Add czi tests

pytools/utils/OMEInfo.py

@@ -30,8 +30,8 @@ def number_of_images(self) -> int:
         return len(self._root_element.findall("OME:Image", self._ome_ns))
 
     def image_names(self) -> Iterable[str]:
-        for e in self._root_element.iterfind("OME:Image", self._ome_ns):
-            yield e.attrib["Name"]
+        for counter, e in enumerate(self._root_element.iterfind("OME:Image", self._ome_ns)):
+            yield e.attrib["Name"] or f"Scene #{counter}"
 
     def channel_names(self, image_index) -> Iterable[str]:
         el = self._image_element(image_index).iterfind("OME:Pixels/OME:Channel", self._ome_ns)

test/test_HedwigZarrImage.py

@@ -15,15 +15,19 @@
 import pytest
 import shutil
 from pytools.HedwigZarrImages import HedwigZarrImages
+from pytools.HedwigZarrImage import HedwigZarrImage
 
 
 @pytest.mark.parametrize(
     "zarr_name, image_ext, array_shape, dims, shader_type, ngff_dims, shader_params",
     [("OM_P1_S1_ScanOnly_1k.zarr", "png", (1, 3, 1, 1024, 521), "XYC", "MultiChannel", "TCZYX", {})],
 )
-def test_HedwigZarrImage_info(
+def test_HedwigZarrImage_info_bad_ome(
     data_path, zarr_name, image_ext, array_shape, dims, shader_type, ngff_dims, shader_params, tmp_path
 ):
+    """
+    Testcase assumes that OME directory can be missing.
+    """
     # Remove OME directory from the .zarr file
     shutil.copytree(data_path / zarr_name, tmp_path / zarr_name)
     shutil.rmtree(tmp_path / zarr_name / "OME")
@@ -39,3 +43,87 @@ def test_HedwigZarrImage_info(
         assert shader_type == z_img.shader_type
         assert ngff_dims == z_img._ome_ngff_multiscale_dims()
         assert shader_params == z_img.neuroglancer_shader_parameters()
+
+
+@pytest.mark.parametrize(
+    "zarr_name, attrs",
+    [
+        (
+            "KC_M3_S2_ReducedImageSubset2.zarr",
+            [
+                ("czi", (1, 2, 1, 3102, 206), "XYC", "MultiChannel", "TCZYX", {"channelArray": 2}),
+                ("label", (1, 3, 1, 758, 1588), "XYC", "RGB", "TCZYX", {}),
+                ("macro", (1, 3, 1, 685, 567), "XYC", "RGB", "TCZYX", {}),
+            ],
+        )
+    ],
+)
+def test_HedwigZarrImage_info_for_czi(data_path, zarr_name, attrs):
+    """
+    Tests ZarrImages attributes generated from valid .czi files
+    """
+    zi = HedwigZarrImages(data_path / zarr_name)
+    assert zi.ome_xml_path is not None
+    image_names = list(zi.get_series_keys())
+    assert len(image_names) == 3
+    assert all(image_names)
+
+    for (k, z_img), attr in zip(zi.series(), attrs):
+        image_ext, array_shape, dims, shader_type, ngff_dims, shader_params = attr
+        # assert image_ext in k
+        assert array_shape == z_img.shape
+        assert dims == z_img.dims
+        assert shader_type == z_img.shader_type
+        assert ngff_dims == z_img._ome_ngff_multiscale_dims()
+        for param_key in shader_params:
+            shader_params[param_key] == len(z_img.neuroglancer_shader_parameters()[param_key])
+
+
+@pytest.mark.parametrize("targetx, targety", [(300, 300), (600, 600), (1024, 1024)])
+def test_hedwigimage_extract_2d(data_path, targetx, targety):
+    """
+    Tests extract_2d image extraction method for HedwigZarrImage
+    Asserts largest dimension matches with the target size of the dimension
+    """
+    zarr_name = "KC_M3_S2_ReducedImageSubset2.zarr"
+    zi = HedwigZarrImages(data_path / zarr_name)
+    for k, z_img in zi.series():
+        sitk_img = z_img.extract_2d(targetx, targety)
+        x, y = sitk_img.GetSize()
+        shape = dict(zip(z_img._ome_ngff_multiscale_dims(), z_img.shape))
+        actualx, actualy = shape["X"], shape["Y"]
+        assert x == targetx if actualx > actualy else y == targety
+
+
+def test_hedwigimage_extract_2d_invalid_shapes(data_path, monkeypatch):
+    """
+    Asserts extract_2d does not work with zarr image having dimensions:
+        time > 1
+        z-axis > 1
+    """
+    zarr_name = "KC_M3_S2_ReducedImageSubset2.zarr"
+    zi = HedwigZarrImages(data_path / zarr_name)
+
+    @property
+    def _mock_shape(obj):
+        return (2, 3, 1, 100, 100)
+
+    monkeypatch.setattr(HedwigZarrImage, "shape", _mock_shape)
+
+    z_img = zi[list(zi.get_series_keys())[0]]
+    assert z_img.shape[0] == 2
+    with pytest.raises(ValueError) as execinfo:
+        z_img.extract_2d(300, 300)
+    assert "Time dimension" in str(execinfo.value)
+
+    @property
+    def _mock_shape(obj):
+        return (1, 3, 3, 100, 100)
+
+    monkeypatch.setattr(HedwigZarrImage, "shape", _mock_shape)
+
+    z_img = zi[list(zi.get_series_keys())[0]]
+    assert z_img.shape[2] == 3
+    with pytest.raises(ValueError) as execinfo:
+        z_img.extract_2d(300, 300)
+    assert "Z dimension" in str(execinfo.value)

test/test_omeinfo.py

@@ -0,0 +1,32 @@
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0.txt
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+from pytools.HedwigZarrImages import HedwigZarrImages
+
+
+def test_ome_info(data_path):
+    """
+    Tests attributes of valid zarr image OMEInfo object
+    """
+    zarr_name = "KC_M3_S2_ReducedImageSubset2.zarr"
+    zi = HedwigZarrImages(data_path / zarr_name)
+    assert zi.ome_xml_path is not None
+    assert zi.ome_info is not None
+    ome = zi.ome_info
+
+    assert ome.number_of_images() == 3
+    # assert all(list(ome.image_names()))
+    assert len(list(ome.channel_names(0))) == 2
+    assert len(list(ome.channel_names(1))) == 0
+    assert len(list(ome.channel_names(2))) == 0