All test_index_cloning tests fail with Antimeridian 0.4.5

[pjonsson]

Antimeridian 0.4.5 started erroring if the geometry was unfixable, and all test_index_cloning tests fail for that reason. Here's the output from one of the tests:

cfg_env_pair = (<datacube.cfg.api.ODCEnvironment object at 0x70a4bb4c4cb0>, <datacube.cfg.api.ODCEnvironment object at 0x70a4bb4c4b90>)
uninitialised_postgres_db_pair = (PostgisDb<engine=Engine(postgresql://opendatacube:***@postgres:35432/pgisintegration)>, PostgresDb<engine=Engine(postgresql+psycopg://opendatacube:***@postgres:35432/pgintegration)>)
extended_eo3_metadata_type_doc = {'dataset': {'creation_dt': ['properties', 'odc:processing_datetime'], 'format': ['properties', 'odc:file_format'], 'g...tial', 'projection'], 'id': ['id'], ...}, 'description': 'EO3 for ARD Landsat Collection 3', 'name': 'eo3_landsat_ard'}
base_eo3_product_doc = {'description': 'Geoscience Australia Landsat Water Observations Collection 3', 'license': 'CC-BY-4.0', 'measurements'...a': {'product': {'name': 'ga_ls_wo_3'}, 'properties': {'odc:file_format': 'GeoTIFF', 'odc:product_family': 'wo'}}, ...}
extended_eo3_product_doc = {'description': 'Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready D...8c_ard_3'}, 'properties': {'eo:platform': 'landsat-8', 'odc:producer': 'ga.gov.au', 'odc:product_family': 'ard'}}, ...}
africa_s2_product_doc = {'description': 'Sentinel-2a and Sentinel-2b imagery, processed to Level 2A (Surface Reflectance) and converted to Clo...t16', 'name': 'B06', 'nodata': 0, ...}, ...], 'metadata': {'product': {'name': 's2_l2a'}}, 'metadata_type': 'eo3', ...}
eo3_ls8_dataset_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'accessories': {'checksum:sha1': {'path': 'ga_ls8c_ard_3-0-0_...://dea-public-data/baseline/ga_ls8c_ard_3/090/086/2016/05/12/ga_ls8c_ard_3-0-0_090086_2016-05-12_final.stac-item.json')
eo3_ls8_dataset2_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'accessories': {'checksum:sha1': {'path': 'ga_ls8c_ard_3-0-0_...://dea-public-data/baseline/ga_ls8c_ard_3/090/086/2016/05/28/ga_ls8c_ard_3-0-0_090086_2016-05-28_final.stac-item.json')
eo3_ls8_dataset3_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'crs': 'epsg:32653', 'geometry': {'coordinates': [[[388119.0,...://dea-public-data/baseline/ga_ls8c_ard_3/101/077/2013/04/04/ga_ls8c_ard_3-0-0_101077_2013-04-04_final.stac-item.json')
eo3_ls8_dataset4_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'crs': 'epsg:32653', 'geometry': {'coordinates': [[[476439.0,...://dea-public-data/baseline/ga_ls8c_ard_3/101/077/2013/07/21/ga_ls8c_ard_3-0-0_101077_2013-07-21_final.stac-item.json')
eo3_wo_dataset_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'accessories': {'checksum:sha1': {'path': 'ga_ls_wo_3_090086_...s3://dea-public-data/derivative/ga_ls_wo_3/1-6-0/090/086/2016/05/12/ga_ls_wo_3_090086_2016-05-12_final.stac-item.json')
eo3_africa_dataset_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'accessories': {'info': {'path': 'https://roda.sentinel-hub.c... 's3://deafrica-sentinel-2/sentinel-s2-l2a-cogs/37/M/CQ/2022/8/S2A_37MCQ_20220808_0_L2A/S2A_37MCQ_20220808_0_L2A.json')
eo3_africa_dataset2_doc = ({'$schema': 'https://schemas.opendatacube.org/dataset', 'accessories': {'info': {'path': 'https://roda.sentinel-hub.c... 's3://deafrica-sentinel-2/sentinel-s2-l2a-cogs/39/M/XR/2020/9/S2A_39MXR_20200909_0_L2A/S2A_39MXR_20200909_0_L2A.json')

    @pytest.fixture
    def index_pair_populated_empty(
        cfg_env_pair: tuple[ODCEnvironment, ...],
        uninitialised_postgres_db_pair,
        extended_eo3_metadata_type_doc,
        base_eo3_product_doc,
        extended_eo3_product_doc,
        africa_s2_product_doc,
        eo3_ls8_dataset_doc,
        eo3_ls8_dataset2_doc,
        eo3_ls8_dataset3_doc,
        eo3_ls8_dataset4_doc,
        eo3_wo_dataset_doc,
        eo3_africa_dataset_doc,
        eo3_africa_dataset2_doc,
    ) -> Generator[tuple]:
        populated_cfg, empty_cfg = cfg_env_pair
        populated_idx = index_connect(populated_cfg, validate_connection=False)
        empty_idx = index_connect(empty_cfg, validate_connection=False)
        populated_idx.init_db()
        empty_idx.init_db(with_default_types=False)
        assert list(empty_idx.products.get_all()) == []
        assert list(populated_idx.products.get_all()) == []
        # Populate the populated index
        populated_idx.metadata_types.add(
            populated_idx.metadata_types.from_doc(extended_eo3_metadata_type_doc)
        )
        for prod_doc in (
            base_eo3_product_doc,
            extended_eo3_product_doc,
            africa_s2_product_doc,
        ):
            populated_idx.products.add_document(prod_doc)
        for ds_doc, ds_path in (
            eo3_ls8_dataset_doc,
            eo3_ls8_dataset2_doc,
            eo3_ls8_dataset3_doc,
            eo3_ls8_dataset4_doc,
            eo3_wo_dataset_doc,
            eo3_africa_dataset_doc,
            eo3_africa_dataset2_doc,
        ):
>           doc_to_ds(populated_idx, ds_doc["product"]["name"], ds_doc, ds_path)

