[pre-commit.ci] pre-commit autoupdate (#5150)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/psf/black: 22.12.0 → 23.1.0](psf/black@22.12.0...23.1.0)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.pre-commit-config.yaml

@@ -29,7 +29,7 @@ repos:
     -   id: no-commit-to-branch
 
 -   repo: https://github.com/psf/black
-    rev: 22.12.0
+    rev: 23.1.0
     hooks:
     -   id: black
         pass_filenames: false

docs/gallery_code/general/plot_lineplot_with_legend.py

@@ -24,7 +24,6 @@ def main():
     )
 
     for cube in temperature.slices("longitude"):
-
         # Create a string label to identify this cube (i.e. latitude: value).
         cube_label = "latitude: %s" % cube.coord("latitude").points[0]
 

docs/gallery_code/general/plot_projections_and_annotations.py

@@ -26,7 +26,6 @@
 
 
 def make_plot(projection_name, projection_crs):
-
     # Create a matplotlib Figure.
     plt.figure()
 

docs/gallery_code/general/plot_zonal_means.py

@@ -16,7 +16,6 @@
 
 
 def main():
-
     # Loads air_temp.pp and "collapses" longitude into a single, average value.
     fname = iris.sample_data_path("air_temp.pp")
     temperature = iris.load_cube(fname)

docs/gallery_code/meteorology/plot_lagged_ensemble.py

@@ -86,7 +86,6 @@ def main():
 
     # Iterate over all possible latitude longitude slices.
     for cube in last_timestep.slices(["latitude", "longitude"]):
-
         # Get the ensemble member number from the ensemble coordinate.
         ens_member = cube.coord("realization").points[0]
 

docs/src/userguide/plotting_examples/1d_with_legend.py

@@ -13,7 +13,6 @@
 temperature = temperature[5:9, :]
 
 for cube in temperature.slices("longitude"):
-
     # Create a string label to identify this cube (i.e. latitude: value)
     cube_label = "latitude: %s" % cube.coord("latitude").points[0]
 

lib/iris/__init__.py

@@ -175,7 +175,6 @@ def __init__(self, datum_support=False, pandas_ndim=False):
         self.__dict__["pandas_ndim"] = pandas_ndim
 
     def __repr__(self):
-
         # msg = ('Future(example_future_flag={})')
         # return msg.format(self.example_future_flag)
         msg = "Future(datum_support={}, pandas_ndim={})"

lib/iris/_merge.py

@@ -1418,6 +1418,7 @@ def _define_space(self, space, positions, indexes, function_matrix):
             participates in a functional relationship.
 
         """
+
         # Heuristic reordering of coordinate defintion indexes into
         # preferred dimension order.
         def axis_and_name(name):

lib/iris/analysis/__init__.py

@@ -296,7 +296,6 @@ def _dimensional_metadata_comparison(*cubes, object_get=None):
     # for coordinate groups
     for cube, coords in zip(cubes, all_coords):
         for coord in coords:
-
             # if this coordinate has already been processed, then continue on
             # to the next one
             if id(coord) in processed_coords:

lib/iris/analysis/_area_weighted.py

@@ -853,7 +853,7 @@ def _calculate_regrid_area_weighted_weights(
         cached_x_bounds = []
         cached_x_indices = []
         max_x_indices = 0
-        for (x_0, x_1) in grid_x_bounds:
+        for x_0, x_1 in grid_x_bounds:
             if grid_x_decreasing:
                 x_0, x_1 = x_1, x_0
             x_bounds, x_indices = _cropped_bounds(src_x_bounds, x_0, x_1)

lib/iris/analysis/_interpolation.py

@@ -268,7 +268,7 @@ def _account_for_circular(self, points, data):
         """
         from iris.analysis.cartography import wrap_lons
 
-        for (circular, modulus, index, dim, offset) in self._circulars:
+        for circular, modulus, index, dim, offset in self._circulars:
             if modulus:
                 # Map all the requested values into the range of the source
                 # data (centred over the centre of the source data to allow

lib/iris/analysis/_scipy_interpolate.py

@@ -225,7 +225,6 @@ def compute_interp_weights(self, xi, method=None):
         prepared = (xi_shape, method) + self._find_indices(xi.T)
 
         if method == "linear":
-
             xi_shape, method, indices, norm_distances, out_of_bounds = prepared
 
             # Allocate arrays for describing the sparse matrix.

lib/iris/analysis/calculus.py

@@ -594,7 +594,6 @@ def curl(i_cube, j_cube, k_cube=None):
         horiz_cs, (iris.coord_systems.GeogCS, iris.coord_systems.RotatedGeogCS)
     )
     if not spherical_coords:
-
         # TODO Implement some mechanism for conforming to a common grid
         dj_dx = _curl_differentiate(j_cube, x_coord)
         prototype_diff = dj_dx

lib/iris/analysis/trajectory.py

@@ -85,7 +85,6 @@ def __init__(self, waypoints, sample_count=10):
         cur_seg = segments[cur_seg_i]
         len_accum = cur_seg.length
         for p in range(self.sample_count):
-
             # calculate the sample position along our total length
             sample_at_len = p * sample_step
 

lib/iris/common/metadata.py

@@ -969,6 +969,7 @@ def _combine_lenient(self, other):
             A list of combined metadata member values.
 
         """
+
         # Perform "strict" combination for "coord_system" and "climatological".
         def func(field):
             left = getattr(self, field)
@@ -1024,6 +1025,7 @@ def _difference_lenient(self, other):
             A list of difference metadata member values.
 
         """
+
         # Perform "strict" difference for "coord_system" and "climatological".
         def func(field):
             left = getattr(self, field)

lib/iris/coord_categorisation.py

@@ -90,6 +90,7 @@ def vectorised_fn(*args):
 # coordinates only
 #
 
+
 # Private "helper" function
 def _pt_date(coord, time):
     """

lib/iris/coord_systems.py

@@ -478,7 +478,6 @@ def datum(self, value):
 
     @classmethod
     def from_datum(cls, datum, longitude_of_prime_meridian=None):
-
         crs = super().__new__(cls)
 
         crs._semi_major_axis = None
@@ -949,7 +948,6 @@ def __init__(
         false_northing=None,
         ellipsoid=None,
     ):
-
         """
         Constructs a Geostationary coord system.
 

lib/iris/coords.py

@@ -2846,7 +2846,6 @@ def _new_bounds_requirements(self, bounds):
             n_bounds = bounds.shape[-1]
             n_points = bounds.shape[0]
             if n_points > 1:
-
                 directions = set()
                 for b_index in range(n_bounds):
                     monotonic, direction = iris.util.monotonic(

lib/iris/cube.py

@@ -2688,7 +2688,6 @@ def subset(self, coord):
             coord_to_extract in self.aux_coords
             and len(coord_to_extract.points) == 1
         ):
-
             # Default to returning None
             result = None
 

lib/iris/experimental/ugrid/mesh.py

@@ -3127,9 +3127,7 @@ def _construct_access_arrays(self):
             flat_inds_safe = al.where(missing_inds, 0, flat_inds_nomask)
             # Here's the core indexing operation.
             # The comma applies all inds-array values to the *first* dimension.
-            bounds = node_points[
-                flat_inds_safe,
-            ]
+            bounds = node_points[flat_inds_safe,]
             # Fix 'missing' locations, and restore the proper shape.
             bounds = al.ma.masked_array(bounds, missing_inds)
             bounds = bounds.reshape(indices.shape)

lib/iris/experimental/ugrid/metadata.py

@@ -53,6 +53,7 @@ def _combine_lenient(self, other):
             A list of combined metadata member values.
 
         """
+
         # Perform "strict" combination for "cf_role", "start_index", "location_axis".
         def func(field):
             left = getattr(self, field)
@@ -113,6 +114,7 @@ def _difference_lenient(self, other):
             A list of difference metadata member values.
 
