Tighten return types of always-succeeding to_affine()

src/transformnd/transforms/affine.py

@@ -78,7 +78,7 @@ def __init__(
         if np.allclose(np.zeros_like(self._translation), self._translation):
             self._translation = None
 
-    def to_affine(self) -> Self | None:
+    def to_affine(self) -> Self:
         return self
 
     def cast_matrix(self, namespace, device) -> ArrayT:

src/transformnd/transforms/map_axis.py

@@ -44,7 +44,7 @@ def __init__(
     def is_identity(self) -> bool:
         return all(a == b for a, b in enumerate(self.permutation))
 
-    def to_affine(self) -> Affine[ArrayT] | None:
+    def to_affine(self) -> Affine[ArrayT]:
         m = np.eye(self.ndims.source)
         m = m[self.permutation, :]
         return Affine.from_linear_map(m, spaces=self.spaces)  # type: ignore

src/transformnd/transforms/project_axis.py

@@ -92,7 +92,7 @@ def apply(self, coords: ArrayT) -> ArrayT:
     def is_identity(self) -> bool:
         return not self.created and not self.dropped
 
-    def to_affine(self) -> Affine | None:
+    def to_affine(self) -> Affine:
         m = np.eye(self.ndims.source)
         out_m = self.apply(m)
         return Affine.from_linear_map(out_m.T)

src/transformnd/transforms/simple.py

@@ -42,7 +42,7 @@ def __init__(
     def invert(self) -> Transform[ArrayT]:
         return type(self)(self.ndims.source, spaces=self.spaces.invert())
 
-    def to_affine(self) -> Affine[ArrayT] | None:
+    def to_affine(self) -> Affine[ArrayT]:
         return Affine[ArrayT].identity(self.ndims.source, spaces=self.spaces)
 
     def apply(self, coords: ArrayT) -> ArrayT:
@@ -81,7 +81,7 @@ def __init__(
             NDims(len(self.translation), len(self.translation)), spaces=spaces
         )
 
-    def to_affine(self) -> Affine[ArrayT] | None:
+    def to_affine(self) -> Affine[ArrayT]:
         return Affine[ArrayT].translation(self.translation, spaces=self.spaces)
 
     def apply(self, coords: ArrayT) -> ArrayT:
@@ -129,7 +129,7 @@ def __init__(
             raise ValueError(f"Scale must be 1D, got shape {self.scale.shape}")
         super().__init__(NDims(len(self.scale), len(self.scale)), spaces=spaces)
 
-    def to_affine(self) -> Affine[ArrayT] | None:
+    def to_affine(self) -> Affine[ArrayT]:
         return Affine[ArrayT].scaling(self.scale, spaces=self.spaces)
 
     def apply(self, coords: ArrayT) -> ArrayT: