def test_365_calendar(self):
f = mock.MagicMock(lbtim=SplittableInt(4, {
'ia': 2,
'ib': 1,
'ic': 0
}),
lbyr=2013,
lbmon=1,
lbdat=1,
lbhr=12,
lbmin=0,
lbsec=0,
spec=PPField3)
f.time_unit = types.MethodType(PPField3.time_unit, f)
f.calendar = iris.unit.CALENDAR_365_DAY
(factories, references, standard_name, long_name, units, attributes,
cell_methods, dim_coords_and_dims, aux_coords_and_dims) = convert(f)
def is_t_coord(coord_and_dims):
coord, dims = coord_and_dims
return coord.standard_name == 'time'
coords_and_dims = filter(is_t_coord, aux_coords_and_dims)
self.assertEqual(len(coords_and_dims), 1)
coord, dims = coords_and_dims[0]
self.assertEqual(guess_coord_axis(coord), 'T')
self.assertEqual(coord.units.calendar, '365_day')
def key_func(coord):
return (
axes.get(guess_coord_axis(coord),
len(axes) + 1),
coord.name(),
cube.coord_dims(coord),
)
def test_365_calendar(self):
f = mock.MagicMock(
lbtim=SplittableInt(4, {"ia": 2, "ib": 1, "ic": 0}),
lbyr=2013,
lbmon=1,
lbdat=1,
lbhr=12,
lbmin=0,
lbsec=0,
spec=PPField3,
)
f.time_unit = six.create_bound_method(PPField3.time_unit, f)
f.calendar = cf_units.CALENDAR_365_DAY
(
factories,
references,
standard_name,
long_name,
units,
attributes,
cell_methods,
dim_coords_and_dims,
aux_coords_and_dims,
) = convert(f)
def is_t_coord(coord_and_dims):
coord, dims = coord_and_dims
return coord.standard_name == "time"
coords_and_dims = list(filter(is_t_coord, aux_coords_and_dims))
self.assertEqual(len(coords_and_dims), 1)
coord, dims = coords_and_dims[0]
self.assertEqual(guess_coord_axis(coord), "T")
self.assertEqual(coord.units.calendar, "365_day")
def __init__(self, cube):
"""
Represents the cube metadata and associated coordinate metadata that
allows suitable cubes for concatenation to be identified.
Args:
* cube:
The :class:`iris.cube.Cube` source-cube.
"""
self.aux_coords_and_dims = []
self.aux_metadata = []
self.dim_coords = cube.dim_coords
self.dim_metadata = []
self.mdi = None
self.ndim = cube.ndim
self.scalar_coords = []
# Determine whether there are any anonymous cube dimensions.
covered = set(cube.coord_dims(coord)[0] for coord in self.dim_coords)
self.anonymous = covered != set(range(self.ndim))
self.defn = cube.metadata
self.data_type = cube.data.dtype
if ma.isMaskedArray(cube.data):
# Only set when we're dealing with a masked payload.
self.mdi = cube.data.fill_value
#
# Collate the dimension coordinate metadata.
#
for coord in self.dim_coords:
metadata = _CoordMetaData(coord, cube.coord_dims(coord))
self.dim_metadata.append(metadata)
#
# Collate the auxiliary coordinate metadata and scalar coordinates.
#
axes = dict(T=0, Z=1, Y=2, X=3)
# Coordinate sort function - by guessed coordinate axis, then
# by coordinate definition, then by dimensions, in ascending order.
key_func = lambda coord: (axes.get(guess_coord_axis(coord),
len(axes) + 1),
coord._as_defn(),
cube.coord_dims(coord))
for coord in sorted(cube.aux_coords, key=key_func):
dims = cube.coord_dims(coord)
if dims:
metadata = _CoordMetaData(coord, dims)
self.aux_metadata.append(metadata)
coord_and_dims = _CoordAndDims(coord, tuple(dims))
self.aux_coords_and_dims.append(coord_and_dims)
else:
self.scalar_coords.append(coord)
def __init__(self, cube):
"""
Represents the cube metadata and associated coordinate metadata that
allows suitable cubes for concatenation to be identified.
