fixed compat

imops/compat.py

@@ -9,13 +9,16 @@
     from numpy import VisibleDeprecationWarning
 
 try:
-    from scipy.ndimage._morphology._ni_support import _normalize_sequence as normalize_sequence
+    from scipy.ndimage._morphology import _ni_support
 except ImportError:
-    from scipy.ndimage.morphology._ni_support import _normalize_sequence as normalize_sequence
+    from scipy.ndimage.morphology import _ni_support
 
 try:
     from scipy.spatial import QhullError
 except ImportError:
     from scipy.spatial.qhull import QhullError
 
 from scipy.ndimage._nd_image import euclidean_feature_transform  # noqa
+
+
+normalize_sequence = _ni_support._normalize_sequence  # noqa

imops/crop.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 import numpy as np
 
 from .backend import BackendLike
@@ -6,7 +8,9 @@
 from .utils import AxesLike, AxesParams, assert_subdtype, broadcast_axis, fill_by_indices
 
 
-def crop_to_shape(x: np.ndarray, shape: AxesLike, axis: AxesLike = None, ratio: AxesParams = 0.5) -> np.ndarray:
+def crop_to_shape(
+    x: np.ndarray, shape: AxesLike, axis: Optional[AxesLike] = None, ratio: AxesParams = 0.5
+) -> np.ndarray:
     """
     Crop `x` to match `shape` along `axis`.
 
@@ -57,8 +61,8 @@ def crop_to_shape(x: np.ndarray, shape: AxesLike, axis: AxesLike = None, ratio:
 def crop_to_box(
     x: np.ndarray,
     box: np.ndarray,
-    axis: AxesLike = None,
-    padding_values: AxesParams = None,
+    axis: Optional[AxesLike] = None,
+    padding_values: Optional[AxesParams] = None,
     num_threads: int = _NUMERIC_DEFAULT_NUM_THREADS,
     backend: BackendLike = None,
 ) -> np.ndarray:

imops/interp1d.py

@@ -1,4 +1,4 @@
-from typing import Union
+from typing import Optional, Union
 from warnings import warn
 
 import numpy as np
@@ -71,7 +71,7 @@ def __init__(
         kind: Union[int, str] = 'linear',
         axis: int = -1,
         copy: bool = True,
-        bounds_error: bool = None,
+        bounds_error: Optional[bool] = None,
         fill_value: Union[float, str] = np.nan,
         assume_sorted: bool = False,
         num_threads: int = -1,

imops/interp2d.py

@@ -1,4 +1,5 @@
 from platform import python_version
+from typing import Optional
 
 import numpy as np
 from scipy.spatial import KDTree
@@ -47,9 +48,9 @@ class Linear2DInterpolator(Linear2DInterpolatorCpp):
     def __init__(
         self,
         points: np.ndarray,
-        values: np.ndarray = None,
+        values: Optional[np.ndarray] = None,
         num_threads: int = 1,
-        triangles: np.ndarray = None,
+        triangles: Optional[np.ndarray] = None,
         **kwargs,
     ):
         if triangles is not None:
@@ -77,7 +78,7 @@ def __init__(
         # FIXME: add backend dispatch
         self.num_threads = normalize_num_threads(num_threads, Cython(), warn_stacklevel=3)
 
-    def __call__(self, points: np.ndarray, values: np.ndarray = None, fill_value: float = 0.0) -> np.ndarray:
+    def __call__(self, points: np.ndarray, values: Optional[np.ndarray] = None, fill_value: float = 0.0) -> np.ndarray:
         """
         Evaluate the interpolant
 

imops/measure.py

@@ -1,6 +1,6 @@
 from collections import namedtuple
 from platform import python_version
-from typing import List, NamedTuple, Sequence, Tuple, Union
+from typing import List, NamedTuple, Optional, Sequence, Tuple, Union
 from warnings import warn
 
 import numpy as np
@@ -32,12 +32,12 @@
 # TODO: Make it work and test on immutable arrays as soon as `cc3d` package is fixed
 def label(
     label_image: np.ndarray,
-    background: int = None,
-    connectivity: int = None,
+    background: Optional[int] = None,
+    connectivity: Optional[int] = None,
     return_num: bool = False,
     return_labels: bool = False,
     return_sizes: bool = False,
-    dtype: type = None,
+    dtype: Optional[type] = None,
 ) -> Union[np.ndarray, NamedTuple]:
     """
     Fast version of `skimage.measure.label` which optionally returns number of connected components, labels and sizes.
@@ -139,8 +139,8 @@ def label(
 
