Fix misleading/confusing error types throughout uxarray

test/core/test_api.py

@@ -85,7 +85,7 @@ def test_open_dataset_single_argument_rejects_invalid_combined_file(datasetpath)
 
     data_path = datasetpath("ugrid", "outCSne30", "outCSne30_var2.nc")
 
-    with pytest.raises(RuntimeError, match="Failed to parse uxgrid information from xarray.Dataset."):
+    with pytest.raises(ux.errors.GridInvalidError, match="Failed to parse uxgrid information from xarray.Dataset."):
         ux.open_dataset(data_path)
 
 

test/grid/grid/test_core.py

@@ -131,5 +131,5 @@ def test_dual_mesh_mpas(gridpath):
 def test_dual_duplicate(gridpath):
     """Test dual mesh creation with duplicate grids."""
     dataset = ux.open_dataset(gridpath("ugrid", "geoflow-small", "grid.nc"), gridpath("ugrid", "geoflow-small", "grid.nc"))
-    with pytest.raises(RuntimeError):
+    with pytest.raises(ux.errors.GridInvalidError):
         dataset.get_dual()

test/io/test_utils.py

@@ -2,6 +2,7 @@
 import pytest
 import xarray as xr
 
+from uxarray.errors import GridInvalidError
 from uxarray.io.utils import _parse_grid_type
 
 
@@ -61,5 +62,5 @@ def test_parse_grid_type_detects_structured_grid():
     ],
 )
 def test_parse_grid_type_rejects_incomplete_format_signals(dataset):
-    with pytest.raises(RuntimeError, match="Failed to parse uxgrid information from xarray.Dataset."):
+    with pytest.raises(GridInvalidError, match="Failed to parse uxgrid information from xarray.Dataset."):
         _parse_grid_type(dataset)

uxarray/__init__.py

@@ -1,4 +1,4 @@
-from . import tutorial
+from . import errors, tutorial
 from .constants import INT_DTYPE, INT_FILL_VALUE
 from .core.api import (
     concat,
@@ -37,4 +37,5 @@
     "INT_DTYPE",
     "INT_FILL_VALUE",
     "Grid",
+    "errors",
 )

uxarray/core/aggregation.py

@@ -90,7 +90,7 @@ def _node_to_face_aggregation(uxda, aggregation, aggregation_func_kwargs):
             uxda, NUMPY_AGGREGATIONS[aggregation], aggregation_func_kwargs
         )
     else:
-        raise ValueError
+        raise TypeError
 
     return uxarray.core.dataarray.UxDataArray(
         uxgrid=uxda.uxgrid,
@@ -158,7 +158,7 @@ def _node_to_edge_aggregation(uxda, aggregation, aggregation_func_kwargs):
             uxda, NUMPY_AGGREGATIONS[aggregation], aggregation_func_kwargs
         )
     else:
-        raise ValueError
+        raise TypeError
 
     return uxarray.core.dataarray.UxDataArray(
         uxgrid=uxda.uxgrid,

uxarray/core/dataarray.py

@@ -860,7 +860,7 @@ def zonal_anomaly(self, lat=(-90, 90, 10), conservative: bool = False):
         elif isinstance(lat, (list, np.ndarray)):
             edges = np.asarray(lat, dtype=float)
         else:
-            raise ValueError(
+            raise TypeError(
                 "Invalid value for 'lat'. Must be a tuple (start, end, step) or array-like band edges."
             )
 
@@ -2167,7 +2167,7 @@ def get_dual(self):
         """
 
         if _check_duplicate_nodes_indices(self.uxgrid):
-            raise RuntimeError("Duplicate nodes found, cannot construct dual")
+            raise GridInvalidError("Duplicate nodes found, cannot construct dual")
 
         if self.uxgrid.partial_sphere_coverage:
             warn(

uxarray/core/dataset.py

@@ -708,7 +708,7 @@ def get_dual(self):
         """
 
         if _check_duplicate_nodes_indices(self.uxgrid):
-            raise RuntimeError("Duplicate nodes found, cannot construct dual")
+            raise GridInvalidError("Duplicate nodes found, cannot construct dual")
 
         if self.uxgrid.partial_sphere_coverage:
             warn(

uxarray/grid/bounds.py

@@ -416,7 +416,7 @@ def insert_pt_in_latlonbox(old_box, new_pt, is_lon_periodic=True):
     else:
         # Validate longitude point
         if not np.isnan(lon_pt) and (lon_pt < 0.0 or lon_pt > 2.0 * np.pi):
-            raise Exception("Longitude point out of range")
+            raise ValueError("Longitude point out of range")
 