         """
+
         # Perform "strict" difference for "cf_role", "start_index", "location_axis".
         def func(field):
             left = getattr(self, field)
@@ -233,6 +235,7 @@ def _difference_lenient(self, other):
             A list of difference metadata member values.
 
         """
+
         # Perform "strict" difference for "topology_dimension",
         # "node_dimension", "edge_dimension" and "face_dimension".
         def func(field):
@@ -297,6 +300,7 @@ def _combine_lenient(self, other):
             A list of combined metadata member values.
 
         """
+
         # It is actually "strict" : return None except where members are equal.
         def func(field):
             left = getattr(self, field)
@@ -352,6 +356,7 @@ def _difference_lenient(self, other):
             A list of different metadata member values.
 
         """
+
         # Perform "strict" difference for location / axis.
         def func(field):
             left = getattr(self, field)

lib/iris/fileformats/abf.py

@@ -219,7 +219,6 @@ def load_cubes(filespecs, callback=None):
 
     for filespec in filespecs:
         for filename in glob.glob(filespec):
-
             field = ABFField(filename)
             cube = field.to_cube()
 

lib/iris/fileformats/name_loaders.py

@@ -994,7 +994,6 @@ def load_NAMEIII_version2(filename):
     # using the next() method. This will come in handy as we wish to
     # progress through the file line by line.
     with open(filename, "r") as file_handle:
-
         # define a dictionary to hold the header metadata about this file
         header = read_header(file_handle)
 
@@ -1005,7 +1004,6 @@ def load_NAMEIII_version2(filename):
         column_headings = {}
         datacol1 = header["Number of preliminary cols"]
         for line in file_handle:
-
             data = [col.strip() for col in line.split(",")][:-1]
 
             # If first column is not zero we have reached the end

lib/iris/fileformats/pp.py

@@ -625,7 +625,7 @@ def __getstate__(self):
     def __setstate__(self, state):
         # Because we have __slots__, this is needed to support Pickle.load()
         # (Use setattr, as there is no object dictionary.)
-        for (key, value) in state:
+        for key, value in state:
             setattr(self, key, value)
 
     def __eq__(self, other):
@@ -2029,10 +2029,8 @@ def pp_filter(field):
         res = True
         if field.stash not in _STASH_ALLOW:
             if pp_constraints.get("stash"):
-
                 res = False
                 for call_func in pp_constraints["stash"]:
-
                     if call_func(str(field.stash)):
                         res = True
                         break

lib/iris/fileformats/pp_load_rules.py

@@ -756,7 +756,6 @@ def date2year(t_in):
             )
         )
     ):
-
         coords_and_dims.append(
             _new_coord_and_dims(
                 do_vector,

lib/iris/fileformats/rules.py

@@ -394,7 +394,7 @@ def _load_pairs_from_fields_and_filenames(
             yield (cube, field)
 
     regrid_cache = {}
-    for (cube, factories, field) in results_needing_reference:
+    for cube, factories, field in results_needing_reference:
         _resolve_factory_references(
             cube, factories, concrete_reference_targets, regrid_cache
         )

lib/iris/fileformats/um/_fast_load_structured_fields.py

@@ -133,6 +133,7 @@ def element_arrays_and_dims(self):
 
     def _field_vector_element_arrays(self):
         """Define the field components used in the structure analysis."""
+
         # Define functions to make t1 and t2 values as date-time tuples.
         # These depend on header version (PPField2 has no seconds values).
         def t1_fn(fld):

lib/iris/quickplot.py

@@ -45,7 +45,6 @@ def _title(cube_or_coord, with_units):
             or units.is_no_unit()
             or units == cf_units.Unit("1")
         ):
-
             if _use_symbol(units):
                 units = units.symbol
             elif units.is_time_reference():

lib/iris/tests/graphics/__init__.py

@@ -187,7 +187,6 @@ def check_graphic(test_id: str, results_dir: Union[str, Path]) -> None:
     try:
 
         def _create_missing(phash: str) -> None:
-
             output_path = test_output_dir / (test_id + ".png")
 
             print(f"Creating image file: {output_path}")
@@ -214,7 +213,6 @@ def _create_missing(phash: str) -> None:
         phash = get_phash(buffer)
 
         if test_id in repo:
-
             expected = hex_to_hash(repo[test_id])
 
