Remove spikeextractors dependency

.github/workflows/testing.yml

@@ -29,12 +29,14 @@ jobs:
           git config --global user.email "[email protected]"
           git config --global user.name "CI Almighty"
           pip install wheel  # needed for scanimage
-      - name: Test minimal installation
-        run: pip install .
-      - name: Test full installation
-        run: pip install .[full]
-      - name: Install testing requirements (-e needed for codecov report)
-        run: pip install -e .[test]
+
+      - name: Install roiextractors with minimal requirements
+        run: pip install .[test]
+      - name: Run minimal tests
+        run: pytest tests/test_internals -n auto --dist loadscope
+
+      - name: Test full installation (-e needed for codecov report)
+        run: pip install -e .[full]
 
       - name: Get ophys_testing_data current head hash
         id: ophys

requirements-minimal.txt

@@ -1,6 +1,5 @@
 h5py>=2.10.0
 pynwb>=2.0.1
-spikeextractors>=0.9.0
 tqdm>=4.48.2
 lazy_ops>=0.2.0
 dill>=0.3.2

requirements-testing.txt

@@ -1,3 +1,4 @@
 pytest
 pytest-cov
 parameterized==0.8.1
+spikeextractors>=0.9.10

setup.py

@@ -1,6 +1,5 @@
 from pathlib import Path
 from setuptools import setup, find_packages
-from copy import copy
 from shutil import copy as copy_file
 
 
@@ -11,9 +10,8 @@
     install_requires = f.readlines()
 with open(root / "requirements-full.txt") as f:
     full_dependencies = f.readlines()
-testing_dependencies = copy(full_dependencies)
 with open(root / "requirements-testing.txt") as f:
-    testing_dependencies.extend(f.readlines())
+    testing_dependencies = f.readlines()
 extras_require = dict(full=full_dependencies, test=testing_dependencies)
 
 # Create a local copy for the gin test configuration file based on the master file `base_gin_test_config.json`

src/roiextractors/example_datasets/toy_example.py

@@ -1,5 +1,4 @@
 import numpy as np
-import spikeextractors as se
 
 from ..extractors.numpyextractors import (
     NumpyImagingExtractor,
@@ -110,6 +109,8 @@ def toy_example(
         The output segmentation extractor
 
     """
+    import spikeextractors as se
+
     # generate ROIs
     num_rois = int(num_rois)
     roi_pixels, im, means = _generate_rois(

src/roiextractors/extraction_tools.py

@@ -1,14 +1,13 @@
 from functools import wraps
 from pathlib import Path
 from typing import Union, Tuple
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 
 import lazy_ops
 import scipy
 import numpy as np
 from numpy.typing import ArrayLike, DTypeLike
 from tqdm import tqdm
-from spikeextractors.extraction_tools import cast_start_end_frame
 
 try:
     import h5py
@@ -22,6 +21,13 @@
     else:
         from scipy.io.matlab.mio5_params import mat_struct
 
+    HAVE_Scipy = True
+except AttributeError:
+    if hasattr(scipy, "io") and hasattr(scipy.io.matlab, "mat_struct"):
+        from scipy.io import mat_struct
+    else:
+        from scipy.io.matlab.mio5_params import mat_struct
+
     HAVE_Scipy = True
 except ImportError:
     HAVE_Scipy = False
@@ -306,6 +312,25 @@ def corrected_args(imaging, frame_idxs, channel=0):
     return corrected_args
 
 
+def _cast_start_end_frame(start_frame, end_frame):
+    if isinstance(start_frame, float):
+        start_frame = int(start_frame)
+    elif isinstance(start_frame, (int, np.integer, type(None))):
+        start_frame = start_frame
+    else:
+        raise ValueError("start_frame must be an int, float (not infinity), or None")
+    if isinstance(end_frame, float) and np.isfinite(end_frame):
+        end_frame = int(end_frame)
+    elif isinstance(end_frame, (int, np.integer, type(None))):
+        end_frame = end_frame
+    # else end_frame is infinity (accepted for get_unit_spike_train)
+    if start_frame is not None:
+        start_frame = int(start_frame)
+    if end_frame is not None and np.isfinite(end_frame):
+        end_frame = int(end_frame)
+    return start_frame, end_frame
+
+
 def check_get_videos_args(func):
     @wraps(func)
     def corrected_args(imaging, start_frame=None, end_frame=None, channel=0):
@@ -325,7 +350,7 @@ def corrected_args(imaging, start_frame=None, end_frame=None, channel=0):
             end_frame = imaging.get_num_frames()
         assert end_frame - start_frame > 0, "'start_frame' must be less than 'end_frame'!"
 
-        start_frame, end_frame = cast_start_end_frame(start_frame, end_frame)
+        start_frame, end_frame = _cast_start_end_frame(start_frame, end_frame)
         channel = int(channel)
         get_videos_correct_arg = func(imaging, start_frame=start_frame, end_frame=end_frame, channel=channel)
 

src/roiextractors/imagingextractor.py

@@ -1,27 +1,20 @@
 """Base class definitions for all ImagingExtractors."""
 from abc import ABC, abstractmethod
 from typing import Union, Optional, Tuple
-import numpy as np
 from copy import deepcopy
 
-from spikeextractors.baseextractor import BaseExtractor
+import numpy as np
 
-from .extraction_tools import (
-    ArrayType,
-    PathType,
-    DtypeType,
-    FloatType,
-    check_get_videos_args,
-)
+from .extraction_tools import ArrayType, PathType, DtypeType, FloatType
 
 
-class ImagingExtractor(ABC, BaseExtractor):
+class ImagingExtractor(ABC):
     """Abstract class that contains all the meta-data and input data from the imaging data."""
 
-    def __init__(self) -> None:
-        BaseExtractor.__init__(self)
-        assert self.installed, self.installation_mesg
-        self._memmapped = False
+    def __init__(self, *args, **kwargs) -> None:
+        self._args = args
+        self._kwargs = kwargs
+        self._times = None
 
     @abstractmethod
     def get_image_size(self) -> Tuple[int, int]:
@@ -119,12 +112,12 @@ def set_times(self, times: ArrayType) -> None:
         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 copy_times(self, extractor: BaseExtractor) -> None:
+    def copy_times(self, extractor) -> None:
         """This function copies times from another extractor.
 
         Parameters
         ----------
-        extractor: BaseExtractor
+        extractor
             The extractor from which the epochs will be copied
         """
         if extractor._times is not None:

src/roiextractors/segmentationextractor.py

@@ -2,13 +2,12 @@
 from typing import Union
 
 import numpy as np
-from spikeextractors.baseextractor import BaseExtractor
 
 from .extraction_tools import ArrayType, IntType, FloatType
 from .extraction_tools import _pixel_mask_extractor
 
 
-class SegmentationExtractor(ABC, BaseExtractor):
+class SegmentationExtractor(ABC):
     """
     An abstract class that contains all the meta-data and output data from
     the ROI segmentation operation when applied to the pre-processed data.
@@ -18,13 +17,9 @@ class SegmentationExtractor(ABC, BaseExtractor):
     format specific classes that inherit from this.
     """
 
-    installed = True
-    installation_mesg = ""
-
     def __init__(self):
-        assert self.installed, self.installation_mesg
-        BaseExtractor.__init__(self)
         self._sampling_frequency = None
+        self._times = None
         self._channel_names = ["OpticalChannel"]
         self._num_planes = 1
         self._roi_response_raw = None