 def center_of_mass(
     array: np.ndarray,
-    labels: np.ndarray = None,
-    index: Union[int, Sequence[int]] = None,
+    labels: Union[np.ndarray, None] = None,
+    index: Union[int, Sequence[int], None] = None,
     num_threads: int = -1,
     backend: BackendLike = None,
 ) -> Union[Tuple[float, ...], List[Tuple[float, ...]]]:

imops/morphology.py

@@ -1,4 +1,4 @@
-from typing import Callable, Tuple, Union
+from typing import Callable, Optional, Tuple, Union
 from warnings import warn
 
 import numpy as np
@@ -32,8 +32,8 @@ def morphology_op_wrapper(
 ) -> Callable:
     def wrapped(
         image: np.ndarray,
-        footprint: np.ndarray = None,
-        output: np.ndarray = None,
+        footprint: Optional[np.ndarray] = None,
+        output: Optional[np.ndarray] = None,
         boxed: bool = False,
         num_threads: int = -1,
         backend: BackendLike = None,
@@ -163,8 +163,8 @@ def wrapped(
 
 def binary_dilation(
     image: np.ndarray,
-    footprint: np.ndarray = None,
-    output: np.ndarray = None,
+    footprint: Optional[np.ndarray] = None,
+    output: Optional[np.ndarray] = None,
     boxed: bool = False,
     num_threads: int = -1,
     backend: BackendLike = None,
@@ -217,8 +217,8 @@ def binary_dilation(
 
 def binary_erosion(
     image: np.ndarray,
-    footprint: np.ndarray = None,
-    output: np.ndarray = None,
+    footprint: Optional[np.ndarray] = None,
+    output: Optional[np.ndarray] = None,
     boxed: bool = False,
     num_threads: int = -1,
     backend: BackendLike = None,
@@ -271,8 +271,8 @@ def binary_erosion(
 
 def binary_closing(
     image: np.ndarray,
-    footprint: np.ndarray = None,
-    output: np.ndarray = None,
+    footprint: Optional[np.ndarray] = None,
+    output: Optional[np.ndarray] = None,
     boxed: bool = False,
     num_threads: int = -1,
     backend: BackendLike = None,
@@ -326,8 +326,8 @@ def binary_closing(
 
 def binary_opening(
     image: np.ndarray,
-    footprint: np.ndarray = None,
-    output: np.ndarray = None,
+    footprint: Optional[np.ndarray] = None,
+    output: Optional[np.ndarray] = None,
     boxed: bool = False,
     num_threads: int = -1,
     backend: BackendLike = None,
@@ -371,7 +371,7 @@ def binary_opening(
 
 def distance_transform_edt(
     image: np.ndarray,
-    sampling: Tuple[float] = None,
+    sampling: Optional[Tuple[float]] = None,
     return_distances: bool = True,
     return_indices: bool = False,
     num_threads: int = -1,

imops/numeric.py

@@ -1,4 +1,4 @@
-from typing import Callable, Sequence, Union
+from typing import Callable, Optional, Sequence, Union
 
 import numpy as np
 
@@ -99,7 +99,7 @@ def _choose_cython_copy(ndim: int, is_fp16: bool, fast: bool) -> Callable:
 def pointwise_add(
     nums: np.ndarray,
     summand: Union[np.array, int, float],
-    output: np.ndarray = None,
+    output: Optional[np.ndarray] = None,
     num_threads: int = _NUMERIC_DEFAULT_NUM_THREADS,
     backend: BackendLike = None,
 ) -> np.ndarray:
@@ -256,7 +256,7 @@ def fill_(
 def full(
     shape: Union[int, Sequence[int]],
     fill_value: Union[np.number, int, float],
-    dtype: Union[type, str] = None,
+    dtype: Union[type, str, None] = None,
     order: str = 'C',
     num_threads: int = _NUMERIC_DEFAULT_NUM_THREADS,
     backend: BackendLike = None,
@@ -302,7 +302,7 @@ def full(
 