             # Calculate hamming distance vector for the result hash.

lib/iris/tests/integration/test_Datums.py

@@ -23,7 +23,6 @@ def setUp(self):
         self.start_crs = ccrs.OSGB(False)
 
     def test_transform_points_datum(self):
-
         # Iris version
         wgs84 = GeogCS.from_datum("WGS84")
         iris_cs = LambertConformal(

lib/iris/tests/test_cdm.py

@@ -349,7 +349,6 @@ def test_similar_coord(self):
         )
 
     def test_cube_summary_cell_methods(self):
-
         cube = self.cube_2d.copy()
 
         # Create a list of values used to create cell methods

lib/iris/tests/test_cf.py

@@ -276,9 +276,7 @@ def test_destructor(self):
         didn't exist because opening the dataset had failed.
         """
         with self.temp_filename(suffix=".nc") as fn:
-
             with open(fn, "wb+") as fh:
-
                 fh.write(
                     b"\x89HDF\r\n\x1a\nBroken file with correct signature"
                 )

lib/iris/tests/test_io_init.py

@@ -126,7 +126,7 @@ def test_format_picker(self):
         ]
 
         # test that each filespec is identified as the expected format
-        for (expected_format_name, file_spec) in test_specs:
+        for expected_format_name, file_spec in test_specs:
             test_path = tests.get_data_path(file_spec)
             with open(test_path, "rb") as test_file:
                 a = iff.FORMAT_AGENT.get_spec(test_path, test_file)

lib/iris/tests/test_merge.py

@@ -190,7 +190,7 @@ def setUp(self):
         )
 
     def test__ndarray_ndarray(self):
-        for (lazy0, lazy1) in self.lazy_combos:
+        for lazy0, lazy1 in self.lazy_combos:
             cubes = iris.cube.CubeList()
             cubes.append(self._make_cube(0, dtype=self.dtype, lazy=lazy0))
             cubes.append(self._make_cube(1, dtype=self.dtype, lazy=lazy1))

lib/iris/tests/test_netcdf.py

@@ -313,9 +313,7 @@ def test_deferred_loading(self):
             cube[((0, 8, 4, 2, 14, 12),)][((0, 2, 4, 1),)],
             ("netcdf", "netcdf_deferred_tuple_1.cml"),
         )
-        subcube = cube[((0, 8, 4, 2, 14, 12),)][((0, 2, 4, 1),)][
-            (1, 3),
-        ]
+        subcube = cube[((0, 8, 4, 2, 14, 12),)][((0, 2, 4, 1),)][(1, 3),]
         self.assertCML(subcube, ("netcdf", "netcdf_deferred_tuple_2.cml"))
 
         # Consecutive mixture on same dimension.
@@ -1417,7 +1415,6 @@ def test_process_flags(self):
         }
 
         for bits, descriptions in multiple_map.items():
-
             ll_cube = stock.lat_lon_cube()
             ll_cube.attributes["ukmo__process_flags"] = descriptions
 

lib/iris/tests/test_nimrod.py

@@ -80,7 +80,8 @@ def test_huge_field_load(self):
     @tests.skip_data
     def test_load_kwarg(self):
         """Tests that the handle_metadata_errors kwarg is effective by setting it to
-        False with a file with known incomplete meta-data (missing ellipsoid)."""
+        False with a file with known incomplete meta-data (missing ellipsoid).
+        """
         datafile = "u1096_ng_ek00_pressure_2km"
         with self.assertRaisesRegex(
             TranslationError,