Merge branch 'main' into spike2

CHANGELOG.md

@@ -2,7 +2,9 @@
 
 ### Back-compatibility break
 * `ExtractorInterface` classes now access their extractor with the classmethod `cls.get_extractor()` instead of the attribute `self.Extractor`. [PR #324](https://github.com/catalystneuro/neuroconv/pull/324)
-* The `spikeextractor_backend` option was removed for several `RecordingExtractorInterface` classes. [PR #324](https://github.com/catalystneuro/neuroconv/pull/324)
+* The `spikeextractor_backend` option was removed for all `RecordingExtractorInterface` classes. ([PR #324](https://github.com/catalystneuro/neuroconv/pull/324), [PR #309](https://github.com/catalystneuro/neuroconv/pull/309)]
+* The `NeuroScopeMultiRecordingExtractor` has been removed. If your conversion required this, please submit an issue requesting instructions for how to implement it. [PR #309](https://github.com/catalystneuro/neuroconv/pull/309)
+* The `SIPickle` interfaces have been removed. [PR #309](https://github.com/catalystneuro/neuroconv/pull/309)
 * The previous conversion option `es_key` has been moved to the `__init__` of all `BaseRecordingExtractorInterface` classes. It is no longer possible to use this argument in the `run_conversion` method. [PR #318](https://github.com/catalystneuro/neuroconv/pull/318)
 
 ### Features

src/neuroconv/datainterfaces/__init__.py

@@ -2,16 +2,11 @@
 from .ecephys.neuroscope.neuroscopedatainterface import (
     NeuroScopeRecordingInterface,
     NeuroScopeLFPInterface,
-    NeuroScopeMultiRecordingTimeInterface,
     NeuroScopeSortingInterface,
 )
 from .ecephys.spikeglx.spikeglxdatainterface import SpikeGLXRecordingInterface, SpikeGLXLFPInterface
 from .ecephys.spikeglx.spikeglxnidqinterface import SpikeGLXNIDQInterface
 from .ecephys.spikegadgets.spikegadgetsdatainterface import SpikeGadgetsRecordingInterface
-from .ecephys.spikeinterface.sipickledatainterfaces import (
-    SIPickleRecordingInterface,
-    SIPickleSortingInterface,
-)
 from .ecephys.intan.intandatainterface import IntanRecordingInterface
 from .ecephys.spike2.spike2datainterface import Spike2RecordingInterface
 from .ecephys.spike2.spike2datainterface import CEDRecordingInterface
@@ -70,16 +65,13 @@
     NeuralynxRecordingInterface,
     NeuralynxSortingInterface,
     NeuroScopeRecordingInterface,
-    NeuroScopeMultiRecordingTimeInterface,
     NeuroScopeSortingInterface,
     NeuroScopeLFPInterface,
     Spike2RecordingInterface,
     SpikeGLXRecordingInterface,
     SpikeGLXLFPInterface,
     SpikeGLXNIDQInterface,
     SpikeGadgetsRecordingInterface,
-    SIPickleRecordingInterface,
-    SIPickleSortingInterface,
     IntanRecordingInterface,
     CEDRecordingInterface,
     CellExplorerSortingInterface,

src/neuroconv/datainterfaces/ecephys/axona/axonadatainterface.py

@@ -10,8 +10,9 @@
 
 
 class AxonaRecordingInterface(BaseRecordingExtractorInterface):
-    """Primary data interface class for converting a Axona data using a
-    :py:class:`~spikeinterface.extractors.AxonaRecordingExtractor`."""
+    """
+    DataInterface for converting raw Axona data using a :py:class:`~spikeinterface.extractors.AxonaRecordingExtractor`.
+    """
 
     def __init__(self, file_path: FilePathType, verbose: bool = True, es_key: str = "ElectricalSeries"):
         """