integration_tests/conftest.py:715:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
integration_tests/conftest.py:310: in doc_to_ds
    index.datasets.add(ds, with_lineage=index.supports_lineage)
datacube/index/postgis/_datasets.py:192: in add
    transaction.update_spindex(dsids=[dataset.id])
datacube/drivers/postgis/_api.py:982: in update_spindex
    self.insert_dataset_spatial(dsid, crs, geom)
datacube/drivers/postgis/_api.py:377: in insert_dataset_spatial
    values = generate_dataset_spatial_values(dataset_id, crs, extent)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
datacube/drivers/postgis/_spatial.py:269: in generate_dataset_spatial_values
    extent = sanitise_extent(extent, crs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
datacube/drivers/postgis/_spatial.py:258: in sanitise_extent
    return Geom(fix_shape(prelim.geom), crs=crs)
                ^^^^^^^^^^^^^^^^^^^^^^
.venv/lib/python3.12/site-packages/antimeridian/_implementation.py:217: in fix_shape
    fix_polygon(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

polygon = <POLYGON ((52.89 -4.056, 52.89 -4.056, 52.89 -4.055, 52.89 -4.056))>

    def fix_polygon(
        polygon: Polygon,
        *,
        force_north_pole: bool = False,
        force_south_pole: bool = False,
        fix_winding: bool = True,
        great_circle: bool = True,
    ) -> Union[Polygon, MultiPolygon]:
        """Fixes a [shapely.Polygon][].

        If the input polygon is wound clockwise, it will be fixed to be wound
        counterclockwise _unless_ `fix_winding` is `False` in which case it
        will be corrected by adding a counterclockwise polygon from (-180, -90) to
        (180, 90) as its exterior.

        In rare cases, the underlying algorithm might need a little help to fix the polygon.
        For example, a polygon that just barely crosses over a pole might have very
        few points at high latitudes, leading to ambiguous antimeridian crossing
        points and invalid geometries. We provide two flags, `force_north_pole`
        and `force_south_pole` for those cases. Most users can ignore these
        flags.

        If either `force_north_pole` or `force_south_pole` is `True`
        `fix_winding` is set to `False`

        Args:
            polygon: The input polygon
            force_north_pole: If the polygon crosses the antimeridian, force the
                joined segments to enclose the north pole.
            force_south_pole: If the polygon crosses the antimeridian, force the
                joined segments to enclose the south pole.
            fix_winding: If the polygon is wound clockwise, reverse its
                coordinates before applying the algorithm.
            great_circle: Compute meridian crossings on the sphere rather than
                using 2D geometry.

        Returns:
            The fixed polygon, either as a single polygon or a multi-polygon (if it
                was split)
        """
        if force_north_pole or force_south_pole:
            fix_winding = False
        polygons = fix_polygon_to_list(
            polygon,
            force_north_pole=force_north_pole,
            force_south_pole=force_south_pole,
            fix_winding=fix_winding,
            great_circle=great_circle,
        )
        if len(polygons) == 1:
            polygon = polygons[0]
            if shapely.is_ccw(polygon.exterior):
                return polygon
            else:
                pole_covering_polygon = Polygon(
                    [(-180, 90), (-180, -90), (180, -90), (180, 90)],
                    [polygon.exterior.coords],
                )
                if shapely.is_valid(pole_covering_polygon):
                    return pole_covering_polygon
                else:
>                   raise ValueError(
                        "Fixed polygon is invalid, check your input polygon for validity. "
                        "Reason your polygon is invalid: "
                        + shapely.is_valid_reason(polygon)
                    )
E                   ValueError: Fixed polygon is invalid, check your input polygon for validity. Reason your polygon is invalid: Too few points in geometry component[52.8896991867137 -4.05589014056015]

.venv/lib/python3.12/site-packages/antimeridian/_implementation.py:368: ValueError
___ ERROR at setup of test_index_clone_small_batch[datacube_env_name_pair3] ____

[SpacemanPaul]

The problem is that one of test datasets has a zero-area extent. It's a real dataset from DEAfrica.

I think we need to check for zero-area extents on indexing, although it's not 100% clear what we should do when we find one. I'm currently thinking:

1. Raise a warning.
2. For postgis driver: do not index the zero-area polygon in ANY spatial index.