         # Check for pole points
         is_pole_point = False
@@ -465,7 +465,7 @@ def insert_pt_in_latlonbox(old_box, new_pt, is_lon_periodic=True):
 
                         # Ensure widths are non-negative
                         if (d_width_a < 0.0) or (d_width_b < 0.0):
-                            raise Exception(
+                            raise AssertionError(
                                 "Logic error in longitude box width calculation"
                             )
 

uxarray/grid/grid.py

@@ -17,7 +17,7 @@
 # Import the utility function for opening datasets with fallback
 from uxarray.core.utils import _open_dataset_with_fallback
 from uxarray.cross_sections import GridCrossSectionAccessor
-from uxarray.errors import DataCenteringError, GridInvalidError
+from uxarray.errors import DataCenteringError, DimensionError, GridInvalidError
 from uxarray.formatting_html import grid_repr
 from uxarray.grid.area import _get_all_face_area_from_coords
 from uxarray.grid.bounds import _populate_face_bounds
@@ -569,7 +569,7 @@ def from_face_vertices(
             Indicates whether the inputted vertices are in lat/lon, with units in degrees
         """
         if not isinstance(face_vertices, (list, tuple, np.ndarray)):
-            raise ValueError("Input must be either a list, tuple, or np.ndarray")
+            raise TypeError("Input must be either a list, tuple, or np.ndarray")
 
         face_vertices = np.asarray(face_vertices)
 
@@ -580,7 +580,7 @@ def from_face_vertices(
             grid_ds = _read_face_vertices(np.array([face_vertices]), latlon)
 
         else:
-            raise RuntimeError(
+            raise DimensionError(
                 f"Invalid Input Dimension: {face_vertices.ndim}. Expected dimension should be "
                 f"3: [n_face, n_node, two/three] or 2 when only "
                 f"one face is passed in."
@@ -633,7 +633,7 @@ def validate(self, check_duplicates=True):
             print("Mesh validation successful.")
             return True
         else:
-            raise RuntimeError("Mesh validation failed.")
+            raise GridInvalidError("Mesh validation failed.")
 
     def construct_face_centers(self, method="cartesian average"):
         """Constructs face centers, this method provides users direct control
@@ -1612,7 +1612,7 @@ def boundary_node_indices(self):
         """Indices of nodes that border regions not covered by any geometry
         (holes) in a partial grid."""
         if "boundary_node_indices" not in self._ds:
-            raise ValueError
+            raise NotImplementedError
 
         return self._ds["boundary_node_indices"]
 
@@ -1663,7 +1663,7 @@ def inverse_indices(self) -> xr.Dataset:
         if self.is_subset:
             return self._inverse_indices
         else:
-            raise Exception(
+            raise AttributeError(
                 "Grid is not a subset, therefore no inverse face indices exist"
             )
 
@@ -2534,7 +2534,7 @@ def get_dual(self, check_duplicate_nodes: bool = False):
         if check_duplicate_nodes:
             if _check_duplicate_nodes_indices(self):
                 # TODO: This is very slow
-                raise RuntimeError("Duplicate nodes found, cannot construct dual")
+                raise GridInvalidError("Duplicate nodes found, cannot construct dual")
 
         # Get dual mesh node face connectivity
         dual_node_face_conn = construct_dual(grid=self)

uxarray/grid/neighbors.py

@@ -4,6 +4,7 @@
 from numpy import deg2rad
 
 from uxarray.constants import ERROR_TOLERANCE, INT_DTYPE, INT_FILL_VALUE
+from uxarray.errors import DimensionError
 
 
 class KDTree:
@@ -96,7 +97,7 @@ def _build_from_nodes(self):
                 ).T
 
             else:
-                raise TypeError(
+                raise ValueError(
                     f"Unknown coordinate_system, {self.coordinate_system}, use either 'cartesian' or "
                     f"'spherical'"
                 )
@@ -192,7 +193,7 @@ def _current_tree(self):
         elif self._coordinates == "edge centers":
             _tree = self._tree_from_edge_centers
         else:
-            raise TypeError(
+            raise ValueError(
                 f"Unknown coordinates location, {self._coordinates}, use either 'nodes', 'face centers', "
                 f"or 'edge centers'"
             )
@@ -1010,13 +1011,13 @@ def _prepare_xy_for_query(xy, use_radians, distance_metric):
 
