Avoid using qt in tests

pyproject.toml

@@ -40,12 +40,6 @@ napari-save-transformed = "napari_save_transformed:napari.yaml"
 [tool.hatch.version]
 source = "vcs"
 
-[tool.hatch.envs.hatch-test]
-extra-dependencies = [
-  "pytest-qt",
-  "pyqt5",
-]
-
 [tool.hatch.envs.types]
 extra-dependencies = [
   "mypy>=1.0.0",

src/napari_save_transformed/__init__.py

@@ -43,7 +43,11 @@ def transform_arrays(arrays, affines):
     translation = Affine(translate=-min_corner)
     for arr, aff in zip(arrays, affines):
         # Apply the transformation
-        output = affine_transform(arr, translation.compose(aff).inverse, output_shape=output_shape)
+        output = affine_transform(
+            input=arr,
+            matrix=translation.compose(aff).inverse,
+            output_shape=output_shape,
+        )
         outputs.append(output)
 
     return outputs, output_shape

tests/test_napari_save_transformed.py

@@ -1,17 +1,18 @@
 import numpy as np
+from napari.layers import Image
 
 from napari_save_transformed import write_transformed_layers
 
 
-def test_write_transformed_layers(make_napari_viewer_proxy, tmp_path):
-    viewer = make_napari_viewer_proxy()
+def test_write_transformed_layers(tmp_path):
+    layers = []
     shape = (100, 200)
     image0 = np.ones(shape=shape)
-    viewer.add_image(image0)
+    layers.append(Image(image0))
     image1 = image0.copy()
-    viewer.add_image(image1, affine=[[1, 0, 30], [0, 1, 10], [0, 0, 1]])
+    layers.append(Image(image1, affine=[[1, 0, 30], [0, 1, 10], [0, 0, 1]]))
     out_path = tmp_path / "output.tif"
-    layer_data = [layer.as_layer_data_tuple() for layer in viewer.layers]
+    layer_data = [layer.as_layer_data_tuple() for layer in layers]
     write_transformed_layers(path=out_path, layer_data=layer_data)
 
     assert out_path.exists()