpc_name_to_info_dict must be provided in metadata"

src/neuroconv/datainterfaces/ecephys/basesortingextractorinterface.py

@@ -220,6 +220,19 @@ def set_aligned_segment_starting_times(self, aligned_segment_starting_times: lis
                 sorting_segment._t_start = aligned_segment_starting_time
 
     def subset_sorting(self):
+        """
+        Generate a subset of the sorting extractor based on spike timing data.
+
+        This method identifies the earliest spike time across all units in the sorting extractor and creates a
+        subset of the sorting data up to 110% of the earliest spike time. If the sorting extractor is associated
+        with a recording, the subset is further limited by the total number of samples in the recording.
+
+        Returns
+        -------
+        SortingExtractor
+            A new `SortingExtractor` object representing the subset of the original sorting data,
+            sliced from the start frame to the calculated end frame.
+        """
         max_min_spike_time = max(
             [
                 min(x)

src/neuroconv/datainterfaces/ecephys/cellexplorer/cellexplorerdatainterface.py

@@ -518,6 +518,33 @@ def __init__(self, file_path: FilePath, verbose: bool = True):
                 )
 
     def generate_recording_with_channel_metadata(self):
+        """
+        Generate a dummy recording extractor with channel metadata from session data.
+
+        This method reads session data from a `.session.mat` file (if available) and generates a dummy recording
+        extractor. The recording extractor is then populated with channel metadata extracted from the session file.
+
+        Returns
+        -------
+        NumpyRecording
+            A `NumpyRecording` object representing the dummy recording extractor, containing the channel metadata.
+
+        Notes
+        -----
+        - The method reads the `.session.mat` file using `pymatreader` and extracts `extracellular` data.
+        - It creates a dummy recording extractor using `spikeinterface.core.numpyextractors.NumpyRecording`.
+        - The generated extractor includes channel IDs and other relevant metadata such as number of channels,
+        number of samples, and sampling frequency.
+        - Channel metadata is added to the dummy extractor using the `add_channel_metadata_to_recoder` function.
+        - If the `.session.mat` file is not found, no extractor is returned.
+
+        Warnings
+        --------
+        Ensure that the `.session.mat` file is correctly located in the expected session path, or the method will not generate
+        a recording extractor. The expected session is self.session_path / f"{self.session_id}.session.mat"
+
+        """
+
         session_data_file_path = self.session_path / f"{self.session_id}.session.mat"
         if session_data_file_path.is_file():
             from pymatreader import read_mat

src/neuroconv/datainterfaces/ophys/baseimagingextractorinterface.py

@@ -47,6 +47,17 @@ def __init__(
     def get_metadata_schema(
         self,
     ) -> dict:
+        """
+        Retrieve the metadata schema for the optical physiology (Ophys) data, with optional handling of photon series type.
+
+        Parameters
+        ----------
+        photon_series_type : {"OnePhotonSeries", "TwoPhotonSeries"}, optional
+            The type of photon series to include in the schema. If None, the value from the instance is used.
+            This argument is deprecated and will be removed in a future version. Set `photon_series_type` during
+            the initialization of the `BaseImagingExtractorInterface` instance.
+
+        """
 
         metadata_schema = super().get_metadata_schema()
 
@@ -93,6 +104,16 @@ def get_metadata_schema(
     def get_metadata(
         self,
     ) -> DeepDict:
+        """
+        Retrieve the metadata for the imaging data, with optional handling of photon series type.
+
+        Parameters
+        ----------
+        photon_series_type : {"OnePhotonSeries", "TwoPhotonSeries"}, optional
+            The type of photon series to include in the metadata. If None, the value from the instance is used.
+            This argument is deprecated and will be removed in a future version. Instead, set `photon_series_type`
+            during the initialization of the `BaseImagingExtractorInterface` instance.
+        """
 
         from ...tools.roiextractors import get_nwb_imaging_metadata
 

src/neuroconv/datainterfaces/ophys/basesegmentationextractorinterface.py

@@ -24,6 +24,27 @@ def __init__(self, verbose: bool = False, **source_data):
         self.segmentation_extractor = self.get_extractor()(**source_data)
 
     def get_metadata_schema(self) -> dict:
+        """
+        Generate the metadata schema for Ophys data, updating required fields and properties.
+
+        This method builds upon the base schema and customizes it for Ophys-specific metadata, including required
+        components such as devices, fluorescence data, imaging planes, and two-photon series. It also applies
+        temporary schema adjustments to handle certain use cases until a centralized metadata schema definition
+        is available.
+
+        Returns
+        -------
+        dict
+            A dictionary representing the updated Ophys metadata schema.
+
+        Notes
+        -----
+        - Ensures that `Device` and `ImageSegmentation` are marked as required.
+        - Updates various properties, including ensuring arrays for `ImagingPlane` and `TwoPhotonSeries`.
+        - Adjusts the schema for `Fluorescence`, including required fields and pattern properties.
+        - Adds schema definitions for `DfOverF`, segmentation images, and summary images.
+        - Applies temporary fixes, such as setting additional properties for `ImageSegmentation` to True.
+        """
         metadata_schema = super().get_metadata_schema()
         metadata_schema["required"] = ["Ophys"]
         metadata_schema["properties"]["Ophys"] = get_base_schema()