Args:
* cube:
The :class:`iris.cube.Cube` source-cube.
"""
self.aux_coords_and_dims = []
self.aux_metadata = []
self.dim_coords = cube.dim_coords
self.dim_metadata = []
self.mdi = None
self.ndim = cube.ndim
self.scalar_coords = []
# Determine whether there are any anonymous cube dimensions.
covered = set(cube.coord_dims(coord)[0] for coord in self.dim_coords)
self.anonymous = covered != set(range(self.ndim))
self.defn = cube.metadata
self.data_type = cube.data.dtype
if ma.isMaskedArray(cube.data):
# Only set when we're dealing with a masked payload.
self.mdi = cube.data.fill_value
#
# Collate the dimension coordinate metadata.
#
for coord in self.dim_coords:
metadata = _CoordMetaData(coord, cube.coord_dims(coord))
self.dim_metadata.append(metadata)
#
# Collate the auxiliary coordinate metadata and scalar coordinates.
#
axes = dict(T=0, Z=1, Y=2, X=3)
# Coordinate sort function - by guessed coordinate axis, then
# by coordinate definition, then by dimensions, in ascending order.
key_func = lambda coord: (axes.get(guess_coord_axis(coord),
len(axes) + 1),
coord._as_defn(),
cube.coord_dims(coord))
for coord in sorted(cube.aux_coords, key=key_func):
dims = cube.coord_dims(coord)
if dims:
metadata = _CoordMetaData(coord, dims)
self.aux_metadata.append(metadata)
coord_and_dims = _CoordAndDims(coord, tuple(dims))
self.aux_coords_and_dims.append(coord_and_dims)
else:
self.scalar_coords.append(coord)
def sort_coords(coord):
"""
Sorts a list of DimCoords trying to ensure that
dates and pressure levels appear first and the
longitude and latitude appear last in the correct
order.
"""
order = {'T': -2, 'Z': -1, 'X': 1, 'Y': 2}
axis = guess_coord_axis(coord)
return (order.get(axis, 0), coord and coord.name())
def sort_coords(coord):
"""
Sorts a list of DimCoords trying to ensure that
dates and pressure levels appear first and the
longitude and latitude appear last in the correct
order.
"""
order = {'T': -2, 'Z': -1, 'X': 1, 'Y': 2}
axis = guess_coord_axis(coord)
return (order.get(axis, 0), coord and coord.name())
def transform(self):
# Modify the attribute 'positive' so the 'guess' function
# won't recognize the 'soil_level' as axis Z
for cube in self._cubes:
if cube.coords('soil_model_level_number'):
coord = cube.coord('soil_model_level_number')
if coord.attributes:
coord.attributes.pop('positive')
guess_coord_axis(coord)
# This handles the depth below land surface
if cube.coords('depth'):
coord = cube.coord('depth')
if coord.attributes:
coord.attributes.pop('positive')
guess_coord_axis(coord)
# Make cfdata be consitent with iris CF_GRIB2_TABLE
if 'type_cloud_area_fraction' in cube.name():
cube.units = '%'
if cube.name() == 'soil_moisture_content':
cube.units = 'kg m-2'
if cube.name() == 'canopy_water_amount':
cube.units = 'kg m-2'
def test_soil_levels(self):
field = mock.MagicMock(lbvc=6, blev=1234)
(factories, references, standard_name, long_name, units,
attributes, cell_methods, dim_coords_and_dims,
aux_coords_and_dims) = convert(field)
def is_model_level_coord(coord_and_dims):
coord, dims = coord_and_dims
return coord.standard_name == 'model_level_number'
coords_and_dims = filter(is_model_level_coord, aux_coords_and_dims)
self.assertEqual(len(coords_and_dims), 1)
coord, dims = coords_and_dims[0]
self.assertEqual(coord.points, 1234)
self.assertIsNone(coord.bounds)
self.assertEqual(guess_coord_axis(coord), 'Z')
def test_potential_temperature_levels(self):
potm_value = 27.32
