DOCS: numpydocs 5

lib/iris/_concatenate.py

@@ -488,7 +488,7 @@ def _coordinate_differences(self, other, attr, reason="metadata"):
         attr : str
             The _CubeSignature attribute within which differences exist
             between `self` and `other`.
-        reason : str
+        reason : str, default="metadata"
             The reason to give for mismatch (function is normally, but not
             always, testing metadata)
 
@@ -854,22 +854,22 @@ def register(
         axis : optional
             Seed the dimension of concatenation for the :class:`_ProtoCube`
             rather than rely on negotiation with source-cubes.
-        error_on_mismatch : bool, optional
+        error_on_mismatch : bool, default=False
             If True, raise an informative error if registration fails.
-        check_aux_coords : bool, optional
+        check_aux_coords : bool, default=False
             Checks if the points and bounds of auxiliary coordinates of the
             cubes match. This check is not applied to auxiliary coordinates
             that span the dimension the concatenation is occurring along.
             Defaults to False.
-        check_cell_measures : bool, optional
+        check_cell_measures : bool, default=False
             Checks if the data of cell measures of the cubes match. This check
             is not applied to cell measures that span the dimension the
             concatenation is occurring along. Defaults to False.
-        check_ancils : bool, optional
+        check_ancils : bool, default=False
             Checks if the data of ancillary variables of the cubes match. This
             check is not applied to ancillary variables that span the dimension
             the concatenation is occurring along. Defaults to False.
-        check_derived_coords : bool, optional
+        check_derived_coords : bool, default=False
             Checks if the points and bounds of derived coordinates of the cubes
             match. This check is not applied to derived coordinates that span
             the dimension the concatenation is occurring along. Note that

lib/iris/_data_manager.py

@@ -273,7 +273,7 @@ def copy(self, data=None):
 
         Parameters
         ----------
-        data :
+        data : optional
             Replace the data of the copy with this data.
 
         Returns

lib/iris/_lazy_data.py

@@ -72,12 +72,12 @@ def _optimum_chunksize_internals(
         Pre-existing chunk shape of the target data.
     shape : tuple of int
         The full array shape of the target data.
-    limit : int
+    limit : int, optional
         The 'ideal' target chunk size, in bytes.  Default from
         :mod:`dask.config`.
     dtype : np.dtype
         Numpy dtype of target data.
-    dims_fixed : list of bool
+    dims_fixed : list of bool, optional
         If set, a list of values equal in length to 'chunks' or 'shape'.
         'True' values indicate a dimension that can not be changed, i.e. that
         element of the result must equal the corresponding value in 'chunks' or
@@ -232,14 +232,14 @@ def as_lazy_data(
         This will be converted to a :class:`dask.array.Array`.
     chunks : list of int, optional
         If present, a source chunk shape, e.g. for a chunked netcdf variable.
-    asarray : bool, optional
+    asarray : bool, default=False
         If True, then chunks will be converted to instances of `ndarray`.
         Set to False (default) to pass passed chunks through unchanged.
     dims_fixed : list of bool, optional
         If set, a list of values equal in length to 'chunks' or data.ndim.
         'True' values indicate a dimension which can not be changed, i.e. the
         result for that index must equal the value in 'chunks' or data.shape.
-    dask_chunking : bool, optional
+    dask_chunking : bool, default=False
         If True, Iris chunking optimisation will be bypassed, and dask's default
         chunking will be used instead. Including a value for chunks while dask_chunking
         is set to True will result in a failure.

lib/iris/_merge.py

@@ -68,7 +68,7 @@ class _CoordMetaData(
     bounds_dtype :
         The bounds data :class:`numpy.dtype` of an associated coordinate.
         None otherwise.
-    kwargs:
+    kwargs :
         A dictionary of key/value pairs required to create a coordinate.
 
     """
@@ -162,11 +162,11 @@ class _CoordPayload(namedtuple("CoordPayload", ["scalar", "vector", "factory_def
 
     Parameters
     ----------
-    scalar:
+    scalar :
         A :class:`_ScalarCoordPayload` instance.
-    vector:
+    vector :
         A :class:`_VectorCoordPayload` instance.
-    factory_defns:
+    factory_defns :
         A list of :class:`_FactoryDefn` instances.
 
     """
@@ -637,7 +637,7 @@ def _separable(name, indexes):
 
     Returns
     -------
-    tupl
+    tuple
         A tuple containing the set of separable and inseparable
         candidate dimensions.
 
@@ -777,7 +777,7 @@ def _is_dependent(dependent, independent, positions, function_mapping=None):
     positions :
         A list containing a dictionary of candidate dimension key to
         scalar value pairs for each source-cube.
-    function_mapping : optional, default=None
+    function_mapping : optional
         A dictionary that enumerates a valid functional relationship
         between the dependent candidate dimension and the independent
         candidate dimension/s.
@@ -1052,7 +1052,7 @@ def derive_space(groups, relation_matrix, positions, function_matrix=None):
     positions :
         A list containing a dictionary of candidate dimension key to
         scalar value pairs for each source-cube.
-    function_matrix : optional, default=None
+    function_matrix : optional
           The function mapping dictionary for each candidate dimension that
           participates in a functional relationship.
 
@@ -1186,7 +1186,7 @@ def merge(self, unique=True):
 
         Parameters
         ----------
-        unique :
+        unique : bool, default=True
             If True, raises `iris.exceptions.DuplicateDataError` if
             duplicate cubes are detected.
 
