remove MultiChannelImage.dimensions

src/depiction/image/multi_channel_image.py

@@ -153,13 +153,6 @@ def bg_mask_flat(self) -> DataArray:
         """A boolean mask indicating the background values as `True` and non-background values as `False`."""
         return ~self.fg_mask_flat
 
-    @property
-    def dimensions(self) -> tuple[int, int]:
-        """Returns width and height of the image."""
-        # TODO reconsider this method (adding it now for compatibility)
-        warnings.warn("dimensions is deprecated, use sizes instead", DeprecationWarning)
-        return self._data.sizes["x"], self._data.sizes["y"]
-
     @property
     def sizes(self) -> dict[Literal["y", "x", "c"], int]:
         """Size of the image along each dimension"""

src/depiction/tools/simulate/generate_synthetic_imzml.py

@@ -1,9 +1,8 @@
-from pathlib import Path
-
 import cyclopts
 import numpy as np
 import polars as pl
 from numpy.typing import NDArray
+from pathlib import Path
 from perlin_noise import PerlinNoise
 
 from depiction.image.multi_channel_image import MultiChannelImage
@@ -63,11 +62,12 @@ def generate_centroided_spectrum(
 
     def write_file(self, labels: MultiChannelImage, target_masses: NDArray[float], output: GenericWriteFile):
         # input validation
-        if labels.n_channels != len(target_masses):
-            msg = f"Number of channels in labels ({labels.n_channels}) does not match the number of target masses ({len(target_masses)})"
-            raise ValueError(msg)
-        if labels.dimensions != (self._width, self._height):
-            msg = f"Dimensions of labels ({labels.dimensions}) do not match the dimensions of the synthetic image ({self._width}, {self._height})"
+        target_sizes = {"x": self._width, "y": self._height, "c": len(target_masses)}
+        if labels.sizes != target_sizes:
+            msg = (
+                f"Dimensions of labels {labels.sizes} do not match the dimensions of the synthetic image "
+                f"{target_sizes}."
+            )
             raise ValueError(msg)
 
         # collect the relevant input information
@@ -127,8 +127,8 @@ def generate_imzml(
     panel_df = pl.read_csv(mass_list_file)
 
     gen = GenerateSyntheticImzml(
-        height=label_img.dimensions[1],
-        width=label_img.dimensions[0],
+        height=label_img.sizes["y"],
+        width=label_img.sizes["x"],
         rng=np.random.default_rng(),
         mz_min=panel_df["mass"].min(),
         mz_max=panel_df["mass"].max(),

system_tests/calibration/test_pipeline_calibration_only.py

@@ -34,6 +34,5 @@ def test_run_pipeline(work_dir: Path):
     process_chunk(chunk_dir=work_dir)
     # basic checks of the .ome.tiff image
     image = OmeTiff.read_image(work_dir / "images_default.ome.tiff", bg_value=0.0)
-    assert image.n_channels == 118
+    assert image.sizes == {"x": 128, "y": 137, "c": 118}
     assert image.n_nonzero == 10131
-    assert image.dimensions == (128, 137)

tests/unit/image/test_multi_channel_image.py

@@ -120,10 +120,6 @@ def test_fg_mask_flat(mock_image_sparse) -> None:
     xarray.testing.assert_equal(expected_fg_mask_flat, mock_image_sparse.fg_mask_flat)
 
 
-def test_dimensions(mock_image: MultiChannelImage) -> None:
-    assert mock_image.dimensions == (2, 3)
-
-
 def test_sizes(mock_image: MultiChannelImage) -> None:
     assert mock_image.sizes == {"y": 3, "x": 2, "c": 2}
 
@@ -245,7 +241,7 @@ def test_read_hdf5(mocker: MockerFixture, mock_data: DataArray) -> None:
 def test_with_channel_names(mock_image: MultiChannelImage) -> None:
     image = mock_image.with_channel_names(channel_names=["New Channel Name", "B"])
     assert image.channel_names == ["New Channel Name", "B"]
-    assert image.dimensions == mock_image.dimensions
+    assert image.sizes == mock_image.sizes
     assert image.n_channels == mock_image.n_channels == 2
     np.testing.assert_array_equal(image.data_spatial.values, mock_image.data_spatial.values)
 

tests/unit/image/test_multi_channel_image_concatenation.py

@@ -80,7 +80,7 @@ def test_get_combined_image_index(concat_image: MultiChannelImageConcatenation)
 def test_get_single_image(request, concat_image: MultiChannelImageConcatenation, image_index: int, image_fixture: str):
     expected_image = request.getfixturevalue(image_fixture)
     result_image = concat_image.get_single_image(index=image_index)
-    assert result_image.dimensions == expected_image.dimensions
+    assert result_image.sizes == expected_image.sizes
     xarray.testing.assert_equal(result_image.coordinates_flat, expected_image.coordinates_flat)
     xarray.testing.assert_equal(result_image.data_flat, expected_image.data_flat)
 

tests/unit/tools/simulate/test_generate_label_image.py

@@ -60,8 +60,7 @@ def test_render(generate) -> None:
     generate._image_height = 2
     generate._image_width = 2
     image = generate.render()
-    assert image.n_channels == 3
-    assert image.dimensions == (2, 2)
+    assert image.sizes == {"x": 2, "y": 2, "c": 3}
     assert image.channel_names == ["synthetic_0", "synthetic_1", "synthetic_2"]