field = mock.MagicMock(lbvc=19, blev=potm_value)
(factories, references, standard_name, long_name, units,
attributes, cell_methods, dim_coords_and_dims,
aux_coords_and_dims) = convert(field)
def is_potm_level_coord(coord_and_dims):
coord, dims = coord_and_dims
return coord.standard_name == 'air_potential_temperature'
coords_and_dims = filter(is_potm_level_coord, aux_coords_and_dims)
self.assertEqual(len(coords_and_dims), 1)
coord, dims = coords_and_dims[0]
self.assertArrayEqual(coord.points, [potm_value])
self.assertIsNone(coord.bounds)
self.assertEqual(guess_coord_axis(coord), 'Z')
def test_365_calendar(self):
f = mock.MagicMock(lbtim=SplittableInt(4, {'ia': 2, 'ib': 1, 'ic': 0}),
lbyr=2013, lbmon=1, lbdat=1, lbhr=12, lbmin=0,
lbsec=0,
spec=PPField3)
f.time_unit = types.MethodType(PPField3.time_unit, f)
f.calendar = iris.unit.CALENDAR_365_DAY
(factories, references, standard_name, long_name, units,
attributes, cell_methods, dim_coords_and_dims,
aux_coords_and_dims) = convert(f)
def is_t_coord(coord_and_dims):
coord, dims = coord_and_dims
return coord.standard_name == 'time'
coords_and_dims = filter(is_t_coord, aux_coords_and_dims)
self.assertEqual(len(coords_and_dims), 1)
coord, dims = coords_and_dims[0]
self.assertEqual(guess_coord_axis(coord), 'T')
self.assertEqual(coord.units.calendar, '365_day')
def test_365_calendar(self):
f = mock.MagicMock(
lbtim=SplittableInt(4, {
"ia": 2,
"ib": 1,
"ic": 0
}),
lbyr=2013,
lbmon=1,
lbdat=1,
lbhr=12,
lbmin=0,
lbsec=0,
t1=cftime.datetime(2013, 1, 1, 12, 0, 0),
t2=cftime.datetime(2013, 1, 2, 12, 0, 0),
spec=PPField3,
)
f.time_unit = MethodType(PPField3.time_unit, f)
f.calendar = cf_units.CALENDAR_365_DAY
(
factories,
references,
standard_name,
long_name,
units,
attributes,
cell_methods,
dim_coords_and_dims,
aux_coords_and_dims,
) = convert(f)
def is_t_coord(coord_and_dims):
coord, dims = coord_and_dims
return coord.standard_name == "time"
coords_and_dims = list(filter(is_t_coord, aux_coords_and_dims))
self.assertEqual(len(coords_and_dims), 1)
coord, dims = coords_and_dims[0]
self.assertEqual(guess_coord_axis(coord), "T")
self.assertEqual(coord.units.calendar, "365_day")
def get_dim_coord(cube, axis):
"""
Return a coordinate from a cube based on the axis it represents.
Uses :py:func:`iris.util.guess_coord_axis` to heuristically match a dimensional coordinate
with the requested axis.
Adapted from https://github.com/LSaffin/iris-extensions
Parameters
----------
cube: iris.cube.Cube
Cube with the desired coordinate.
axis: str
The co-ordinate axis to take from the cube. Must be one of X, Y, Z, T.
Returns
-------
iris.coords.DimCoord
The dimensional coordinate matching the requested axis on the given cube.
Raises
------
ArgumentError: If axis is not one of {X, Y, Z, T}.
NotFoundError: If the cube does not contain a coord with the requested axis.
"""
_allowed = ["X", "Y", "Z", "T"]
axis = axis.upper()
# If the axis supplied is not correct raise an error
if axis not in _allowed:
raise ArgumentError(f"Axis must be one of {_allowed}, {axis} is given.")
# Loop over dimensional coords in the cube
for coord in cube.dim_coords:
# Return the coordinate if it matches the axis
if axis == guess_coord_axis(coord):
return coord
# If no coordinate matches raise an error
raise NotFoundError(f"Cube has no coordinate for axis {axis}")
def key_func(coord):
return (axes.get(guess_coord_axis(coord), len(axes) + 1),
coord._as_defn(),
cube.coord_dims(coord))