src/neuroconv/datainterfaces/ecephys/baserecordingextractorinterface.py

@@ -111,22 +111,14 @@ def subset_recording(self, stub_test: bool = False):
         ----------
         stub_test : bool, default: False
         """
-        from spikeextractors import RecordingExtractor, SubRecordingExtractor
-        from spikeinterface import BaseRecording
-
         kwargs = dict()
         if stub_test:
             num_frames = 100
             end_frame = min([num_frames, self.recording_extractor.get_num_frames()])
             kwargs.update(end_frame=end_frame)
         if self.subset_channels is not None:
             kwargs.update(channel_ids=self.subset_channels)
-        if isinstance(self.recording_extractor, RecordingExtractor):
-            recording_extractor = SubRecordingExtractor(self.recording_extractor, **kwargs)
-        elif isinstance(self.recording_extractor, BaseRecording):
-            recording_extractor = self.recording_extractor.frame_slice(start_frame=0, end_frame=end_frame)
-        else:
-            raise TypeError(f"{self.recording_extractor} should be either se.RecordingExtractor or si.BaseRecording")
+        recording_extractor = self.recording_extractor.frame_slice(start_frame=0, end_frame=end_frame)
         return recording_extractor
 
     def run_conversion(

src/neuroconv/datainterfaces/ecephys/basesortingextractorinterface.py

@@ -81,9 +81,6 @@ def align_timestamps(self, synchronized_timestamps: np.ndarray):
         self.sorting_extractor.set_times(times=synchronized_timestamps)
 
     def subset_sorting(self):
-        from spikeextractors import SortingExtractor, SubSortingExtractor
-        from spikeinterface import BaseSorting
-
         max_min_spike_time = max(
             [
                 min(x)
@@ -93,17 +90,7 @@ def subset_sorting(self):
             ]
         )
         end_frame = 1.1 * max_min_spike_time
-        if isinstance(self.sorting_extractor, SortingExtractor):
-            stub_sorting_extractor = SubSortingExtractor(
-                self.sorting_extractor,
-                unit_ids=self.sorting_extractor.get_unit_ids(),
-                start_frame=0,
-                end_frame=end_frame,
-            )
-        elif isinstance(self.sorting_extractor, BaseSorting):
-            stub_sorting_extractor = self.sorting_extractor.frame_slice(start_frame=0, end_frame=end_frame)
-        else:
-            raise TypeError(f"{self.sorting_extractor} should be either se.SortingExtractor or si.BaseSorting")
+        stub_sorting_extractor = self.sorting_extractor.frame_slice(start_frame=0, end_frame=end_frame)
         return stub_sorting_extractor
 
     def run_conversion(

src/neuroconv/datainterfaces/ecephys/neuroscope/neuroscopedatainterface.py

@@ -127,65 +127,6 @@ def get_metadata(self):
         return metadata
 
 
-class NeuroScopeMultiRecordingTimeInterface(NeuroScopeRecordingInterface):
-    """Primary data interface class for converting a NeuroscopeMultiRecordingTimeExtractor."""
-
-    RXModule = "spikeextractors"
-    RXName = "NeuroscopeMultiRecordingTimeExtractor"
-
-    def __init__(
-        self,
-        folder_path: FolderPathType,
-        gain: Optional[float] = None,
-        xml_file_path: OptionalFilePathType = None,
-    ):
-        """
-        Load and prepare raw acquisition data and corresponding metadata from the Neuroscope format (.dat files).
-
-        For all the .dat files in the folder_path, this concatenates them in time assuming no gaps in between.
-        If there are gaps, timestamps inside the RecordingExtractor should be overridden.
-
-        Parameters
-        ----------
-        folder_path : FolderPathType
-            Path to folder of multiple .dat files.
-        gain : Optional[float], optional
-            Conversion factors from int16 to Volts are not contained in xml_file_path; set them explicitly here.
-            Most common value is 0.195 for an intan recording system.
-            The default is None.
-        xml_file_path : OptionalFilePathType, optional
-            Path to .xml file containing device and electrode configuration.
-            If unspecified, it will be automatically set as the only .xml file in the same folder as the .dat file.
-            The default is None.
-        """
-        # TODO: Remove this sub interface
-        warn(
-            message=(
-                "Interfaces using a spikeextractors backend will soon be deprecated! "
-                "Please use the SpikeInterface backend with multiple segments instead."
-            ),
-            category=DeprecationWarning,
-            stacklevel=2,
-        )
-
-        get_package(package_name="lxml")
-        from spikeinterface.core.old_api_utils import OldToNewRecording
-
-        if xml_file_path is None:
-            xml_file_path = get_xml_file_path(data_file_path=folder_path)
-        super(NeuroScopeRecordingInterface, self).__init__(
-            folder_path=folder_path,
-            gain=gain,
-            xml_file_path=xml_file_path,
-        )
-        self.recording_extractor = OldToNewRecording(oldapi_recording_extractor=self.recording_extractor)
-
-        self.recording_extractor = subset_shank_channels(
-            recording_extractor=self.recording_extractor, xml_file_path=xml_file_path
-        )
-        add_recording_extractor_properties(recording_extractor=self.recording_extractor, xml_file_path=xml_file_path)
-
-
 class NeuroScopeLFPInterface(BaseLFPExtractorInterface):
     """Primary data interface class for converting Neuroscope LFP data."""
 
