Add Base extractor

src/roiextractors/baseextractor.py

@@ -0,0 +1,116 @@
+from abc import ABC, abstractmethod
+from typing import Union, Tuple
+from copy import deepcopy
+import numpy as np
+from .extraction_tools import ArrayType, FloatType
+
+
+class BaseExtractor(ABC):
+
+    def __init__(self):
+        self._times = None
+
+    @abstractmethod
+    def get_image_size(self) -> Tuple[int, int]:
+        """Get the size of each image in the recording (num_rows, num_columns).
+
+        Returns
+        -------
+        image_size: tuple
+            Size of each image (num_rows, num_columns).
+        """
+        pass
+
+    @abstractmethod
+    def get_num_frames(self) -> int:
+        """Get the number of frames in the recording.
+
+        Returns
+        -------
+        num_frames: int
+            Number of frames in the recording.
+        """
+        pass
+
+    @abstractmethod
+    def get_sampling_frequency(self) -> float:
+        """Get the sampling frequency of the recording in Hz.
+
+        Returns
+        -------
+        sampling_frequency: float
+            Sampling frequency of the recording in Hz.
+        """
+        pass
+
+    def frame_to_time(self, frames: ArrayType) -> Union[FloatType, np.ndarray]:
+        """Convert user-inputted frame indices to times with units of seconds.
+
+        Parameters
+        ----------
+        frames: array-like
+            The frame or frames to be converted to times.
+
+        Returns
+        -------
+        times: float or array-like
+            The corresponding times in seconds.
+        """
+        # Default implementation
+        frames = np.asarray(frames)
+        if self._times is None:
+            return frames / self.get_sampling_frequency()
+        else:
+            return self._times[frames]
+
+    def time_to_frame(self, times: ArrayType) -> Union[FloatType, np.ndarray]:
+        """Convert a user-inputted times (in seconds) to a frame indices.
+
+        Parameters
+        ----------
+        times: array-like
+            The times (in seconds) to be converted to frame indices.
+
+        Returns
+        -------
+        frames: float or array-like
+            The corresponding frame indices.
+        """
+        # Default implementation
+        times = np.asarray(times)
+        if self._times is None:
+            return np.round(times * self.get_sampling_frequency()).astype("int64")
+        else:
+            return np.searchsorted(self._times, times).astype("int64")
+
+    def set_times(self, times: ArrayType) -> None:
+        """Set the recording times (in seconds) for each frame.
+
+        Parameters
+        ----------
+        times: array-like
+            The times in seconds for each frame
+        """
+        assert len(times) == self.get_num_frames(), "'times' should have the same length of the number of frames!"
+        self._times = np.array(times).astype("float64")
+
+    def has_time_vector(self) -> bool:
+        """Detect if the ImagingExtractor has a time vector set or not.
+
+        Returns
+        -------
+        has_times: bool
+            True if the ImagingExtractor has a time vector set, otherwise False.
+        """
+        return self._times is not None
+
+    def copy_times(self, extractor) -> None:
+        """Copy times from another extractor.
+
+        Parameters
+        ----------
+        extractor
+            The extractor from which the times will be copied.
+        """
+        if extractor._times is not None:
+            self.set_times(deepcopy(extractor._times))

src/roiextractors/imagingextractor.py

@@ -8,57 +8,19 @@
     Class to get a lazy frame slice.
 """
 
-from abc import ABC, abstractmethod
+from abc import abstractmethod
 from typing import Union, Optional, Tuple, get_args
 from copy import deepcopy
 
 import numpy as np
 
+from .baseextractor import BaseExtractor
 from .extraction_tools import ArrayType, PathType, DtypeType, FloatType, IntType
 
 
-class ImagingExtractor(ABC):
+class ImagingExtractor(BaseExtractor):
     """Abstract class that contains all the meta-data and input data from the imaging data."""
 
-    def __init__(self, *args, **kwargs) -> None:
-        """Initialize the ImagingExtractor object."""
-        self._args = args
-        self._kwargs = kwargs
-        self._times = None
-
-    @abstractmethod
-    def get_image_size(self) -> Tuple[int, int]:
-        """Get the size of the video (num_rows, num_columns).
-
-        Returns
-        -------
-        image_size: tuple
-            Size of the video (num_rows, num_columns).
-        """
-        pass
-
-    @abstractmethod
-    def get_num_frames(self) -> int:
-        """Get the number of frames in the video.
-
-        Returns
-        -------
-        num_frames: int
-            Number of frames in the video.
-        """
-        pass
-
-    @abstractmethod
-    def get_sampling_frequency(self) -> float:
-        """Get the sampling frequency in Hz.
-
-        Returns
-        -------
-        sampling_frequency: float
-            Sampling frequency in Hz.
-        """
-        pass
-
     @abstractmethod
     def get_dtype(self) -> DtypeType:
         """Get the data type of the video.
@@ -175,78 +137,6 @@ def _validate_get_frames_arguments(self, frame_idxs: ArrayType) -> Tuple[int, in
 
