Unified ignoring of iris.warnings.IrisVagueMetadataWarning in preprocessors (#2646)

Co-authored-by: Valeriu Predoi <[email protected]>

Author: schlunma

esmvalcore/cmor/_fixes/emac/emac.py

@@ -12,6 +12,7 @@
 """
 
 import logging
+import warnings
 from shutil import copyfile
 
 import dask.array as da
@@ -23,6 +24,8 @@
 from netCDF4 import Dataset
 from scipy import constants
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+
 from ..shared import add_aux_coords_from_cubes
 from ._base_fixes import EmacFix, NegateData
 
@@ -230,14 +233,22 @@ def fix_metadata(self, cubes):
         )
         dt_cube = self.get_cube(cubes, var_name="dt")
 
-        cube = (
-            noxcg_cube.collapsed(
-                ["longitude", "latitude"], iris.analysis.SUM, weights=None
-            )
-            + noxic_cube.collapsed(
-                ["longitude", "latitude"], iris.analysis.SUM, weights=None
+        with warnings.catch_warnings(), ignore_iris_vague_metadata_warnings():
+            warnings.filterwarnings(
+                "ignore",
+                message="Collapsing spatial coordinate 'latitude' without "
+                "weighting",
+                category=UserWarning,
+                module="iris",
             )
-        ) / dt_cube
+            cube = (
+                noxcg_cube.collapsed(
+                    ["longitude", "latitude"], iris.analysis.SUM, weights=None
+                )
+                + noxic_cube.collapsed(
+                    ["longitude", "latitude"], iris.analysis.SUM, weights=None
+                )
+            ) / dt_cube
         cube.units = "kg s-1"
         cube.var_name = self.vardef.short_name
 
@@ -261,7 +272,8 @@ def fix_metadata(self, cubes):
         cubes = super().fix_metadata(cubes)
         cube = self.get_cube(cubes)
         z_coord = cube.coord(axis="Z")
-        cube = cube.collapsed(z_coord, iris.analysis.SUM)
+        with ignore_iris_vague_metadata_warnings():
+            cube = cube.collapsed(z_coord, iris.analysis.SUM)
         return CubeList([cube])
 
 

esmvalcore/iris_helpers.py

@@ -2,6 +2,9 @@
 
 from __future__ import annotations
 
+import warnings
+from collections.abc import Generator
+from contextlib import contextmanager
 from typing import Dict, Iterable, List, Literal, Sequence
 
 import dask.array as da
@@ -13,10 +16,28 @@
 from iris.coords import Coord
 from iris.cube import Cube
 from iris.exceptions import CoordinateMultiDimError, CoordinateNotFoundError
+from iris.warnings import IrisVagueMetadataWarning
 
 from esmvalcore.typing import NetCDFAttr
 
 
+@contextmanager
+def ignore_iris_vague_metadata_warnings() -> Generator[None]:
+    """Ignore specific warnings.
+
+    This can be used as a context manager. See also
+    https://scitools-iris.readthedocs.io/en/stable/generated/api/iris.warnings.html#iris.warnings.IrisVagueMetadataWarning.
+
+    """
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore",
+            category=IrisVagueMetadataWarning,
+            module="iris",
+        )
+        yield
+
+
 def add_leading_dim_to_cube(cube, dim_coord):
     """Add new leading dimension to cube.
 

esmvalcore/preprocessor/_area.py

@@ -7,7 +7,6 @@
 from __future__ import annotations
 
 import logging
-import warnings
 from pathlib import Path
 from typing import TYPE_CHECKING, Iterable, Literal, Optional
 
@@ -21,6 +20,7 @@
 from iris.cube import Cube, CubeList
 from iris.exceptions import CoordinateNotFoundError
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
 from esmvalcore.preprocessor._shared import (
     apply_mask,
     get_dims_along_axes,
@@ -240,7 +240,8 @@ def zonal_statistics(
             "Zonal statistics on irregular grids not yet implemented"
         )
     (agg, agg_kwargs) = get_iris_aggregator(operator, **operator_kwargs)
-    result = cube.collapsed("longitude", agg, **agg_kwargs)
+    with ignore_iris_vague_metadata_warnings():
+        result = cube.collapsed("longitude", agg, **agg_kwargs)
     if normalize is not None:
         result = get_normalized_cube(cube, result, normalize)
     return result
@@ -289,7 +290,8 @@ def meridional_statistics(
             "Meridional statistics on irregular grids not yet implemented"
         )
     (agg, agg_kwargs) = get_iris_aggregator(operator, **operator_kwargs)
-    result = cube.collapsed("latitude", agg, **agg_kwargs)
+    with ignore_iris_vague_metadata_warnings():
+        result = cube.collapsed("latitude", agg, **agg_kwargs)
     if normalize is not None:
         result = get_normalized_cube(cube, result, normalize)
     return result
@@ -355,15 +357,7 @@ def area_statistics(
         agg, agg_kwargs, "cell_area", cube, try_adding_calculated_cell_area
     )
 
