🔧 mypy type check wsicore

.github/workflows/mypy-type-check.yml

@@ -50,4 +50,7 @@ jobs:
           tiatoolbox/models/__init__.py \
           tiatoolbox/models/models_abc.py \
           tiatoolbox/models/architecture/__init__.py \
-          tiatoolbox/models/architecture/utils.py
+          tiatoolbox/models/architecture/utils.py \
+          tiatoolbox/wsicore/__init__.py \
+          tiatoolbox/wsicore/wsimeta.py \
+          tiatoolbox/wsicore/metadata/

tests/test_meta_ngff_dataclasses.py

@@ -29,6 +29,21 @@ def test_multiscales_defaults() -> None:
         """Test :class:`ngff.Multiscales` init with default args."""
         ngff.Multiscales()
 
+    @staticmethod
+    def test_multiscales_iter() -> None:
+        """Test :class:`ngff.Multiscales` init."""
+        multiscales = ngff.Multiscales()
+        iter_values = list(iter(multiscales))
+
+        # Check if all attributes are present in the yielded values
+        assert multiscales.axes in iter_values
+        assert multiscales.datasets in iter_values
+        assert multiscales.version in iter_values
+
+        # Check the order of yielded values matches __dict__ order
+        expected = list(multiscales.__dict__.values())
+        assert iter_values == expected
+
     @staticmethod
     def test_omero_defaults() -> None:
         """Test :class:`ngff.Omero` init with default args."""

tests/test_wsireader.py

@@ -16,6 +16,7 @@
 import glymur
 import numpy as np
 import pytest
+import tifffile
 import zarr
 from click.testing import CliRunner
 from packaging.version import Version
@@ -770,6 +771,17 @@ def test_is_tiled_tiff(source_image: Path) -> None:
     source_image.with_suffix(".tiff").replace(source_image)
 
 
+def test_is_not_tiled_tiff(tmp_samples_path: Path) -> None:
+    """Test if source_image is not a tiled tiff."""
+    temp_tiff_path = tmp_samples_path / "not_tiled.tiff"
+    images = [np.zeros(shape=(4, 4)) for _ in range(3)]
+    # Write multi-page TIFF with all pages not tiled
+    with tifffile.TiffWriter(temp_tiff_path) as tif:
+        for image in images:
+            tif.write(image, compression=None, tile=None)
+    assert wsireader.is_tiled_tiff(temp_tiff_path) is False
+
+
 def test_read_rect_openslide_levels(sample_ndpi: Path) -> None:
     """Test openslide read rect with resolution in levels.
 

tiatoolbox/wsicore/metadata/ngff.py

@@ -9,13 +9,14 @@
 
 from __future__ import annotations
 
-from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Literal
 
-from tiatoolbox import __version__ as tiatoolbox_version
-
 if TYPE_CHECKING:  # pragma: no cover
-    from numbers import Number
+    from collections.abc import Iterator
+
+from dataclasses import dataclass, field
+
+from tiatoolbox import __version__ as tiatoolbox_version
 
 SpaceUnits = Literal[
     "angstrom",
@@ -169,6 +170,15 @@ class Multiscales:
     datasets: list[Dataset] = field(default_factory=lambda: [Dataset()])
     version: str = "0.4"
 
+    def __iter__(self: Multiscales) -> Iterator:
+        """Iterate over the values of the attributes in the `Multiscales` object.
+
+        Yields:
+            Iterator: An iterator
+
+        """
+        yield from self.__dict__.values()
+
 
 @dataclass
 class Window:
@@ -186,10 +196,10 @@ class Window:
 
     """
 
-    end: Number = 255
-    max: Number = 255
-    min: Number = 0
-    start: Number = 0
+    end: int = 255
+    max: int = 255
+    min: int = 0
+    start: int = 0
 
 
 @dataclass

tiatoolbox/wsicore/wsimeta.py

@@ -11,7 +11,7 @@
 
 from numbers import Number
 from pathlib import Path
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, cast
 
 import numpy as np
 
@@ -121,7 +121,7 @@ def __init__(
         self.level_downsamples = (
             [float(x) for x in level_downsamples]
             if level_downsamples is not None
-            else None
+            else [1.0]
         )
         self.level_count = (
             int(level_count) if level_count is not None else len(self.level_dimensions)
@@ -212,7 +212,9 @@ def level_downsample(
         ceil = int(np.ceil(level))
         floor_downsample = level_downsamples[floor]
         ceil_downsample = level_downsamples[ceil]
-        return np.interp(level, [floor, ceil], [floor_downsample, ceil_downsample])
+        return float(
+            np.interp(level, [floor, ceil], [floor_downsample, ceil_downsample])
+        )
 
     def relative_level_scales(
         self: WSIMeta,
@@ -260,20 +262,25 @@ def relative_level_scales(
             [0.125, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0, 32.0]
 
         """
+        base_scale: np.ndarray
+        resolution_array: np.ndarray
+        msg: str
+
         if units not in ("mpp", "power", "level", "baseline"):
             msg = "Invalid units"
             raise ValueError(msg)
 
         level_downsamples = self.level_downsamples
 
-        def np_pair(x: Number | np.array) -> np.ndarray:
+        def np_pair(x: Resolution) -> np.ndarray:
             """Ensure input x is a numpy array of length 2."""
             # If one number is given, the same value is used for x and y
             if isinstance(x, Number):
                 return np.array([x] * 2)
             return np.array(x)
 
         if units == "level":
+            resolution = cast("float", resolution)
             if resolution >= len(level_downsamples):
                 msg = (
                     f"Target scale level {resolution} > "
@@ -282,32 +289,37 @@ def np_pair(x: Number | np.array) -> np.ndarray:
                 raise ValueError(
                     msg,
                 )
-            base_scale, resolution = 1, self.level_downsample(resolution)
-
-        resolution = np_pair(resolution)
+            resolution_array = np.array(
+                [self.level_downsample(resolution)] * 2, dtype=float
+            )
+            base_scale = np.array([1.0, 1.0], dtype=float)
 
-        if units == "mpp":
+        elif units == "mpp":
             if self.mpp is None:
                 msg = "MPP is None. Cannot determine scale in terms of MPP."
                 raise ValueError(msg)
             base_scale = self.mpp
+            resolution_array = np_pair(resolution)
 
-        if units == "power":
+        elif units == "power":
             if self.objective_power is None:
                 msg = (
                     "Objective power is None. "
-                    "Cannot determine scale in terms of objective power.",
+                    "Cannot determine scale in terms of objective power."
                 )
                 raise ValueError(
                     msg,
                 )
-            base_scale, resolution = 1 / self.objective_power, 1 / resolution
+            base_scale = np.array([1 / self.objective_power] * 2, dtype=float)
+            resolution_array = 1.0 / np_pair(resolution)
 
-        if units == "baseline":
-            base_scale, resolution = 1, 1 / resolution
+        else:  # units == "baseline"
+            base_scale = np.array([1.0, 1.0], dtype=float)
+            resolution_array = 1.0 / np_pair(resolution)
 
         return [
-            (base_scale * downsample) / resolution for downsample in level_downsamples
+            (base_scale * downsample) / resolution_array
+            for downsample in level_downsamples
         ]
 
     def as_dict(self: WSIMeta) -> dict: