refactor(transforms): fix typo in variable name

yzx9 · Jun 3, 2024 · 663b0ae · 663b0ae
1 parent 7d38ea8
commit 663b0ae
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Showing 3 changed files with 16 additions and 5 deletions.
diff --git a/examples/pytorch/branch_dataset.py b/examples/pytorch/branch_dataset.py
@@ -41,7 +41,7 @@ def __init__(
         save : Union[str, bool], default `True`
             Save branch data to file if not False. If `True`, automatically
             generate file name.
-        transfroms : Transfroms[Branch, T], optional
+        transforms : Transforms[Branch, T], optional
             Branch transformations.
 
         See Also

diff --git a/examples/pytorch/tree_folder_dataset.py b/examples/pytorch/tree_folder_dataset.py
@@ -30,7 +30,7 @@ def __init__(
         ----------
         swc_dir : str
             Path of SWC file directory.
-        transfroms : Transfroms[Tree, T], optional
+        transforms : Transforms[Tree, T], optional
             Branch transformations.
 
         See Also

diff --git a/swcgeom/transforms/image_stack.py b/swcgeom/transforms/image_stack.py
@@ -27,6 +27,7 @@
     SDFObject,
 )
 from tqdm import tqdm
+from typing_extensions import deprecated
 
 from swcgeom.core import Population, Tree
 from swcgeom.transforms.base import Transform
@@ -63,9 +64,9 @@ def __call__(self, x: Tree) -> npt.NDArray[np.uint8]:
         ONLY works for small image stacks, use :meth`transform_and_save`
         for big image stack.
         """
-        return np.stack(list(self.transfrom(x, verbose=False)), axis=0)
+        return np.stack(list(self.transform(x, verbose=False)), axis=0)
 
-    def transfrom(
+    def transform(
         self,
         x: Tree,
         verbose: bool = True,
@@ -102,10 +103,20 @@ def transfrom(
             frame = (255 * voxel[..., 0, 0]).astype(np.uint8)
             yield frame
 
+    @deprecated("Use transform instead")
+    def transfrom(
+        self,
+        x: Tree,
+        verbose: bool = True,
+        *,
+        ranges: Optional[tuple[npt.ArrayLike, npt.ArrayLike]] = None,
+    ) -> Iterable[npt.NDArray[np.uint8]]:
+        return self.transform(x, verbose, ranges=ranges)
+
     def transform_and_save(
         self, fname: str, x: Tree, verbose: bool = True, **kwargs
     ) -> None:
-        self.save_tif(fname, self.transfrom(x, verbose=verbose, **kwargs))
+        self.save_tif(fname, self.transform(x, verbose=verbose, **kwargs))
 
     def transform_population(
         self, population: Population | str, verbose: bool = True