Source code for neuroconv.datainterfaces.ophys.brukertiff.brukertiffconverter

from typing import Literal, Optional

from pynwb import NWBFile

from ... import (
    BrukerTiffMultiPlaneImagingInterface,
    BrukerTiffSinglePlaneImagingInterface,
)
from ....nwbconverter import NWBConverter
from ....tools.nwb_helpers import make_or_load_nwbfile
from ....utils import FolderPathType, get_schema_from_method_signature


[docs]class BrukerTiffMultiPlaneConverter(NWBConverter):
[docs] @classmethod def get_source_schema(cls): return get_schema_from_method_signature(cls)
[docs] def get_conversion_options_schema(self): interface_name = list(self.data_interface_objects.keys())[0] return self.data_interface_objects[interface_name].get_conversion_options_schema()
def __init__( self, folder_path: FolderPathType, plane_separation_type: Literal["disjoint", "contiguous"] = None, verbose: bool = False, ): """ Initializes the data interfaces for Bruker volumetric imaging data stream. Parameters ---------- folder_path : PathType The path to the folder that contains the Bruker TIF image files (.ome.tif) and configuration files (.xml, .env). plane_separation_type: {'contiguous', 'disjoint'} Defines how to write volumetric imaging data. Use 'contiguous' to create the volumetric two photon series, and 'disjoint' to create separate imaging plane and two photon series for each plane. verbose : bool, default: True Controls verbosity. """ self.verbose = verbose self.data_interface_objects = dict() if plane_separation_type is None or plane_separation_type not in ["disjoint", "contiguous"]: raise ValueError( "For volumetric imaging data the plane separation method must be one of 'disjoint' or 'contiguous'." ) streams = BrukerTiffMultiPlaneImagingInterface.get_streams( folder_path=folder_path, plane_separation_type=plane_separation_type, ) channel_streams = streams["channel_streams"] interface_name = "BrukerImaging" for channel_stream_name in channel_streams: plane_streams = streams["plane_streams"][channel_stream_name] for plane_stream in plane_streams: if len(plane_streams) > 1: interface_name += plane_stream.replace("_", "") if plane_separation_type == "contiguous": self.data_interface_objects[interface_name] = BrukerTiffMultiPlaneImagingInterface( folder_path=folder_path, stream_name=plane_stream, ) elif plane_separation_type == "disjoint": self.data_interface_objects[interface_name] = BrukerTiffSinglePlaneImagingInterface( folder_path=folder_path, stream_name=plane_stream, ) def add_to_nwbfile( self, nwbfile: NWBFile, metadata, stub_test: bool = False, stub_frames: int = 100, ): for photon_series_index, (interface_name, data_interface) in enumerate(self.data_interface_objects.items()): data_interface.add_to_nwbfile( nwbfile=nwbfile, metadata=metadata, photon_series_index=photon_series_index, stub_test=stub_test, stub_frames=stub_frames, )
[docs] def run_conversion( self, nwbfile_path: Optional[str] = None, nwbfile: Optional[NWBFile] = None, metadata: Optional[dict] = None, overwrite: bool = False, stub_test: bool = False, stub_frames: int = 100, ) -> None: if metadata is None: metadata = self.get_metadata() self.validate_metadata(metadata=metadata) 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=nwbfile_out, metadata=metadata, stub_test=stub_test, stub_frames=stub_frames)
[docs]class BrukerTiffSinglePlaneConverter(NWBConverter):
[docs] @classmethod def get_source_schema(cls): return get_schema_from_method_signature(cls)
[docs] def get_conversion_options_schema(self): interface_name = list(self.data_interface_objects.keys())[0] return self.data_interface_objects[interface_name].get_conversion_options_schema()
def __init__( self, folder_path: FolderPathType, verbose: bool = False, ): """ Initializes the data interfaces for Bruker imaging data stream. Parameters ---------- folder_path : PathType The path to the folder that contains the Bruker TIF image files (.ome.tif) and configuration files (.xml, .env). verbose : bool, default: True Controls verbosity. """ from roiextractors.extractors.tiffimagingextractors.brukertiffimagingextractor import ( _determine_imaging_is_volumetric, ) if _determine_imaging_is_volumetric(folder_path=folder_path): raise ValueError("For volumetric imaging data use BrukerTiffMultiPlaneConverter.") self.verbose = verbose self.data_interface_objects = dict() streams = BrukerTiffSinglePlaneImagingInterface.get_streams(folder_path=folder_path) channel_streams = streams["channel_streams"] interface_name = "BrukerImaging" for channel_stream_name in channel_streams: if len(channel_streams) > 1: interface_name += channel_stream_name.replace("_", "") self.data_interface_objects[interface_name] = BrukerTiffSinglePlaneImagingInterface( folder_path=folder_path, stream_name=channel_stream_name, ) def add_to_nwbfile( self, nwbfile: NWBFile, metadata, stub_test: bool = False, stub_frames: int = 100, ): for photon_series_index, (interface_name, data_interface) in enumerate(self.data_interface_objects.items()): data_interface.add_to_nwbfile( nwbfile=nwbfile, metadata=metadata, photon_series_index=photon_series_index, stub_test=stub_test, stub_frames=stub_frames, )
[docs] def run_conversion( self, nwbfile_path: Optional[str] = None, nwbfile: Optional[NWBFile] = None, metadata: Optional[dict] = None, overwrite: bool = False, stub_test: bool = False, stub_frames: int = 100, ) -> None: if metadata is None: metadata = self.get_metadata() self.validate_metadata(metadata=metadata) 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=nwbfile_out, metadata=metadata, stub_test=stub_test, stub_frames=stub_frames)