Do not use MRO with NamedTuples, which is not supported prior to py 3.11.

PiperOrigin-RevId: 783502750

Author: mjanusz

connectomics/common/array.py

@@ -43,9 +43,9 @@
 CanonicalSliceOrPointLookups = Union[CanonicalSlice, PointLookups]
 
 ArrayLike = npt.ArrayLike
-Tuple3f = Tuple[float, float, float]
-Tuple3i = Tuple[int, int, int]
-Tuple4i = Tuple[int, int, int, int]
+Tuple3f = tuple[float, float, float]
+Tuple3i = tuple[int, int, int]
+Tuple4i = tuple[int, int, int, int]
 ArrayLike3d = Union[npt.ArrayLike, Tuple3f, Tuple3i]
 
 

connectomics/common/tuples.py

@@ -22,7 +22,8 @@
 C = TypeVar('C')
 
 
-class XYZ(Generic[T], NamedTuple):
+@dataclasses.dataclass(frozen=True)
+class XYZ(Generic[T]):
   """XYZ is a named tuple for a 3-dimensional vector.
 
   Allows static type checker to differentiate between XYZ and ZYX, and allows
@@ -48,8 +49,18 @@ def xyz(self) -> 'XYZ[T]':
   def zyx(self) -> 'ZYX[T]':
     return ZYX(*self[::-1])
 
+  def __iter__(self):
+    return iter(dataclasses.astuple(self))
+
+  def __getitem__(self, item):
+    return dataclasses.astuple(self)[item]
+
+  def __len__(self):
+    return 3
+
 
-class ZYX(Generic[T], NamedTuple):
+@dataclasses.dataclass(frozen=True)
+class ZYX(Generic[T]):
   """ZYX is a named tuple for a 3-dimensional vector.
 
   Allows static type checker to differentiate between XYZ and ZYX, and allows
@@ -75,8 +86,18 @@ def __eq__(self, other):
     # Defer to tuple equality.
     return self[:] == other
 
+  def __iter__(self):
+    return iter(dataclasses.astuple(self))
+
+  def __getitem__(self, item):
+    return dataclasses.astuple(self)[item]
+
+  def __len__(self):
+    return 3
+
 
-class XYZC(Generic[T], NamedTuple):
+@dataclasses.dataclass(frozen=True)
+class XYZC(Generic[T]):
   """XYZC is a named tuple for a 4-dimensional vector."""
 
   x: T
@@ -111,8 +132,18 @@ def xyzc(self) -> 'XYZC[T]':
   def czyx(self) -> 'CZYX[T]':
     return CZYX(*self[::-1])
 
+  def __iter__(self):
+    return iter(dataclasses.astuple(self))
+
+  def __getitem__(self, item):
+    return dataclasses.astuple(self)[item]
+
+  def __len__(self):
+    return 4
+
 
-class CZYX(Generic[T], NamedTuple):
+@dataclasses.dataclass(frozen=True)
+class CZYX(Generic[T]):
   """CZYX is a named tuple for a 4-dimensional vector."""
 
   c: T
@@ -148,6 +179,15 @@ def __eq__(self, other):
     # Defer to tuple equality.
     return self[:] == other
 
+  def __iter__(self):
+    return iter(dataclasses.astuple(self))
+
+  def __getitem__(self, item):
+    return dataclasses.astuple(self)[item]
+
+  def __len__(self):
+    return 4
+
 
 def named_tuple_field(
     cls: C,

connectomics/volume/base.py

@@ -21,11 +21,13 @@
 
 from connectomics.common import array
 from connectomics.common import bounding_box
+from connectomics.common import tuples
 from connectomics.volume import metadata
 from connectomics.volume import subvolume
 import numpy as np
 
 Subvolume = subvolume.Subvolume
+XYZ = tuples.XYZ
 
 
 def slice_to_bbox(ind: array.CanonicalSlice) -> bounding_box.BoundingBox:
@@ -114,12 +116,12 @@ def write(self, subvol: subvolume.Subvolume):
         subvol.data)
 
   @property
-  def volume_size(self) -> array.Tuple3i:
+  def volume_size(self) -> XYZ[int]:
     """Volume size in voxels, XYZ."""
     return self.meta.volume_size
 
   @property
-  def pixel_size(self) -> array.Tuple3f:
+  def pixel_size(self) -> XYZ[float]:
     """Size of an individual voxels in physical dimensions (Nanometers)."""
     return self.meta.pixel_size
 

connectomics/volume/metadata.py

@@ -45,8 +45,8 @@ class VolumeMetadata(
     dtype: Datatype of the volume. Must be numpy compatible.
   """
   path: str
-  volume_size: XYZ[int] = tuples.named_tuple_field(XYZ[int])
-  pixel_size: XYZ[float] = tuples.named_tuple_field(XYZ[float])
+  volume_size: XYZ[int] # = tuples.named_tuple_field(XYZ[int])
+  pixel_size: XYZ[float]  #= tuples.named_tuple_field(XYZ[float])
   bounding_boxes: list[bounding_box.BoundingBox] = dataclasses.field(
       default_factory=list
   )

connectomics/volume/tsv_decorator.py

@@ -18,9 +18,13 @@
 
 from connectomics.common import array
 from connectomics.common import bounding_box
+from connectomics.common import tuples
 from connectomics.volume import base
 import numpy as np
 
+
+XYZ = tuples.XYZ
+
 # List of python dicts of specs to decorate a volume. Expected to have the
 # following fields:
 #   "decorator": Name of the decorator class. By default the decorator is looked
@@ -100,11 +104,11 @@ def get_slices(self, slices: array.CanonicalSlice) -> np.ndarray:
     return self._wrapped.get_slices(slices)
 
   @property
-  def volume_size(self) -> array.Tuple3i:
+  def volume_size(self) -> XYZ[int]:
     return self._wrapped.volume_size
 
   @property
-  def voxel_size(self) -> array.Tuple3f:
+  def voxel_size(self) -> XYZ[float]:
     return self._wrapped.pixel_size
 
   @property