@@ -1294,7 +1294,7 @@ def register(self, cube, error_on_mismatch=False):
         cube :
             Candidate :class:`iris.cube.Cube` to be associated with
             this :class:`ProtoCube`.
-        error_on_mismatch :bool,  optional, default=False
+        error_on_mismatch :bool, default=False
             If True, raise an informative
             :class:`~iris.exceptions.MergeError` if registration fails.
 

lib/iris/analysis/_area_weighted.py

@@ -29,7 +29,7 @@ def __init__(self, src_grid_cube, target_grid_cube, mdtol=1):
             The :class:`~iris.cube.Cube` providing the source grid.
         target_grid_cube : :class:`~iris.cube.Cube`
             The :class:`~iris.cube.Cube` providing the target grid.
-        mdtol : float, optional
+        mdtol : float, default=1
             Tolerance of missing data. The value returned in each element of
             the returned array will be masked if the fraction of masked data
             exceeds mdtol. mdtol=0 means no missing data is tolerated while

lib/iris/analysis/_interpolation.py

@@ -123,7 +123,7 @@ def get_xy_coords(cube, dim_coords=False):
     ----------
     cube : :class:`iris.cube.Cube`
         An instance of :class:`iris.cube.Cube`.
-    dim_coords : bool, optional, default=False
+    dim_coords : bool, default=False
         Set this to True to only return dimension coordinates. Defaults to
         False.
 
@@ -482,7 +482,7 @@ def _points(self, sample_points, data, data_dims=None):
             The data to interpolate - not necessarily the data from the cube
             that was used to construct this interpolator. If the data has
             fewer dimensions, then data_dims must be defined.
-        data_dims : optional, default=None
+        data_dims : optional
             The dimensions of the given data array in terms of the original
             cube passed through to this interpolator's constructor. If None,
             the data dimensions must map one-to-one onto the increasing
@@ -574,7 +574,7 @@ def __call__(self, sample_points, collapse_scalar=True):
             A list of N iterables, where N is the number of coordinates
             passed to the constructor.
             [sample_values_for_coord_0, sample_values_for_coord_1, ...]
-        collapse_scalar : bool, optional
+        collapse_scalar : bool, default=True
             Whether to collapse the dimension of the scalar sample points
             in the resulting cube. Default is True.
 

lib/iris/analysis/_regrid.py

@@ -384,7 +384,7 @@ def __init__(self, src_grid_cube, target_grid_cube, weights=None):
             The :class:`~iris.cube.Cube` providing the source grid.
         tgt_grid_cube : :class:`~iris.cube.Cube`
             The :class:`~iris.cube.Cube` providing the target grid.
-        weights : optional, default=None
+        weights : optional
             A :class:`numpy.ndarray` instance that defines the weights
             for the grid cells of the source grid. Must have the same shape
             as the data of the source grid.
@@ -636,9 +636,9 @@ def _regrid(
             A 2-dimensional array of sample X values.
         sample_grid_y :
             A 2-dimensional array of sample Y values.
-        method: str, optional
+        method: str, default="linear"
             Either 'linear' or 'nearest'. The default method is 'linear'.
-        extrapolation_mode : str, optional
+        extrapolation_mode : str, default="nanmask"
             Must be one of the following strings:
 
             * 'linear' - The extrapolation points will be calculated by
@@ -656,7 +656,7 @@ def _regrid(
 
         Returns
         -------
-        NumPu array
+        NumPy array
             The regridded data as an N-dimensional NumPy array. The lengths
             of the X and Y dimensions will now match those of the sample
             grid.

lib/iris/analysis/cartography.py

@@ -205,7 +205,7 @@ def _xy_range(cube, mode=None):
     ----------
     cube :
         The cube for which to calculate xy extents.
-    mode : optional, default=None
+    mode : optional
         If the coordinate has bounds, set this to specify the
         min/max calculation.
         Set to iris.coords.POINT_MODE or iris.coords.BOUND_MODE.
@@ -397,7 +397,7 @@ def area_weights(cube, normalize=False):
     ----------
     cube : :class:`iris.cube.Cube`
         The cube to calculate area weights for.
-    normalize : bool, optional, default=False
+    normalize : bool, default=False
         If False, weights are grid cell areas. If True, weights are grid
         cell areas divided by the total grid area.
 
@@ -605,10 +605,10 @@ def project(cube, target_proj, nx=None, ny=None):
         An instance of the Cartopy Projection class, or an instance of
         :class:`iris.coord_systems.CoordSystem` from which a projection
         will be obtained.
-    nx : optional, default=None
+    nx : optional
         Desired number of sample points in the x direction for a domain
         covering the globe.
-    ny : optional, default=None
+    ny : optional
         Desired number of sample points in the y direction for a domain
         covering the globe.
 

lib/iris/analysis/geometry.py

@@ -163,17 +163,14 @@ def geometry_area_weights(cube, geometry, normalize=False):
         This function does not maintain laziness when called; it realises data.
         See more at :doc:`/userguide/real_and_lazy_data`.
 
-    Args:
-
-    * cube (:class:`iris.cube.Cube`):
+    Parameters
+    ----------
+    cube : :class:`iris.cube.Cube`
         A Cube containing a bounded, horizontal grid definition.
-    * geometry (a shapely geometry instance):
+    geometry : shapely geometry instance
         The geometry of interest. To produce meaningful results this geometry
         must have a non-zero area. Typically a Polygon or MultiPolygon.
-
-    Kwargs:
-
-    * normalize:
+    normalize : bool, default=False
         Calculate each individual cell weight as the cell area overlap between
         the cell and the given shapely geometry divided by the total cell area.
         Default is False.