 def copy(
     nums: np.ndarray,
-    output: np.ndarray = None,
+    output: Optional[np.ndarray] = None,
     order: str = 'K',
     num_threads: int = _NUMERIC_DEFAULT_NUM_THREADS,
     backend: BackendLike = None,

imops/pad.py

@@ -1,4 +1,4 @@
-from typing import Callable, Sequence, Union
+from typing import Callable, Optional, Sequence, Union
 
 import numpy as np
 
@@ -10,7 +10,7 @@
 def pad(
     x: np.ndarray,
     padding: Union[AxesLike, Sequence[Sequence[int]]],
-    axis: AxesLike = None,
+    axis: Optional[AxesLike] = None,
     padding_values: Union[AxesParams, Callable] = 0,
     num_threads: int = _NUMERIC_DEFAULT_NUM_THREADS,
     backend: BackendLike = None,
@@ -76,7 +76,7 @@ def pad(
 def pad_to_shape(
     x: np.ndarray,
     shape: AxesLike,
-    axis: AxesLike = None,
+    axis: Optional[AxesLike] = None,
     padding_values: Union[AxesParams, Callable] = 0,
     ratio: AxesParams = 0.5,
     num_threads: int = _NUMERIC_DEFAULT_NUM_THREADS,
@@ -135,7 +135,7 @@ def pad_to_shape(
 def pad_to_divisible(
     x: np.ndarray,
     divisor: AxesLike,
-    axis: AxesLike = None,
+    axis: Optional[AxesLike] = None,
     padding_values: Union[AxesParams, Callable] = 0,
     ratio: AxesParams = 0.5,
     remainder: AxesLike = 0,

imops/radon.py

@@ -1,4 +1,4 @@
-from typing import Sequence, Tuple, Union
+from typing import Optional, Sequence, Tuple, Union
 
 import numpy as np
 from scipy.fftpack import fft, ifft
@@ -15,7 +15,7 @@
 
 def radon(
     image: np.ndarray,
-    axes: Tuple[int, int] = None,
+    axes: Optional[Tuple[int, int]] = None,
     theta: Union[int, Sequence[float]] = 180,
     return_fill: bool = False,
     num_threads: int = -1,
@@ -104,8 +104,8 @@ def radon(
 
 def inverse_radon(
     sinogram: np.ndarray,
-    axes: Tuple[int, int] = None,
-    theta: Union[int, Sequence[float]] = None,
+    axes: Optional[Tuple[int, int]] = None,
+    theta: Union[int, Sequence[float], None] = None,
     fill_value: float = 0,
     a: float = 0,
     b: float = 1,

imops/utils.py

@@ -169,7 +169,9 @@ def wrapper(
     return wrapper
 
 
-def build_slices(start: Sequence[int], stop: Sequence[int] = None, step: Sequence[int] = None) -> Tuple[slice, ...]:
+def build_slices(
+    start: Sequence[int], stop: Optional[Sequence[int]] = None, step: Optional[Sequence[int]] = None
+) -> Tuple[slice, ...]:
     """
     Returns a tuple of slices built from `start` and `stop` with `step`.
 

imops/zoom.py

@@ -1,5 +1,5 @@
 from platform import python_version
-from typing import Callable, Sequence, Union
+from typing import Callable, Optional, Sequence, Union
 from warnings import warn
 
 import numpy as np
@@ -72,7 +72,7 @@ def _choose_numba_zoom(ndim: int, order: int) -> Callable:
 def zoom(
     x: np.ndarray,
     scale_factor: AxesParams,
-    axis: AxesLike = None,
+    axis: Optional[AxesLike] = None,
     order: int = 1,
     fill_value: Union[float, Callable] = 0,
     num_threads: int = -1,
@@ -129,7 +129,7 @@ def zoom(
 def zoom_to_shape(
     x: np.ndarray,
     shape: AxesLike,
-    axis: AxesLike = None,
+    axis: Optional[AxesLike] = None,
     order: int = 1,
     fill_value: Union[float, Callable] = 0,
     num_threads: int = -1,
@@ -191,7 +191,7 @@ def zoom_to_shape(
 def _zoom(
     image: np.ndarray,
     zoom: Sequence[float],
-    output: np.ndarray = None,
+    output: Optional[np.ndarray] = None,
     order: int = 1,
     mode: str = 'constant',
     cval: float = 0.0,