Pad images with 0 on right and bottom, if images differ in dimensions

.gitignore

@@ -50,3 +50,4 @@ data/
 tests/data
 uv.lock
 .asv/
+.venv/

src/spatialdata_io/readers/macsima.py

@@ -38,6 +38,7 @@
     "B": "bleach",  # v1
     "AntigenCycle": "stain",  # v0
     "S": "stain",  # v1
+    "AF": "autofluorescence",
 }
 
 
@@ -125,12 +126,11 @@ def from_paths(
                 ),
             )
         imgs = [imread(img, **imread_kwargs) for img in valid_files]
-        for img, path in zip(imgs, valid_files, strict=True):
-            if img.shape[1:] != imgs[0].shape[1:]:
-                raise ValueError(
-                    f"Images are not all the same size. Image {path} has shape {img.shape[1:]} while the first image "
-                    f"{valid_files[0]} has shape {imgs[0].shape[1:]}"
-                )
+
+        # Pad images to same dimensions if necessary
+        if cls._check_for_differing_xy_dimensions(imgs):
+            imgs = cls._pad_images(imgs)
+
         # create MultiChannelImage object with imgs and metadata
         output = cls(data=imgs, metadata=channel_metadata)
         return output
@@ -220,6 +220,56 @@ def calc_scale_factors(self, default_scale_factor: int = 2) -> list[int]:
     def get_stack(self) -> da.Array:
         return da.stack(self.data, axis=0).squeeze(axis=1)
 
+    @staticmethod
+    def _check_for_differing_xy_dimensions(imgs: list[da.Array]) -> bool:
+        """Checks whether any of the images have differing extent in dimensions X and Y."""
+        # Shape has order CYX
+        dims_x = [x.shape[2] for x in imgs]
+        dims_y = [x.shape[1] for x in imgs]
+
+        dims_x_different = False if len(set(dims_x)) == 1 else True
+        dims_y_different = False if len(set(dims_y)) == 1 else True
+
+        different_dimensions = any([dims_x_different, dims_y_different])
+
+        warnings.warn(
+            "Supplied images have different dimensions!",
+            UserWarning,
+            stacklevel=2,
+        )
+
+        return different_dimensions
+
+    @staticmethod
+    def _pad_images(imgs: list[da.Array]) -> list[da.Array]:
+        """Pad all images to the same dimensions in X and Y with 0s."""
+        dims_x_max = max([x.shape[2] for x in imgs])
+        dims_y_max = max([x.shape[1] for x in imgs])
+
+        warnings.warn(
+            f"Padding images with 0s to same size of ({dims_y_max}, {dims_x_max})",
+            UserWarning,
+            stacklevel=2,
+        )
+
+        padded_imgs = []
+        for img in imgs:
+            pad_y = dims_y_max - img.shape[1]
+            pad_x = dims_x_max - img.shape[2]
+            # Only pad if necessary
+            if (pad_y, pad_y) != (0, 0):
+                # Always pad to the right/bottom
+                pad_width = (
+                    (0, 0),
+                    (0, pad_y),
+                    (0, pad_x),
+                )
+
+                img = da.pad(img, pad_width, mode="constant", constant_values=0)
+            padded_imgs.append(img)
+
+        return padded_imgs
+
 
 def macsima(
     path: str | Path,
@@ -331,6 +381,9 @@ def macsima(
             for p in path.iterdir()
             if p.is_dir() and (not filter_folder_names or not any(f in p.name for f in filter_folder_names))
         ]:
+            if not len(list(p.glob("*.tif*"))):
+                warnings.warn(f"No tif files found in {p}, skipping it!", UserWarning, stacklevel=2)
+                continue
             sdatas[p.stem] = parse_processed_folder(
                 path=p,
                 imread_kwargs=imread_kwargs,

tests/test_macsima.py

@@ -1,4 +1,5 @@
 import math
+import os
 import shutil
 from copy import deepcopy
 from pathlib import Path
@@ -93,14 +94,61 @@ def test_exception_on_no_valid_files(tmp_path: Path) -> None:
     # Write a tiff file without metadata
     height = 10
     width = 10
-    arr = np.zeros((height, width, 1), dtype=np.uint16)
+    arr = np.zeros((1, height, width), dtype=np.uint16)
     path_no_metadata = Path(tmp_path) / "tiff_no_metadata.tiff"
     imwrite(path_no_metadata, arr, metadata=None, description=None, software=None, datetime=None)
 
     with pytest.raises(ValueError, match="No valid files were found"):
         macsima(tmp_path)
 
 
+def test_multiple_subfolder_parsing_skips_emtpy_folders(tmp_path: Path) -> None:
+    parent_folder = tmp_path / "test_folder"
+    shutil.copytree("./data/OMAP23_small", parent_folder / "OMAP23_small")
+    os.makedirs(parent_folder / "empty_folder")
+
+    with pytest.warns(UserWarning, match="No tif files found in .* skipping it"):
+        sdata = macsima(parent_folder, parsing_style="processed_multiple_folders")
+    assert len(sdata.images.keys()) == 1
+
+
+@pytest.mark.parametrize(
+    "dimensions,expected",
+    [
+        (((10, 10), (10, 10)), False),
+        (((10, 10), (15, 10)), True),
+        (((10, 10), (10, 15)), True),
+        (((15, 10), (10, 15)), True),
+    ],
+)
+def test_check_differing_dimensions_works(dimensions: tuple[tuple[int, int], tuple[int, int]], expected: bool) -> None:
+    imgs = []
+    for img_dim in dimensions:
+        arr = da.from_array(np.ones((1, img_dim[0], img_dim[1]), dtype=np.uint16))
+        imgs.append(arr)
+
+    if expected:
+        with pytest.warns(UserWarning, match="Supplied images have different dimensions!"):
+            assert MultiChannelImage._check_for_differing_xy_dimensions(imgs) == expected
+    else:
+        assert MultiChannelImage._check_for_differing_xy_dimensions(imgs) == expected
+
+
+def test_padding_on_differing_dimensions() -> None:
+    heights = [10, 10, 15, 20]
+    widths = [10, 15, 10, 20]
+
+    imgs = []
+    for height, width in zip(heights, widths, strict=True):
+        arr = da.from_array(np.ones((1, height, width), dtype=np.uint16))
+        imgs.append(arr)
+
+    with pytest.warns(UserWarning, match="Padding images with 0s to same size of \\(20, 20\\)"):
+        imgs_padded = MultiChannelImage._pad_images(imgs)
+    for img in imgs_padded:
+        assert img.shape == (1, 20, 20)
+
+
 @skip_if_below_python_version()
 @pytest.mark.parametrize(
     "dataset,expected",