switched from local MultiPlaneIE to rebased VolumetricIE

src/roiextractors/extractors/tiffimagingextractors/scanimagetiffimagingextractor.py

@@ -12,6 +12,7 @@
 
 from ...extraction_tools import PathType, FloatType, ArrayType, DtypeType, get_package
 from ...imagingextractor import ImagingExtractor
+from ...volumetricimagingextractor import VolumetricImagingExtractor
 from .scanimagetiff_utils import (
     extract_extra_metadata,
     parse_metadata,
@@ -20,150 +21,7 @@
 )
 
 
-class MultiPlaneImagingExtractor(ImagingExtractor):
-    """Class to combine multiple ImagingExtractor objects by depth plane."""
-
-    extractor_name = "MultiPlaneImaging"
-    installed = True
-    installatiuon_mesage = ""
-
-    def __init__(self, imaging_extractors: List[ImagingExtractor]):
-        """Initialize a MultiPlaneImagingExtractor object from a list of ImagingExtractors.
-
-        Parameters
-        ----------
-        imaging_extractors: list of ImagingExtractor
-            list of imaging extractor objects
-        """
-        super().__init__()
-        assert isinstance(imaging_extractors, list), "Enter a list of ImagingExtractor objects as argument"
-        assert all(isinstance(imaging_extractor, ImagingExtractor) for imaging_extractor in imaging_extractors)
-        self._check_consistency_between_imaging_extractors(imaging_extractors)
-        self._imaging_extractors = imaging_extractors
-        self._num_planes = len(imaging_extractors)
-
-    # TODO: Add consistency check for channel_names when API is standardized
-    def _check_consistency_between_imaging_extractors(self, imaging_extractors: List[ImagingExtractor]):
-        """Check that essential properties are consistent between extractors so that they can be combined appropriately.
-
-        Parameters
-        ----------
-        imaging_extractors: list of ImagingExtractor
-            list of imaging extractor objects
-
-        Raises
-        ------
-        AssertionError
-            If any of the properties are not consistent between extractors.
-
-        Notes
-        -----
-        This method checks the following properties:
-            - sampling frequency
-            - image size
-            - number of channels
-            - channel names
-            - data type
-            - num_frames
-        """
-        properties_to_check = dict(
-            get_sampling_frequency="The sampling frequency",
-            get_image_size="The size of a frame",
-            get_num_channels="The number of channels",
-            get_dtype="The data type",
-            get_num_frames="The number of frames",
-        )
-        for method, property_message in properties_to_check.items():
-            values = [getattr(extractor, method)() for extractor in imaging_extractors]
-            unique_values = set(tuple(v) if isinstance(v, Iterable) else v for v in values)
-            assert (
-                len(unique_values) == 1
-            ), f"{property_message} is not consistent over the files (found {unique_values})."
-
-    def get_video(self, start_frame: Optional[int] = None, end_frame: Optional[int] = None) -> np.ndarray:
-        """Get the video frames.
-
-        Parameters
-        ----------
-        start_frame: int, optional
-            Start frame index (inclusive).
-        end_frame: int, optional
-            End frame index (exclusive).
-
-        Returns
-        -------
-        video: numpy.ndarray
-            The 3D video frames (num_rows, num_columns, num_planes).
-        """
-        start_frame = start_frame if start_frame is not None else 0
-        end_frame = end_frame if end_frame is not None else self.get_num_frames()
-
-        video = np.zeros((end_frame - start_frame, *self.get_image_size()), self.get_dtype())
-        for i, imaging_extractor in enumerate(self._imaging_extractors):
-            video[..., i] = imaging_extractor.get_video(start_frame, end_frame)
-        return video
-
-    def get_frames(self, frame_idxs: ArrayType) -> np.ndarray:
-        """Get specific video frames from indices (not necessarily continuous).
-
-        Parameters
-        ----------
-        frame_idxs: array-like
-            Indices of frames to return.
-
-        Returns
-        -------
-        frames: numpy.ndarray
-            The 3D video frames (num_rows, num_columns, num_planes).
-        """
-        if isinstance(frame_idxs, int):
-            frame_idxs = [frame_idxs]
-
-        if not all(np.diff(frame_idxs) == 1):
-            frames = np.zeros((len(frame_idxs), *self.get_image_size()), self.get_dtype())
-            for i, imaging_extractor in enumerate(self._imaging_extractors):
-                frames[..., i] = imaging_extractor.get_frames(frame_idxs)
-        else:
-            return self.get_video(start_frame=frame_idxs[0], end_frame=frame_idxs[-1] + 1)
-
-    def get_image_size(self) -> Tuple:
-        """Get the size of a single frame.
-
-        Returns
-        -------
-        image_size: tuple
-            The size of a single frame (num_rows, num_columns, num_planes).
-        """
-        image_size = (*self._imaging_extractors[0].get_image_size(), self.get_num_planes())
-        return image_size
-
-    def get_num_planes(self) -> int:
-        """Get the number of depth planes.
-
-        Returns
-        -------
-        _num_planes: int
-            The number of depth planes.
-        """
-        return self._num_planes
-
-    def get_num_frames(self) -> int:
-        return self._imaging_extractors[0].get_num_frames()
-
-    def get_sampling_frequency(self) -> float:
-        return self._imaging_extractors[0].get_sampling_frequency()
-
-    def get_channel_names(self) -> list:
-        return self._imaging_extractors[0].get_channel_names()
-
-    def get_num_channels(self) -> int:
-        return self._imaging_extractors[0].get_num_channels()
-
-    def get_dtype(self) -> DtypeType:
-        return self._imaging_extractors[0].get_dtype()
-
-
-class ScanImageTiffMultiPlaneImagingExtractor(MultiPlaneImagingExtractor):
+class ScanImageTiffMultiPlaneImagingExtractor(VolumetricImagingExtractor):
     """Specialized extractor for reading multi-plane (volumetric) TIFF files produced via ScanImage."""
 
     extractor_name = "ScanImageTiffMultiPlaneImaging"