removing None's when it shouldn't be allowed

uxarray/core/api.py

@@ -38,7 +38,7 @@
 def open_grid(
     grid_filename_or_obj: str | os.PathLike[Any] | dict | xr.Dataset,
     chunks=None,
-    use_dual: bool | None = False,
+    use_dual: bool = False,
     **kwargs: dict[str, Any],
 ):
     """Constructs and returns a ``Grid`` from a grid file.
@@ -371,7 +371,7 @@ def open_dataset(
     filename_or_obj: str | os.PathLike[Any] | xr.Dataset | None = None,
     chunks=None,
     chunk_grid: bool = True,
-    use_dual: bool | None = False,
+    use_dual: bool = False,
     grid_kwargs: dict[str, Any] | None = None,
     **kwargs: dict[str, Any],
 ) -> UxDataset:
@@ -501,7 +501,7 @@ def open_mfdataset(
     paths: str | os.PathLike,
     chunks=None,
     chunk_grid: bool = True,
-    use_dual: bool | None = False,
+    use_dual: bool = False,
     grid_kwargs: dict[str, Any] | None = None,
     **kwargs: dict[str, Any],
 ) -> UxDataset:

uxarray/core/dataarray.py

@@ -247,11 +247,11 @@ def data_mapping(self):
 
     def to_geodataframe(
         self,
-        periodic_elements: str | None = "exclude",
+        periodic_elements: str = "exclude",
         projection=None,
-        cache: bool | None = True,
-        override: bool | None = False,
-        engine: str | None = "spatialpandas",
+        cache: bool = True,
+        override: bool = False,
+        engine: str = "spatialpandas",
         project: bool = True,
     ):
         """Constructs a ``GeoDataFrame`` consisting of polygons representing
@@ -341,11 +341,11 @@ def to_geodataframe(
 
     def to_polycollection(
         self,
-        periodic_elements: Optional[str] = "exclude",
+        periodic_elements: str = "exclude",
         projection: Optional[ccrs.Projection] = None,
-        return_indices: Optional[bool] = False,
-        cache: Optional[bool] = True,
-        override: Optional[bool] = False,
+        return_indices: bool = False,
+        cache: bool = True,
+        override: bool = False,
         **kwargs,
     ):
         """Constructs a ``matplotlib.collections.PolyCollection``` consisting
@@ -661,7 +661,7 @@ def _binary_op(self, other, f, reflexive=False, **kw_super):
         return result
 
     def integrate(
-        self, quadrature_rule: str | None = "triangular", order: int | None = 4
+        self, quadrature_rule: str = "triangular", order: int = 4
     ) -> UxDataArray:
         """Computes the integral of a data variable.
 
@@ -2033,7 +2033,7 @@ def scalardotgradient(self, v: "UxDataArray", q: "UxDataArray") -> "UxDataArray"
         result = result.assign_attrs(attrs)
         return result
 
-    def difference(self, destination: str | None = "edge"):
+    def difference(self, destination: str = "edge"):
         """Computes the absolute difference of a data variable.
 
         The difference for a face-centered data variable can be computed on each edge using the ``edge_face_connectivity``,

uxarray/grid/grid.py

@@ -258,7 +258,7 @@ def __init__(
     subset = UncachedAccessor(GridSubsetAccessor)
 
     @classmethod
-    def from_dataset(cls, dataset, use_dual: bool | None = False, **kwargs):
+    def from_dataset(cls, dataset, use_dual: bool = False, **kwargs):
         """Constructs a ``Grid`` object from a dataset.
 
         Parameters
@@ -352,7 +352,7 @@ def from_dataset(cls, dataset, use_dual: bool | None = False, **kwargs):
     def from_file(
         cls,
         filename: str,
-        backend: str | None = "geopandas",
+        backend: str = "geopandas",
         **kwargs,
     ):
         """Constructs a ``Grid`` object from a using the read_file method with
@@ -472,7 +472,7 @@ def from_topology(
         node_lat: np.ndarray,
         face_node_connectivity: np.ndarray,
         fill_value: int | float | None = None,
-        start_index: int | None = 0,
+        start_index: int = 0,
         dims_dict: dict | None = None,
         **kwargs,
     ):
@@ -493,7 +493,7 @@ def from_topology(
             Face node connectivity, mapping each face to the nodes that surround them
         fill_value: int | float | None
             Value used for padding connectivity variables when the maximum number of elements in a row is less than the maximum.
-        start_index: int | None, default=0
+        start_index: int, default=0
             Start index (typically 0 or 1)
         dims_dict : dict | None
             Dictionary of dimension names mapped to the ugrid conventions (i.e. {"nVertices": "n_node})
@@ -589,7 +589,7 @@ def from_structured(
     def from_face_vertices(
         cls,
         face_vertices: list | tuple | np.ndarray,
-        latlon: bool | None = True,
+        latlon: bool = True,
     ):
         """Constructs a ``Grid`` object from user-defined face vertices.
 