-    with warnings.catch_warnings():
-        # Silence various warnings about collapsing multi-dimensional and/or
-        # non contiguous coordinates as this should be fine when the cell areas
-        # are provided and will fail when they needed but not provided.
-        warnings.filterwarnings(
-            "ignore",
-            category=iris.warnings.IrisVagueMetadataWarning,
-            module="iris",
-        )
+    with ignore_iris_vague_metadata_warnings():
         result = cube.collapsed(["latitude", "longitude"], agg, **agg_kwargs)
     if normalize is not None:
         result = get_normalized_cube(cube, result, normalize)

esmvalcore/preprocessor/_compare_with_refs.py

@@ -17,7 +17,10 @@
 from iris.cube import Cube, CubeList
 from scipy.stats import wasserstein_distance
 
-from esmvalcore.iris_helpers import rechunk_cube
+from esmvalcore.iris_helpers import (
+    ignore_iris_vague_metadata_warnings,
+    rechunk_cube,
+)
 from esmvalcore.preprocessor._io import concatenate
 from esmvalcore.preprocessor._other import histogram
 from esmvalcore.preprocessor._shared import (
@@ -431,7 +434,8 @@ def _calculate_metric(
 
     # Get result cube with correct dimensional metadata by using dummy
     # operation (max)
-    res_cube = cube.collapsed(coords, iris.analysis.MAX)
+    with ignore_iris_vague_metadata_warnings():
+        res_cube = cube.collapsed(coords, iris.analysis.MAX)
     res_cube.data = res_data
     res_cube.metadata = res_metadata
     res_cube.cell_methods = [*cube.cell_methods, CellMethod(metric, coords)]

esmvalcore/preprocessor/_cycles.py

@@ -5,6 +5,8 @@
 import iris
 import iris.coord_categorisation
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+
 logger = logging.getLogger(__name__)
 
 
@@ -69,8 +71,9 @@ def amplitude(cube, coords):
             )
 
     # Calculate amplitude
-    max_cube = cube.aggregated_by(coords, iris.analysis.MAX)
-    min_cube = cube.aggregated_by(coords, iris.analysis.MIN)
+    with ignore_iris_vague_metadata_warnings():
+        max_cube = cube.aggregated_by(coords, iris.analysis.MAX)
+        min_cube = cube.aggregated_by(coords, iris.analysis.MIN)
     amplitude_cube = max_cube - min_cube
     amplitude_cube.metadata = cube.metadata
 

esmvalcore/preprocessor/_derive/_shared.py

@@ -8,6 +8,8 @@
 from iris import NameConstraint
 from scipy import constants
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+
 logger = logging.getLogger(__name__)
 
 
@@ -21,12 +23,13 @@ def cloud_area_fraction(cubes, tau_constraint, plev_constraint):
         for coord in new_cube.coords()
         if len(coord.points) > 1
     ]
-    if "atmosphere_optical_thickness_due_to_cloud" in coord_names:
-        new_cube = new_cube.collapsed(
-            "atmosphere_optical_thickness_due_to_cloud", iris.analysis.SUM
-        )
-    if "air_pressure" in coord_names:
-        new_cube = new_cube.collapsed("air_pressure", iris.analysis.SUM)
+    with ignore_iris_vague_metadata_warnings():
+        if "atmosphere_optical_thickness_due_to_cloud" in coord_names:
+            new_cube = new_cube.collapsed(
+                "atmosphere_optical_thickness_due_to_cloud", iris.analysis.SUM
+            )
+        if "air_pressure" in coord_names:
+            new_cube = new_cube.collapsed("air_pressure", iris.analysis.SUM)
 
     return new_cube
 
@@ -108,11 +111,12 @@ def column_average(cube, hus_cube, zg_cube, ps_cube):
     cube.data = cube.core_data() * n_dry.core_data()
 
     # Column-average
-    cube = cube.collapsed("air_pressure", iris.analysis.SUM)
-    cube.data = (
-        cube.core_data()
-        / n_dry.collapsed("air_pressure", iris.analysis.SUM).core_data()
-    )
+    with ignore_iris_vague_metadata_warnings():
+        cube = cube.collapsed("air_pressure", iris.analysis.SUM)
+        cube.data = (
+            cube.core_data()
+            / n_dry.collapsed("air_pressure", iris.analysis.SUM).core_data()
+        )
     return cube
 
 

esmvalcore/preprocessor/_derive/amoc.py

@@ -3,6 +3,8 @@
 import iris
 import numpy as np
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+
 from ._baseclass import DerivedVariableBase
 
 
@@ -86,9 +88,7 @@ def calculate(cubes):
         cube = cube.extract(constraint=rapid_constraint)
 
         # 4: find the maximum in the water column along the time axis.
-        cube = cube.collapsed(
-            ["depth", "region"],
-            iris.analysis.MAX,
-        )
+        with ignore_iris_vague_metadata_warnings():
+            cube = cube.collapsed(["depth", "region"], iris.analysis.MAX)
 
         return cube

esmvalcore/preprocessor/_derive/toz.py

@@ -1,12 +1,11 @@
 """Derivation of variable ``toz``."""
 