src/neuroconv/datainterfaces/ophys/brukertiff/brukertiffconverter.py

@@ -31,6 +31,7 @@ def get_source_schema(cls):
         return source_schema
 
     def get_conversion_options_schema(self):
+        """get the conversion options schema."""
         interface_name = list(self.data_interface_objects.keys())[0]
         return self.data_interface_objects[interface_name].get_conversion_options_schema()
 
@@ -91,6 +92,20 @@ def add_to_nwbfile(
         stub_test: bool = False,
         stub_frames: int = 100,
     ):
+        """
+        Add data from multiple data interfaces to the specified NWBFile.
+
+        Parameters
+        ----------
+        nwbfile : NWBFile
+            The NWBFile object to which the data will be added.
+        metadata : dict
+            Metadata dictionary containing information to describe the data being added to the NWB file.
+        stub_test : bool, optional
+            If True, only a subset of the data (up to `stub_frames`) will be added for testing purposes. Default is False.
+        stub_frames : int, optional
+            The number of frames to include in the subset if `stub_test` is True. Default is 100.
+        """
         for photon_series_index, (interface_name, data_interface) in enumerate(self.data_interface_objects.items()):
             data_interface.add_to_nwbfile(
                 nwbfile=nwbfile,
@@ -109,6 +124,24 @@ def run_conversion(
         stub_test: bool = False,
         stub_frames: int = 100,
     ) -> None:
+        """
+        Run the conversion process for the instantiated data interfaces and add data to the NWB file.
+
+        Parameters
+        ----------
+        nwbfile_path : FilePath, optional
+            Path where the NWB file will be written. If None, the file will be handled in-memory.
+        nwbfile : NWBFile, optional
+            An in-memory NWBFile object. If None, a new NWBFile object will be created.
+        metadata : dict, optional
+            Metadata dictionary for describing the NWB file. If None, it will be auto-generated using the `get_metadata()` method.
+        overwrite : bool, optional
+            If True, overwrites the existing NWB file at `nwbfile_path`. If False, appends to the file (default is False).
+        stub_test : bool, optional
+            If True, only a subset of the data (up to `stub_frames`) will be added for testing purposes, by default False.
+        stub_frames : int, optional
+            The number of frames to include in the subset if `stub_test` is True, by default 100.
+        """
         if metadata is None:
             metadata = self.get_metadata()
 
@@ -141,6 +174,7 @@ def get_source_schema(cls):
         return get_json_schema_from_method_signature(cls)
 
     def get_conversion_options_schema(self):
+        """Get the conversion options schema."""
         interface_name = list(self.data_interface_objects.keys())[0]
         return self.data_interface_objects[interface_name].get_conversion_options_schema()
 
@@ -187,6 +221,21 @@ def add_to_nwbfile(
         stub_test: bool = False,
         stub_frames: int = 100,
     ):
+        """
+        Add data from all instantiated data interfaces to the provided NWBFile.
+
+        Parameters
+        ----------
+        nwbfile : NWBFile
+            The NWBFile object to which the data will be added.
+        metadata : dict
+            Metadata dictionary containing information about the data to be added.
+        stub_test : bool, optional
+            If True, only a subset of the data (defined by `stub_frames`) will be added for testing purposes,
+            by default False.
+        stub_frames : int, optional
+            The number of frames to include in the subset if `stub_test` is True, by default 100.
+        """
         for photon_series_index, (interface_name, data_interface) in enumerate(self.data_interface_objects.items()):
             data_interface.add_to_nwbfile(
                 nwbfile=nwbfile,
@@ -205,6 +254,24 @@ def run_conversion(
         stub_test: bool = False,
         stub_frames: int = 100,
     ) -> None:
+        """
+        Run the NWB conversion process for all instantiated data interfaces.
+
+        Parameters
+        ----------
+        nwbfile_path : FilePath, optional
+            The file path where the NWB file will be written. If None, the file is handled in-memory.
+        nwbfile : NWBFile, optional
+            An existing in-memory NWBFile object. If None, a new NWBFile object will be created.
+        metadata : dict, optional
+            Metadata dictionary used to create or validate the NWBFile. If None, metadata is automatically generated.
+        overwrite : bool, optional
+            If True, the NWBFile at `nwbfile_path` is overwritten if it exists. If False (default), data is appended.
+        stub_test : bool, optional
+            If True, only a subset of the data (up to `stub_frames`) is used for testing purposes. By default False.
+        stub_frames : int, optional
+            The number of frames to include in the subset if `stub_test` is True. By default 100.
+        """
         if metadata is None:
             metadata = self.get_metadata()