@@ -1828,9 +1828,9 @@ def chunk(self, n_node="auto", n_edge="auto", n_face="auto"):
 
     def get_ball_tree(
         self,
-        coordinates: str | None = "face centers",
-        coordinate_system: str | None = "spherical",
-        distance_metric: str | None = "haversine",
+        coordinates: str = "face centers",
+        coordinate_system: str = "spherical",
+        distance_metric: str = "haversine",
         reconstruct: bool = False,
     ):
         """Get the BallTree data structure of this Grid that allows for nearest
@@ -1924,9 +1924,7 @@ def neighborhood(self, r: float = 1.0, on: str = "face centers") -> Neighborhood
         """
         return Neighborhood(self, r=r, on=on)
 
-    def _get_scipy_kd_tree(
-        self, coordinates: str | None = "face", reconstruct: bool = False
-    ):
+    def _get_scipy_kd_tree(self, coordinates: str = "face", reconstruct: bool = False):
         """
         Build or retrieve a KDTree for efficient nearest-neighbor searches on grid points.
 
@@ -1978,9 +1976,9 @@ def _get_scipy_kd_tree(
 
     def get_kd_tree(
         self,
-        coordinates: str | None = "face centers",
-        coordinate_system: str | None = "cartesian",
-        distance_metric: str | None = "minkowski",
+        coordinates: str = "face centers",
+        coordinate_system: str = "cartesian",
+        distance_metric: str = "minkowski",
         reconstruct: bool = False,
     ):
         """Get the KDTree data structure of this Grid that allows for nearest
@@ -2473,7 +2471,7 @@ def sphere_radius(self, radius: float) -> None:
 
         self._ds.attrs["sphere_radius"] = radius
 
-    def to_xarray(self, grid_format: str | None = "ugrid"):
+    def to_xarray(self, grid_format: str = "ugrid"):
         """Returns an ``xarray.Dataset`` with the variables stored under the
         ``Grid`` encoded in a specific grid format.
 
@@ -2520,13 +2518,13 @@ def to_xarray(self, grid_format: str | None = "ugrid"):
 
     def to_geodataframe(
         self,
-        periodic_elements: str | None = "exclude",
+        periodic_elements: str = "exclude",
         projection=None,
-        cache: bool | None = True,
-        override: bool | None = False,
-        engine: str | None = "spatialpandas",
-        return_non_nan_polygon_indices: bool | None = False,
-        exclude_nan_polygons: bool | None = True,
+        cache: bool = True,
+        override: bool = False,
+        engine: str = "spatialpandas",
+        return_non_nan_polygon_indices: bool = False,
+        exclude_nan_polygons: bool = True,
         project: bool = True,
     ):
         """Constructs a ``GeoDataFrame`` consisting of polygons representing
@@ -2637,12 +2635,12 @@ def to_geodataframe(
 
     def to_polycollection(
         self,
-        periodic_elements: Optional[str] = "exclude",
+        periodic_elements: str = "exclude",
         projection: Optional[ccrs.Projection] = None,
-        return_indices: Optional[bool] = False,
-        cache: Optional[bool] = True,
-        override: Optional[bool] = False,
-        return_non_nan_polygon_indices: Optional[bool] = False,
+        return_indices: bool = False,
+        cache: bool = True,
+        override: bool = False,
+        return_non_nan_polygon_indices: bool = False,
         **kwargs,
     ):
         """Constructs a ``matplotlib.collections.PolyCollection``` consisting
@@ -2723,10 +2721,10 @@ def to_polycollection(
 
     def to_linecollection(
         self,
-        periodic_elements: Optional[str] = "exclude",
+        periodic_elements: str = "exclude",
         projection: Optional[ccrs.Projection] = None,
-        cache: Optional[bool] = True,
-        override: Optional[bool] = False,
+        cache: bool = True,
+        override: bool = False,
         **kwargs,
     ):
         """Constructs a ``matplotlib.collections.LineCollection``` consisting

uxarray/grid/neighbors.py

@@ -50,9 +50,9 @@ class KDTree:
     def __init__(
         self,
         grid,
-        coordinates: str | None = "face centers",
-        coordinate_system: str | None = "cartesian",
-        distance_metric: str | None = "minkowski",
+        coordinates: str = "face centers",
+        coordinate_system: str = "cartesian",
+        distance_metric: str = "minkowski",
         reconstruct: bool = False,
     ):
         # Set up references
@@ -217,12 +217,12 @@ def _current_tree(self):
     def query(
         self,
         coords: np.ndarray | list | tuple,
-        k: int | None = 1,
-        return_distance: bool | None = True,
-        in_radians: bool | None = False,
-        dualtree: bool | None = False,
-        breadth_first: bool | None = False,
-        sort_results: bool | None = True,
+        k: int = 1,
+        return_distance: bool = True,
+        in_radians: bool = False,
+        dualtree: bool = False,
+        breadth_first: bool = False,
+        sort_results: bool = True,
     ):
         """Queries the tree for the ``k`` nearest neighbors.
 
