Cleaned test_xarray and added aoi, large_aoi to init

src/coincident/io/xarray.py

@@ -37,7 +37,7 @@ def to_dataset(
     bands: list[str] | None = None,
     aoi: gpd.GeoDataFrame | None = None,
     mask: bool = False,
-    **kwargs: dict[str, Any],
+    **kwargs: Any,
 ) -> xr.DataArray:
     """
     Convert a GeoDataFrame to an xarray DataArray using odc.stac

tests/__init__.py

@@ -1,5 +1,22 @@
 from __future__ import annotations
 
+import geopandas as gpd
+import pytest
+
 # import os
 # if not os.environ.get('MAXAR_API_KEY'):
 #    os.environ['MAXAR_API_KEY'] = 'fake-test-key'
+
+
+@pytest.fixture
+def aoi():
+    # 11 vertices, 1,361km^2
+    aoi_url = "https://raw.githubusercontent.com/SlideRuleEarth/sliderule-python/main/data/grandmesa.geojson"
+    return gpd.read_file(aoi_url)
+
+
+@pytest.fixture
+def large_aoi():
+    # 260 vertices, large area 269,590 km^2
+    aoi_url = "https://raw.githubusercontent.com/unitedstates/districts/refs/heads/gh-pages/states/CO/shape.geojson"
+    return gpd.read_file(aoi_url)

tests/test_search.py

@@ -1,3 +1,7 @@
+# ruff: noqa: F401
+# ruff: noqa: F811
+# F401 for ruff deeming 'aoi' and 'large_aoi' being unused imports
+# F811 for ruff deeming 'aoi' and 'large_aoi' variables being undefined
 from __future__ import annotations
 
 import typing
@@ -7,12 +11,13 @@
 from geopandas.testing import assert_geodataframe_equal
 
 import coincident
+from tests import aoi, large_aoi  # Importing the fixture from __init__.py
 
 # Decorate tests requiring internet (slow & flaky)
 network = pytest.mark.network
 
 try:
-    import maxar_platform.discovery  # noqa: F401
+    import maxar_platform.discovery
 
     not_authenticated = False
 except:  # noqa: E722
@@ -22,20 +27,6 @@
 )
 
 
-@pytest.fixture
-def aoi():
-    # 11 vertices, 1,361km^2
-    aoi_url = "https://raw.githubusercontent.com/SlideRuleEarth/sliderule-python/main/data/grandmesa.geojson"
-    return gpd.read_file(aoi_url)
-
-
-@pytest.fixture
-def large_aoi():
-    # 260 vertices, large area 269,590 km^2
-    aoi_url = "https://raw.githubusercontent.com/unitedstates/districts/refs/heads/gh-pages/states/CO/shape.geojson"
-    return gpd.read_file(aoi_url)
-
-
 @typing.no_type_check
 def test_no_dataset_specified():
     with pytest.raises(

tests/test_xarray.py

@@ -1,84 +1,74 @@
+# ruff: noqa: F401
+# ruff: noqa: F811
+# F401 for ruff deeming 'aoi' being unused import
+# F811 for ruff deeming 'aoi' variable being undefined
 from __future__ import annotations
 
+import matplotlib as mpl  # because ruff
 import pytest
 import xarray as xr
 
 import coincident
 from coincident.io.xarray import plot_esa_worldcover, to_dataset
+from tests import aoi  # Importing the fixture from __init__.py
 
-# These tests are based on the workflow from https://coincident.readthedocs.io/en/latest/examples/contextual_data.html
-# I couldn't think of a way to generalized these tests since the
-# xarray funcs are pretty tailored to COP30 and ESA WC
+# Decorate tests requiring internet (slow & flaky)
+network = pytest.mark.network
 
-# mypy doesn't like the resolution argument in to_dataset
-# Argument "resolution" to "to_dataset" has incompatible type "float"; expected "dict[str, Any]"  [arg-type]
 
-@pytest.fixture
-def search_aoi():
-    """Fixture to load a simplified AOI from realistic lidar data."""
-    workunit = "CO_WestCentral_2019"
-    df_wesm = coincident.search.wesm.read_wesm_csv()
-    gf_lidar = coincident.search.wesm.load_by_fid(
-        df_wesm[df_wesm.workunit == workunit].index
-    )
-    return gf_lidar.simplify(0.01)
-
-
-@pytest.mark.network
-def test_to_dataset_with_cop30(search_aoi):
+@network
+def test_to_dataset_with_cop30(aoi):
     """Test `to_dataset` functionality with COP30 dataset."""
     gf_cop30 = coincident.search.search(
         dataset="cop30",
-        intersects=search_aoi,
+        intersects=aoi,
     )
     ds = to_dataset(
         gf_cop30,
-        aoi=search_aoi,
-        resolution=0.00081,  # ~90m
-        mask=True,
+        aoi=aoi,
+        resolution=0.1,  # ~1km
     ).compute()
     assert isinstance(ds, xr.Dataset), "Expected output to be an xarray Dataset."
     assert "data" in ds.data_vars, "Expected 'data' variable in the Dataset."
 
 
-@pytest.mark.network
-def test_to_dataset_with_worldcover(search_aoi):
+@network
+def test_to_dataset_with_worldcover(aoi):
     """Test `to_dataset` functionality with WorldCover dataset."""
     gf_wc = coincident.search.search(
         dataset="worldcover",
-        intersects=search_aoi,
+        intersects=aoi,
         datetime=["2020"],
     )
     ds = to_dataset(
         gf_wc,
         bands=["map"],
-        aoi=search_aoi,
-        resolution=0.00081,  # ~90m
-        mask=True,
+        aoi=aoi,
+        resolution=0.1,  # ~1km
     ).compute()
-    ds = ds.rename(map="landcover")
     assert isinstance(ds, xr.Dataset), "Expected output to be an xarray Dataset."
-    assert "landcover" in ds.data_vars, "Expected 'landcover' variable in the Dataset."
+    assert "map" in ds.data_vars, "Expected 'map' variable in the Dataset."
 
 
-# Tests for `plot_esa_worldcover`
-@pytest.mark.network
-def test_plot_esa_worldcover_valid(search_aoi):
+@network
+def test_plot_esa_worldcover_valid(aoi):
     """Test `plot_esa_worldcover` with valid WorldCover dataset."""
     gf_wc = coincident.search.search(
         dataset="worldcover",
-        intersects=search_aoi,
-        datetime=["2020"],
+        intersects=aoi,
+        datetime=["2021"],
     )
     ds = to_dataset(
         gf_wc,
         bands=["map"],
-        aoi=search_aoi,
-        resolution=0.00081,  # ~90m
-        mask=True,
+        aoi=aoi,
+        resolution=0.1,  # ~1km
     ).compute()
     ds = ds.rename(map="landcover")
     ax = plot_esa_worldcover(ds)
     assert ax is not None, "Expected a valid Matplotlib Axes object."
-    assert len(ax.images) > 0, "Expected at least one image in the plot."
-    ax.set_title("ESA WorldCover")
+    # https://matplotlib.org/stable/users/prev_whats_new/whats_new_3.4.0.html
+    # https://github.com/matplotlib/matplotlib/blob/main/lib/matplotlib/tests/test_contour.py#L146
+    assert any(
+        isinstance(c, mpl.collections.QuadMesh) for c in ax.get_children()
+    ), "Expected at least one pcolormesh object in the plot."