tests for seqfish

tests/test_seqfish.py

@@ -0,0 +1,27 @@
+import math
+from pathlib import Path
+
+import pytest
+
+from spatialdata_io.readers.seqfish import seqfish
+from tests._utils import skip_if_below_python_version
+
+
+# See https://github.com/scverse/spatialdata-io/blob/main/.github/workflows/prepare_test_data.yaml for instructions on
+# how to download and place the data on disk
+@skip_if_below_python_version()
+@pytest.mark.parametrize("dataset,expected", [("instrument 2 official", "{'y': (0, 108), 'x': (0, 108)}")])
+@pytest.mark.parametrize("rois", [[1], None])
+@pytest.mark.parametrize("cells_as_circles", [False, True])
+def test_example_data(dataset: str, expected: str, rois: list[int] | None, cells_as_circles: bool) -> None:
+    f = Path("./data") / dataset
+    assert f.is_dir()
+    sdata = seqfish(f, cells_as_circles=cells_as_circles, rois=rois)
+    from spatialdata import get_extent
+
+    extent = get_extent(sdata, exact=False)
+    extent = {ax: (math.floor(extent[ax][0]), math.ceil(extent[ax][1])) for ax in extent}
+    if cells_as_circles:
+        # manual correction required to take into account for the circle radii
+        expected = "{'y': (-2, 109), 'x': (-2, 109)}"
+    assert str(extent) == expected

tests/test_xenium.py

@@ -40,12 +40,8 @@ def test_roundtrip_with_data_limits() -> None:
     assert np.array_equal(cell_id_str, f0(*f1(cell_id_str)))
 
 
-# The datasets should be downloaded from
-# https://www.10xgenomics.com/support/software/xenium-onboard-analysis/latest/resources/xenium-example-data#test-data
-# and placed in the "data" directory; if you run the tests locally you may need to create a symlink in "tests/data"
-# pointing to "data".
-# The GitHub workflow "prepare_test_data.yaml" takes care of downloading the datasets and uploading an artifact for the
-# tests to use
+# See https://github.com/scverse/spatialdata-io/blob/main/.github/workflows/prepare_test_data.yaml for instructions on
+# how to download and place the data on disk
 @skip_if_below_python_version()
 @pytest.mark.parametrize(
     "dataset,expected",