@@ -301,11 +301,11 @@ def query(
     def query_radius(
         self,
         coords: np.ndarray | list | tuple,
-        r: int | None = 1.0,
-        return_distance: bool | None = False,
-        in_radians: bool | None = False,
-        count_only: bool | None = False,
-        sort_results: bool | None = False,
+        r: int = 1.0,
+        return_distance: bool = False,
+        in_radians: bool = False,
+        count_only: bool = False,
+        sort_results: bool = False,
     ):
         """Queries the tree for all neighbors within a radius ``r``.
 
@@ -440,9 +440,9 @@ class BallTree:
     def __init__(
         self,
         grid,
-        coordinates: str | None = "face centers",
-        coordinate_system: str | None = "spherical",
-        distance_metric: str | None = "haversine",
+        coordinates: str = "face centers",
+        coordinate_system: str = "spherical",
+        distance_metric: str = "haversine",
         reconstruct: bool = False,
     ):
         # maintain a reference to the source grid
@@ -602,12 +602,12 @@ def _current_tree(self):
     def query(
         self,
         coords: np.ndarray | list | tuple,
-        k: int | None = 1,
-        in_radians: bool | None = False,
-        return_distance: bool | None = True,
-        dualtree: bool | None = False,
-        breadth_first: bool | None = False,
-        sort_results: bool | None = True,
+        k: int = 1,
+        in_radians: bool = False,
+        return_distance: bool = True,
+        dualtree: bool = False,
+        breadth_first: bool = False,
+        sort_results: bool = True,
     ):
         """Queries the tree for the ``k`` nearest neighbors.
 
@@ -686,11 +686,11 @@ def query(
     def query_radius(
         self,
         coords: np.ndarray | list | tuple,
-        r: int | None = 1.0,
-        in_radians: bool | None = False,
-        return_distance: bool | None = False,
-        count_only: bool | None = False,
-        sort_results: bool | None = False,
+        r: int = 1.0,
+        in_radians: bool = False,
+        return_distance: bool = False,
+        count_only: bool = False,
+        sort_results: bool = False,
     ):
         """Queries the tree for all neighbors within a radius ``r``.
 
@@ -905,8 +905,8 @@ def _initialize_face_hash_table(self):
     def query(
         self,
         coords: np.ndarray | list | tuple,
-        in_radians: bool | None = False,
-        tol: float | None = 1e-6,
+        in_radians: bool = False,
+        tol: float = 1e-6,
     ):
         """Queries the hash table.
 

uxarray/plot/accessor.py

@@ -406,11 +406,11 @@ def __getattr__(self, name: str) -> Any:
 
     def polygons(
         self,
-        periodic_elements: str | None = "split",
+        periodic_elements: str = "split",
         backend: str | None = None,
-        engine: str | None = "spatialpandas",
-        rasterize: bool | None = True,
-        dynamic: bool | None = False,
+        engine: str = "spatialpandas",
+        rasterize: bool = True,
+        dynamic: bool = False,
         projection=None,
         xlabel: str | None = "Longitude",
         ylabel: str | None = "Latitude",

uxarray/remap/accessor.py

@@ -66,7 +66,7 @@ def nearest_neighbor(
         destination_grid: Grid,
         remap_to: str = "faces",
         backend: str = "uxarray",
-        yac_method: str | None = "nnn",
+        yac_method: str = "nnn",
         yac_options: dict | None = None,
         **kwargs,
     ) -> UxDataArray | UxDataset:

uxarray/subset/dataarray_accessor.py

@@ -66,7 +66,7 @@ def bounding_circle(
         self,
         center_coord: tuple | list | np.ndarray,
         r: float | int,
-        element: str | None = "face centers",
+        element: str = "face centers",
         inverse_indices: list[str] | set[str] | bool = False,
         **kwargs,
     ):
@@ -96,7 +96,7 @@ def nearest_neighbor(
         self,
         center_coord: tuple | list | np.ndarray,
         k: int,
-        element: str | None = "face centers",
+        element: str = "face centers",
         inverse_indices: list[str] | set[str] | bool = False,
         **kwargs,
     ):

uxarray/subset/grid_accessor.py

@@ -68,7 +68,7 @@ def bounding_circle(
         self,
         center_coord: tuple | list | np.ndarray,
         r: float | int,
-        element: str | None = "face centers",
+        element: str = "face centers",
         inverse_indices: list[str] | set[str] | bool = False,
         **kwargs,
     ):
@@ -107,7 +107,7 @@ def nearest_neighbor(
         self,
         center_coord: tuple | list | np.ndarray,
         k: int,
-        element: str | None = "face centers",
+        element: str = "face centers",
         inverse_indices: list[str] | set[str] | bool = False,
         **kwargs,
     ):