     # expected shape is [n_pairs, 2]
     if xy.shape[1] == 3:
-        raise AssertionError(
+        raise DimensionError(
             "The dimension of each coordinate pair must be two (lon, lat). Did you attempt to query using Cartesian "
             "(x, y, z) coordinates?"
         )
 
     if xy.shape[1] != 2:
-        raise AssertionError(
+        raise DimensionError(
             "The dimension of each coordinate pair must be two (lon, lat).)"
         )
 
@@ -1044,13 +1045,13 @@ def _prepare_xyz_for_query(xyz):
 
     # expected shape is [n_pairs, 3]
     if xyz.shape[1] == 2:
-        raise AssertionError(
+        raise DimensionError(
             "The dimension of each coordinate pair must be three (x, y, z). Did you attempt to query using latlon "
             "(lat, lon) coordinates?"
         )
 
     if xyz.shape[1] != 3:
-        raise AssertionError(
+        raise DimensionError(
             "The dimension of each coordinate pair must be three (x, y, z).)"
         )
 

uxarray/grid/slice.py

@@ -32,7 +32,7 @@ def _slice_node_indices(
     """
 
     if inclusive is False:
-        raise ValueError("Exclusive slicing is not yet supported.")
+        raise NotImplementedError("Exclusive slicing is not yet supported.")
 
     # faces that saddle nodes given in 'indices'
     face_indices = np.unique(grid.node_face_connectivity.values[indices].ravel())
@@ -62,7 +62,7 @@ def _slice_edge_indices(
     """
 
     if inclusive is False:
-        raise ValueError("Exclusive slicing is not yet supported.")
+        raise NotImplementedError("Exclusive slicing is not yet supported.")
 
     # faces that saddle nodes given in 'indices'
     face_indices = np.unique(grid.edge_face_connectivity.values[indices].ravel())

uxarray/grid/utils.py

@@ -439,7 +439,7 @@ def make_setter(key: str):
 
     def setter(self, value):
         if not isinstance(value, xr.DataArray):
-            raise ValueError(f"{key} must be an xr.DataArray")
+            raise TypeError(f"{key} must be an xr.DataArray")
         self._ds[key] = value
 
     return setter

uxarray/io/_esmf.py

@@ -76,7 +76,7 @@ def _read_esmf(in_ds):
             )
 
     else:
-        raise ValueError(
+        raise NotImplementedError(
             "Reading in ESMF grids with Cartesian coordinates not yet supported"
         )
 

uxarray/io/_icon.py

@@ -156,4 +156,6 @@ def _read_icon(ext_ds, use_dual=False):
     if not use_dual:
         return _primal_to_ugrid(ext_ds, out_ds)
     else:
-        raise ValueError("Conversion of the ICON Dual mesh is not yet supported.")
+        raise NotImplementedError(
+            "Conversion of the ICON Dual mesh is not yet supported."
+        )

uxarray/io/_scrip.py

@@ -120,7 +120,7 @@ def _to_ugrid(in_ds, out_ds):
         )
 
     else:
-        raise Exception("Structured scrip files are not yet supported")
+        raise NotImplementedError("Structured scrip files are not yet supported")
 
     # populate source dims
     source_dims_dict[in_ds["grid_center_lon"].dims[0]] = "n_face"

uxarray/io/utils.py

@@ -1,6 +1,7 @@
 import numpy as np
 import xarray as xr
 
+from uxarray.errors import GridInvalidError
 from uxarray.io._esmf import _esmf_to_ugrid_dims
 from uxarray.io._icon import _icon_to_ugrid_dims
 from uxarray.io._mpas import _mpas_to_ugrid_dims
@@ -120,7 +121,9 @@ def _parse_grid_type(dataset):
         mesh_type = "Structured"
         return mesh_type, lon_name, lat_name
     else:
-        raise RuntimeError("Failed to parse uxgrid information from xarray.Dataset.")
+        raise GridInvalidError(
+            "Failed to parse uxgrid information from xarray.Dataset."
+        )
 
     return mesh_type, None, None
 

uxarray/remap/yac.py

@@ -122,7 +122,7 @@ def _get_lon_lat(grid, dim: str) -> tuple[np.ndarray, np.ndarray]:
     lon = getattr(grid, lon_attr, None)
     lat = getattr(grid, lat_attr, None)
     if lon is None or lat is None:
-        raise ValueError(
+        raise AttributeError(
             f"Grid does not provide {lon_attr}/{lat_attr} required for YAC remapping."
         )
     return np.deg2rad(np.asarray(lon.values, dtype=np.float64)), np.deg2rad(