         return start_frame, end_frame
 
-    def frame_to_time(self, frames: ArrayType) -> Union[FloatType, np.ndarray]:
-        """Convert user-inputted frame indices to times with units of seconds.
-
-        Parameters
-        ----------
-        frames: array-like
-            The frame or frames to be converted to times.
-
-        Returns
-        -------
-        times: float or array-like
-            The corresponding times in seconds.
-        """
-        # Default implementation
-        frames = np.asarray(frames)
-        if self._times is None:
-            return frames / self.get_sampling_frequency()
-        else:
-            return self._times[frames]
-
-    def time_to_frame(self, times: ArrayType) -> Union[FloatType, np.ndarray]:
-        """Convert a user-inputted times (in seconds) to a frame indices.
-
-        Parameters
-        ----------
-        times: array-like
-            The times (in seconds) to be converted to frame indices.
-
-        Returns
-        -------
-        frames: float or array-like
-            The corresponding frame indices.
-        """
-        # Default implementation
-        times = np.asarray(times)
-        if self._times is None:
-            return np.round(times * self.get_sampling_frequency()).astype("int64")
-        else:
-            return np.searchsorted(self._times, times).astype("int64")
-
-    def set_times(self, times: ArrayType) -> None:
-        """Set the recording times (in seconds) for each frame.
-
-        Parameters
-        ----------
-        times: array-like
-            The times in seconds for each frame
-        """
-        assert len(times) == self.get_num_frames(), "'times' should have the same length of the number of frames!"
-        self._times = np.array(times).astype("float64")
-
-    def has_time_vector(self) -> bool:
-        """Detect if the ImagingExtractor has a time vector set or not.
-
-        Returns
-        -------
-        has_times: bool
-            True if the ImagingExtractor has a time vector set, otherwise False.
-        """
-        return self._times is not None
-
-    def copy_times(self, extractor) -> None:
-        """Copy times from another extractor.
-
-        Parameters
-        ----------
-        extractor
-            The extractor from which the times will be copied.
-        """
-        if extractor._times is not None:
-            self.set_times(deepcopy(extractor._times))
-
     def __eq__(self, imaging_extractor2):
         image_size_equal = self.get_image_size() == imaging_extractor2.get_image_size()
         num_frames_equal = self.get_num_frames() == imaging_extractor2.get_num_frames()

src/roiextractors/segmentationextractor.py

@@ -10,17 +10,18 @@
     Class to get a lazy frame slice.
 """
 
-from abc import ABC, abstractmethod
+from abc import abstractmethod
 from typing import Union, Optional, Tuple, Iterable, List, get_args
 
 import numpy as np
 from numpy.typing import ArrayLike
 
+from .baseextractor import BaseExtractor
 from .extraction_tools import ArrayType, IntType, FloatType
 from .extraction_tools import _pixel_mask_extractor
 
 
-class SegmentationExtractor(ABC):
+class SegmentationExtractor(BaseExtractor):
     """Abstract segmentation extractor class.
 
     An abstract class that contains all the meta-data and output data from
@@ -31,43 +32,6 @@ class SegmentationExtractor(ABC):
     format specific classes that inherit from this.
     """
 
-    def __init__(self):
-        """Create a new SegmentationExtractor for a specific data format (unique to each child SegmentationExtractor)."""
-        self._times = None
-
-    @abstractmethod
-    def get_image_size(self) -> ArrayType:
-        """Get frame size of movie (height, width).
-
-        Returns
-        -------
-        no_rois: array_like
-            2-D array: image height x image width
-        """
-        pass
-
-    @abstractmethod
-    def get_num_frames(self) -> int:
-        """Get the number of frames in the recording (duration of recording).
-
-        Returns
-        -------
-        num_frames: int
-            Number of frames in the recording.
-        """
-        pass
-
-    @abstractmethod
-    def get_sampling_frequency(self) -> float:
-        """Get the sampling frequency in Hz.
-
-        Returns
-        -------
-        sampling_frequency: float
-            Sampling frequency of the recording in Hz.
-        """
-        pass
-
     @abstractmethod
     def get_roi_ids(self) -> list:
         """Get the list of ROI ids.
@@ -308,50 +272,6 @@ def get_summary_images(self, names: Optional[list[str]] = None) -> dict:
         """
         pass
 
-    # TODO: Refactor _times methods from ImagingExtractor and SegmentationExtractor into a BaseExtractor class
-    def set_times(self, times: ArrayType):
-        """Set the recording times in seconds for each frame.
-
-        Parameters
-        ----------
-        times: array-like
-            The times in seconds for each frame
-
-        Notes
-        -----
-        Operates on _times attribute of the SegmentationExtractor object.
-        """
-        assert len(times) == self.get_num_frames(), "'times' should have the same length of the number of frames!"
-        self._times = np.array(times, dtype=np.float64)
-
-    def has_time_vector(self) -> bool:
-        """Detect if the SegmentationExtractor has a time vector set or not.
-
-        Returns
-        -------
-        has_time_vector: bool
-            True if the SegmentationExtractor has a time vector set, otherwise False.
-        """
-        return self._times is not None
-
-    def frame_to_time(self, frames: Union[IntType, ArrayType]) -> Union[FloatType, ArrayType]:
-        """Get the timing of frames in unit of seconds.
-
-        Parameters
-        ----------
-        frames: int or array-like
-            The frame or frames to be converted to times
-
-        Returns
-        -------
-        times: float or array-like
-            The corresponding times in seconds
-        """
-        if self._times is None:
-            return frames / self.get_sampling_frequency()
-        else:
-            return self._times[frames]
-
     def frame_slice(self, start_frame: Optional[int] = None, end_frame: Optional[int] = None):
         """Return a new ImagingExtractor ranging from the start_frame to the end_frame.