-import warnings
-
 import cf_units
 import iris
 from scipy import constants
 
 from esmvalcore.cmor.table import CMOR_TABLES
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
 
 from .._regrid import extract_levels, regrid
 from ._baseclass import DerivedVariableBase
@@ -104,7 +103,8 @@ def calculate(cubes):
         # have correct shapes
         if not o3_cube.coords("longitude"):
             o3_cube = add_longitude_coord(o3_cube)
-            ps_cube = ps_cube.collapsed("longitude", iris.analysis.MEAN)
+            with ignore_iris_vague_metadata_warnings():
+                ps_cube = ps_cube.collapsed("longitude", iris.analysis.MEAN)
             ps_cube.remove_coord("longitude")
             ps_cube = add_longitude_coord(ps_cube)
 
@@ -117,12 +117,7 @@ def calculate(cubes):
         # widths
         p_layer_widths = pressure_level_widths(o3_cube, ps_cube, top_limit=0.0)
         toz_cube = o3_cube * p_layer_widths / STANDARD_GRAVITY * MW_O3 / MW_AIR
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                category=UserWarning,
-                message="Collapsing a non-contiguous coordinate",
-            )
+        with ignore_iris_vague_metadata_warnings():
             toz_cube = toz_cube.collapsed("air_pressure", iris.analysis.SUM)
         toz_cube.units = (
             o3_cube.units

esmvalcore/preprocessor/_derive/troz.py

@@ -3,6 +3,8 @@
 import dask.array as da
 import iris
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+
 from ._baseclass import DerivedVariableBase
 from .soz import STRATOSPHERIC_O3_THRESHOLD
 from .toz import DerivedVariable as Toz
@@ -45,7 +47,8 @@ def calculate(cubes):
         # have correct shapes
         if not o3_cube.coords("longitude"):
             o3_cube = add_longitude_coord(o3_cube)
-            ps_cube = ps_cube.collapsed("longitude", iris.analysis.MEAN)
+            with ignore_iris_vague_metadata_warnings():
+                ps_cube = ps_cube.collapsed("longitude", iris.analysis.MEAN)
             ps_cube.remove_coord("longitude")
             ps_cube = add_longitude_coord(ps_cube)
 

esmvalcore/preprocessor/_derive/uajet.py

@@ -4,6 +4,8 @@
 import iris
 import numpy as np
 
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+
 from ._baseclass import DerivedVariableBase
 
 # Constants (Southern hemisphere at 850 hPa)
@@ -31,7 +33,8 @@ def calculate(cubes):
         ua_cube = ua_cube.extract(
             iris.Constraint(latitude=lambda cell: LAT[0] <= cell <= LAT[1])
         )
-        ua_cube = ua_cube.collapsed("longitude", iris.analysis.MEAN)
+        with ignore_iris_vague_metadata_warnings():
+            ua_cube = ua_cube.collapsed("longitude", iris.analysis.MEAN)
 
         # Calculate maximum jet position
         uajet_vals = []

esmvalcore/preprocessor/_mask.py

@@ -21,7 +21,10 @@
 from iris.cube import Cube
 from iris.util import rolling_window
 
-from esmvalcore.preprocessor._shared import apply_mask
+from esmvalcore.iris_helpers import ignore_iris_vague_metadata_warnings
+from esmvalcore.preprocessor._shared import (
+    apply_mask,
+)
 
 from ._supplementary_vars import register_supplementaries
 
@@ -396,12 +399,13 @@ def count_spells(
     # if you want overlapping windows set the step to be m*spell_length
     # where m is a float
     ###############################################################
-    hit_windows = rolling_window(
-        data_hits,
-        window=spell_length,
-        step=spell_length,
-        axis=axis,
-    )
+    with ignore_iris_vague_metadata_warnings():
+        hit_windows = rolling_window(
+            data_hits,
+            window=spell_length,
+            step=spell_length,
+            axis=axis,
+        )
     # Find the windows "full of True-s" (along the added 'window axis').
     full_windows = array_module.all(hit_windows, axis=axis + 1)
     # Count points fulfilling the condition (along the time axis).
@@ -726,12 +730,13 @@ def _get_fillvalues_mask(
     )
 
     # Calculate the statistic.
-    counts_windowed_cube = cube.collapsed(
-        "time",
-        spell_count,
-        threshold=min_value,
-        spell_length=time_window,
-    )
+    with ignore_iris_vague_metadata_warnings():
+        counts_windowed_cube = cube.collapsed(
+            "time",
+            spell_count,
+            threshold=min_value,
+            spell_length=time_window,
+        )
 
     # Create mask
     mask = counts_windowed_cube.core_data() < counts_threshold