Source code for neuroconv.datainterfaces.ecephys.phy.phydatainterface

from pydantic import DirectoryPath, validate_call

from ..basesortingextractorinterface import BaseSortingExtractorInterface
from ....utils import DeepDict


[docs] class PhySortingInterface(BaseSortingExtractorInterface): """ Primary data interface class for converting Phy data. Uses :py:func:`~spikeinterface.extractors.read_phy` from SpikeInterface. """ display_name = "Phy Sorting" associated_suffixes = (".npy",) info = "Interface for Phy sorting data."
[docs] @classmethod def get_source_schema(cls) -> dict: source_schema = super().get_source_schema() source_schema["properties"]["exclude_cluster_groups"]["items"] = dict(type="string") source_schema["properties"]["folder_path"][ "description" ] = "Path to the output Phy folder (containing the params.py)." return source_schema
[docs] @classmethod def get_extractor_class(cls): from spikeinterface.extractors.extractor_classes import read_phy return read_phy
@validate_call def __init__( self, folder_path: DirectoryPath, exclude_cluster_groups: list[str] | None = None, verbose: bool = False, ): """ Initialize a PhySortingInterface. Parameters ---------- folder_path : str or Path Path to the output Phy folder (containing the params.py). exclude_cluster_groups : str or list of str, optional Cluster groups to exclude (e.g. "noise" or ["noise", "mua"]). verbose : bool, default: False """ super().__init__(folder_path=folder_path, exclude_cluster_groups=exclude_cluster_groups, verbose=verbose)
[docs] def get_metadata(self) -> DeepDict: metadata = super().get_metadata() # See Kilosort save_to_phy() docstring for more info on these fields: https://github.com/MouseLand/Kilosort/blob/main/kilosort/io.py # Or see phy documentation: https://github.com/cortex-lab/phy/blob/master/phy/apps/base.py metadata["Ecephys"]["UnitProperties"] = [ dict(name="n_spikes", description="Number of spikes recorded from each unit."), dict(name="fr", description="Average firing rate of each unit."), dict(name="depth", description="Estimated depth of each unit in micrometers."), dict(name="Amplitude", description="Per-template amplitudes, computed as the L2 norm of the template."), dict( name="ContamPct", description="Contamination rate for each template, computed as fraction of refractory period violations relative to expectation based on a Poisson process.", ), dict( name="KSLabel", description="Label indicating whether each template is 'mua' (multi-unit activity) or 'good' (refractory).", ), dict(name="original_cluster_id", description="Original cluster ID assigned by Kilosort."), dict( name="amp", description="For every template, the maximum amplitude of the template waveforms across all channels.", ), dict(name="ch", description="The channel label of the best channel, as defined by the user."), dict(name="sh", description="The shank label of the best channel."), ] return metadata