@@ -196,7 +137,6 @@ def __init__(
         file_path: FilePathType,
         gain: Optional[float] = None,
         xml_file_path: OptionalFilePathType = None,
-        spikeextractors_backend: bool = False,
     ):
         """
         Load and prepare lfp data and corresponding metadata from the Neuroscope format (.eeg or .lfp files).
@@ -213,35 +153,14 @@ def __init__(
             Path to .xml file containing device and electrode configuration.
             If unspecified, it will be automatically set as the only .xml file in the same folder as the .dat file.
             The default is None.
-        spikeextractors_backend : bool
-            False by default. When True the interface uses the old extractor from the spikextractors library instead
-            of a new spikeinterface object.
         """
         get_package(package_name="lxml")
 
         if xml_file_path is None:
             xml_file_path = get_xml_file_path(data_file_path=file_path)
 
-        if spikeextractors_backend:
-            # TODO: Remove spikeextractors backend
-            warn(
-                message=(
-                    "Interfaces using a spikeextractors backend will soon be deprecated! "
-                    "Please use the SpikeInterface backend instead."
-                ),
-                category=DeprecationWarning,
-                stacklevel=2,
-            )
-
-            from spikeextractors import NeuroscopeRecordingExtractor
-            from spikeinterface.core.old_api_utils import OldToNewRecording
-
-            self.Extractor = NeuroscopeRecordingExtractor
-            super().__init__(file_path=file_path, xml_file_path=xml_file_path)
-            self.recording_extractor = OldToNewRecording(oldapi_recording_extractor=self.recording_extractor)
-        else:
-            super().__init__(file_path=file_path)
-            self.source_data["xml_file_path"] = xml_file_path
+        super().__init__(file_path=file_path)
+        self.source_data["xml_file_path"] = xml_file_path
 
         add_recording_extractor_properties(
             recording_extractor=self.recording_extractor, xml_file_path=xml_file_path, gain=gain
@@ -269,12 +188,6 @@ def __init__(
         exclude_shanks: Optional[list] = None,
         xml_file_path: OptionalFilePathType = None,
         verbose: bool = True,
-        spikeextractors_backend: bool = False,
-        # TODO: we can enable this once
-        #     a) waveforms on unit columns support conversion factor in NWB
-        #     b) write_sorting utils support writing said waveforms properly to a units table
-        # load_waveforms: bool = False,
-        # gain: Optional[float] = None,
     ):
         """
         Load and prepare spike sorted data and corresponding metadata from the Neuroscope format (.res/.clu files).
@@ -293,47 +206,15 @@ def __init__(
             Path to .xml file containing device and electrode configuration.
             If unspecified, it will be automatically set as the only .xml file in the same folder as the .dat file.
             The default is None.
-        load_waveforms : bool, optional
-            If True, extracts waveform data from .spk.%i files in the path corresponding to
-            the .res.%i and .clue.%i files and sets these as unit spike features.
-            The default is False.
-            Not currently in use pending updates to NWB waveforms.
-        gain : float, optional
-            If loading waveforms, this value converts the data type of the waveforms to units of microvolts.
-            Conversion factors from int16 to Volts are not contained in xml_file_path; set them explicitly here.
-            Most common value is 0.195 for an intan recording system.
-            The default is None.
-            Not currently in use pending updates to NWB waveforms.
-        spikeextractors_backend : bool
-            False by default. When True the interface uses the old extractor from the spikextractors library instead
-            of a new spikeinterface object.
         """
         get_package(package_name="lxml")
-        from spikeextractors import NeuroscopeMultiSortingExtractor
-
-        if spikeextractors_backend:
-            # TODO: Remove spikeextractors backend
-            warn(
-                message=(
-                    "Interfaces using a spikeextractors backend will soon be deprecated! "
-                    "Please use the SpikeInterface backend instead."
-                ),
-                category=DeprecationWarning,
-                stacklevel=2,
-            )
-            self.Extractor = NeuroscopeMultiSortingExtractor
 
