Add tests for Xarray io functions

pyproject.toml

@@ -31,39 +31,37 @@ classifiers = [
 dynamic = ["version"]
 
 dependencies = [
-  #"aiohttp>=3.10.6,<4",
   "cloudpathlib[s3]>=0.20.0,<0.21",
-  #"fsspec>=2024.9.0,<2025",
   "geopandas>=1.0.1,<2",
   "maxar-platform>=1.0.2,<2",
+  "odc-stac>=0.3.10,<0.4",
   "planetary-computer>=1.0.0,<2",
   "pyarrow>=18.0.0,<19",
   "pystac-client>=0.8.3,<0.9",
   "requests>=2.32.3,<3",
   "rioxarray>=0.17.0,<0.18",
   "stac-asset>=0.4.3,<0.5",
   "stac-geoparquet>=0.6.0,<0.7",
-  "odc-stac>=0.3.10,<0.4",
 ]
 
 [project.optional-dependencies]
 dev = [
   "ipykernel>=6.29.5,<7",
+  "matplotlib>=3.9.4,<4",
   "mypy>=1.11.2,<2",
   "pre-commit>=3.8.0,<4",
   "pylint>=3.3.1,<4",
   "pytest >=6",
   "pytest-cov >=3",
+  "sliderule>=4.7.1,<5",
 ]
 docs = [
   "folium", # comes w/ geopandas on conda-forge but not pypi
-  #"furo>=2023.08.17",
   "mapclassify",
   "matplotlib",
   "myst-nb",
   "myst_parser>=0.13",
   "pydata-sphinx-theme>=0.16.0,<0.17",
-  #"rpds-py>=0.21.0,<0.22",
   "sphinx>=7.0",
   "sphinx_autodoc_typehints",
   "sphinx_copybutton",
@@ -211,37 +209,36 @@ docs = { features = ["docs"], solve-group = "default" }
 # If a package is listed in project.dependencies but not repeated here, it is installed from pypi
 [tool.pixi.dependencies]
 python = "<3.13" # https://github.com/stac-utils/stac-geoparquet/issues/81
-#aiohttp = "*"
-#fsspec = "*"
 geopandas = "*"
+odc-stac = "*"
 planetary-computer = "*"
 pystac-client = "*"
 requests = "*"
 rioxarray = "*"
 # stac-asset = "*" # not on conda-forge
-#s3fs = "*"
 stac-geoparquet = "*"
 pyarrow = "*"
+# Testing additional dependencies (not in pypi list
 jsonschema = ">=4.23.0,<5"
 libgdal-arrow-parquet = ">=3.10.0,<4"
-odc-stac = "*"
-#nbconvert = ">=7.16.4,<8"
-#cloudpathlib-s3 = ">=0.20.0,<0.21"
-#matplotlib-base = ">=3.9.2,<4"
-#sliderule = ">=4.7.1,<5"
+
 
 [tool.pixi.feature.dev.dependencies]
 # NOTE: ipykernel to run notebooks in vscode
 ipykernel = ">=6.29.5,<7"
+matplotlib = "*"
+mypy = "*"
 # Bug if=*? Because you require pre-commit>=3.8.0,<4 and pre-commit==4.0.0, we can conclude that your requirements are unsatisfiable.
 pre-commit = "<4"
 pylint = "*"
 pytest = "*"
-mypy = "*"
-# Testing additional dependencies
+sliderule = "*"
+
+# NOTE: test new dependencies locally by adding below
 #rich = ">=13.8.1,<14" # Optional. convenient for rich.print(dataset)
 #xvec = ">=0.3.0,<0.4"
-sliderule = ">=4.7.1,<5"
+#sliderule = ">=4.7.1,<5"
+#matplotlib = ">=3.9.4,<4"
 
 [tool.pixi.pypi-dependencies]
 coincident = { path = ".", editable = false }

src/coincident/datasets/planetary_computer.py

@@ -19,15 +19,15 @@
 
 @dataclass
 class COP30(Dataset):
-    """Essential metadata for Copernicus DEM"""
+    """Essential metadata and data access for Copernicus DEM"""
 
     alias: str = "cop30"
     has_stac_api: bool = True
     collections: list[str] = field(default_factory=lambda: ["cop-dem-glo-30"])
     search: str = STACAPI
-    start: str | None = None  # NOTE: has 'representative' datetime of 2021-04-22
+    start: str | None = None  # Copernicus DEM has 'representative' datetime: 2021-04-22
     end: str | None = None
-    type: str = "sar"
+    type: str = "dem"
     provider: str = "microsoft"
 
 

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 +0,0 @@
-from __future__ import annotations
-
-# import os
-# if not os.environ.get('MAXAR_API_KEY'):
-#    os.environ['MAXAR_API_KEY'] = 'fake-test-key'

tests/conftest.py

@@ -0,0 +1,23 @@
+# ruff: noqa: ARG001
+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(scope="package")
+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(scope="package"):
+    # 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

@@ -18,24 +18,10 @@
 except:  # noqa: E722
     not_authenticated = True
 maxar_authenticated = pytest.mark.skipif(
-    not_authenticated, reason="tests for linux only"
+    not_authenticated, reason="Not authenticated with Maxar API"
 )
 
 
-@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

@@ -0,0 +1,70 @@
+from __future__ import annotations
+
+import pytest
+import xarray as xr
+from matplotlib.collections import QuadMesh
+
+import coincident
+from coincident.io.xarray import plot_esa_worldcover, to_dataset
+
+# Decorate tests requiring internet (slow & flaky)
+network = pytest.mark.network
+
+
+@network
+def test_to_dataset_with_cop30(aoi):
+    """Test `to_dataset` functionality with COP30 dataset."""
+    gf_cop30 = coincident.search.search(
+        dataset="cop30",
+        intersects=aoi,
+    )
+    ds = to_dataset(
+        gf_cop30,
+        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."
+
+
+@network
+def test_to_dataset_with_worldcover(aoi):
+    """Test `to_dataset` functionality with WorldCover dataset."""
+    gf_wc = coincident.search.search(
+        dataset="worldcover",
+        intersects=aoi,
+        datetime=["2020"],
+    )
+    ds = to_dataset(
+        gf_wc,
+        bands=["map"],
+        aoi=aoi,
+        resolution=0.1,  # ~1km
+    ).compute()
+    assert isinstance(ds, xr.Dataset), "Expected output to be an xarray Dataset."
+    assert "map" in ds.data_vars, "Expected 'map' variable in the Dataset."
+
+
+@network
+def test_plot_esa_worldcover_valid(aoi):
+    """Test `plot_esa_worldcover` with valid WorldCover dataset."""
+
+    gf_wc = coincident.search.search(
+        dataset="worldcover",
+        intersects=aoi,
+        datetime=["2021"],
+    )
+    ds = to_dataset(
+        gf_wc,
+        bands=["map"],
+        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."
+    # 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, QuadMesh) for c in ax.get_children()
+    ), "Expected at least one pcolormesh object in the plot."