         super().__init__(
             folder_path=folder_path,
             keep_mua_units=keep_mua_units,
             exclude_shanks=exclude_shanks,
             xml_file_path=xml_file_path,
             verbose=verbose,
-            # TODO: we can enable this once
-            #     a) waveforms on unit columns support conversion factor in NWB
-            #     b) write_sorting utils support writing said waveforms properly to a units table
-            # load_waveforms=load_waveforms,
-            # gain=gain,
         )
 
     def get_metadata(self):

src/neuroconv/datainterfaces/ecephys/phy/phydatainterface.py

@@ -15,7 +15,6 @@ def __init__(
         folder_path: FolderPathType,
         exclude_cluster_groups: Optional[list] = None,
         verbose: bool = True,
-        spikeextractors_backend: bool = False,
     ):
         """
         Initialize a PhySortingInterface.
@@ -27,19 +26,5 @@ def __init__(
         exclude_cluster_groups : str or list of str, optional
             Cluster groups to exclude (e.g. "noise" or ["noise", "mua"]).
         verbose : bool, default: True
-        spikeextractors_backend : bool, default: False
         """
-        if spikeextractors_backend:
-            # TODO: Remove spikeextractors backend
-            warn(
-                message=(
-                    "Interfaces using a spikeextractors backend will soon be deprecated! "
-                    "Please use the SpikeInterface backend instead."
-                ),
-                category=DeprecationWarning,
-                stacklevel=2,
-            )
-            from spikeextractors import PhySortingExtractor
-
-            self.Extractor = PhySortingExtractor
         super().__init__(folder_path=folder_path, exclude_cluster_groups=exclude_cluster_groups, verbose=verbose)

src/neuroconv/datainterfaces/ecephys/requirements.txt

@@ -1,3 +1,2 @@
 spikeinterface>=0.97.0
-spikeextractors>=0.9.10
 packaging<22.0

src/neuroconv/datainterfaces/ecephys/spike2/spike2datainterface.py

@@ -33,8 +33,7 @@ def get_source_schema(cls):
     def get_all_channels_info(cls, file_path: FilePathType):
         """Retrieve and inspect necessary channel information prior to initialization."""
         _test_sonpy_installation()
-        getattr(cls, "RX")  # Required to trigger dynamic access in case this method is called first
-        return cls.RX.get_all_channels_info(file_path=file_path)
+        return cls.get_extractor().get_all_channels_info(file_path=file_path)
 
     def __init__(self, file_path: FilePathType, verbose: bool = True, es_key: str = "ElectricalSeries"):
         """

src/neuroconv/datainterfaces/ecephys/spikegadgets/spikegadgetsdatainterface.py

@@ -36,7 +36,6 @@ def __init__(
             or an array of values for each channel.
         es_key : str, default: "ElectricalSeries"
         """
-
         super().__init__(file_path=file_path, stream_id="trodes", verbose=verbose, es_key=es_key)
 
         self.source_data = dict(file_path=file_path, verbose=verbose)