def test_coord_with_string_points(self):
# Check that a `TypeError` is captured.
coord = AuxCoord(["a", "b", "c"])
result = is_regular(coord)
self.assertFalse(result)
def build_spotdata_cube(
data,
name,
units,
altitude,
latitude,
longitude,
wmo_id,
scalar_coords=None,
neighbour_methods=None,
grid_attributes=None,
additional_dims=None,
):
"""
Function to build a spotdata cube with expected dimension and auxiliary
coordinate structure.
It can be used to create spot data cubes. In this case the data is the
spot data values at each site, and the coordinates that describe each site.
It can also be used to create cubes which describe the grid points that are
used to extract each site from a gridded field, for different selection
method. The selection methods are specified by the neighbour_methods
coordinate. The grid_attribute coordinate encapsulates information required
to extract data, for example the x/y indices that identify the grid point
neighbour.
.. See the documentation for examples of these cubes.
.. include:: extended_documentation/spotdata/build_spotdata_cube/
build_spotdata_cube_examples.rst
Args:
data (float or numpy.ndarray):
Float spot data or array of data points from several sites.
The spot index should be the last dimension if the array is
multi-dimensional (see optional additional dimensions below).
name (str):
Cube name (eg 'air_temperature')
units (str):
Cube units (eg 'K')
altitude (float or numpy.ndarray):
Float or 1d array of site altitudes in metres
latitude (float or numpy.ndarray):
Float or 1d array of site latitudes in degrees
longitude (float or numpy.ndarray):
Float or 1d array of site longitudes in degrees
wmo_id (str or list of str):
String or list of site 5-digit WMO identifiers
scalar_coords (list of iris.coords.AuxCoord):
Optional list of iris.coords.AuxCoord instances
neighbour_methods (list of str):
Optional list of neighbour method names, e.g. 'nearest'
grid_attributes (list of str):
Optional list of grid attribute names, e.g. x-index, y-index
additional_dims (list of iris.coords.DimCoord):
Optional list of additional dimensions to preceed the spot data dimension.
Returns:
iris.cube.Cube:
A cube containing the extracted spot data with spot data being the final dimension.
"""
# construct auxiliary coordinates
alt_coord = AuxCoord(altitude, "altitude", units="m")
lat_coord = AuxCoord(latitude, "latitude", units="degrees")
lon_coord = AuxCoord(longitude, "longitude", units="degrees")
id_coord = AuxCoord(wmo_id, long_name="wmo_id", units="no_unit")
aux_coords_and_dims = []
# append scalar coordinates
if scalar_coords is not None:
for coord in scalar_coords:
aux_coords_and_dims.append((coord, None))
# construct dimension coordinates
if np.isscalar(data):
data = np.array([data])
spot_index = DimCoord(np.arange(data.shape[-1], dtype=np.int32),
long_name="spot_index",
units="1")
dim_coords_and_dims = []
current_dim = 0
if neighbour_methods is not None:
neighbour_methods_coord = DimCoord(
np.arange(len(neighbour_methods), dtype=np.int32),
long_name="neighbour_selection_method",
units="1",
)
neighbour_methods_key = AuxCoord(
neighbour_methods,
long_name="neighbour_selection_method_name",
units="no_unit",
)
dim_coords_and_dims.append((neighbour_methods_coord, current_dim))
aux_coords_and_dims.append((neighbour_methods_key, current_dim))
current_dim += 1
if grid_attributes is not None:
grid_attributes_coord = DimCoord(
np.arange(len(grid_attributes), dtype=np.int32),
long_name="grid_attributes",
units="1",
)
grid_attributes_key = AuxCoord(grid_attributes,
long_name="grid_attributes_key",
units="no_unit")
dim_coords_and_dims.append((grid_attributes_coord, current_dim))
aux_coords_and_dims.append((grid_attributes_key, current_dim))
current_dim += 1
if additional_dims is not None:
for coord in additional_dims:
dim_coords_and_dims.append((coord, current_dim))
current_dim += 1
dim_coords_and_dims.append((spot_index, current_dim))
for coord in [alt_coord, lat_coord, lon_coord, id_coord]:
aux_coords_and_dims.append((coord, current_dim))
# create output cube
spot_cube = iris.cube.Cube(
data,
long_name=name,
units=units,
dim_coords_and_dims=dim_coords_and_dims,
aux_coords_and_dims=aux_coords_and_dims,
)
# rename to force a standard name to be set if name is valid
spot_cube.rename(name)
return spot_cube
def test_numpy_scalar_coord__zero_ndim(self):
points = np.array(1)
coord = AuxCoord(points)
result = AuxCoordFactory._nd_points(coord, (), 0)
expected = np.array([1])
self.assertArrayEqual(result, expected)
def _generate_cubes(header, column_headings, coords, data_arrays,
cell_methods=None):
"""
Yield :class:`iris.cube.Cube` instances given
the headers, column headings, coords and data_arrays extracted
from a NAME file.
"""
for i, data_array in enumerate(data_arrays):
# Turn the dictionary of column headings with a list of header
# information for each field into a dictionary of headings for
# just this field.
field_headings = {k: v[i] for k, v in six.iteritems(column_headings)}
# Make a cube.
cube = iris.cube.Cube(data_array)
# Determine the name and units.
name = '{} {}'.format(field_headings['Species'],
field_headings['Quantity'])
name = name.upper().replace(' ', '_')
cube.rename(name)
# Some units are not in SI units, are missing spaces or typed
# in the wrong case. _parse_units returns units that are
# recognised by Iris.
cube.units = _parse_units(field_headings['Units'])
# Define and add the singular coordinates of the field (flight
# level, time etc.)
if 'Z' in field_headings:
upper_bound, = [field_headings['... to [Z]']
if '... to [Z]' in field_headings else None]
lower_bound, = [field_headings['... from [Z]']
if '... from [Z]' in field_headings else None]
z_coord = _cf_height_from_name(field_headings['Z'],
upper_bound=upper_bound,
lower_bound=lower_bound)
cube.add_aux_coord(z_coord)
# Define the time unit and use it to serialise the datetime for
# the time coordinate.
time_unit = cf_units.Unit(
'hours since epoch', calendar=cf_units.CALENDAR_GREGORIAN)
# Build time, height, latitude and longitude coordinates.
for coord in coords:
pts = coord.values
coord_sys = None
if coord.name == 'latitude' or coord.name == 'longitude':
coord_units = 'degrees'
coord_sys = iris.coord_systems.GeogCS(EARTH_RADIUS)
if coord.name == 'height':
coord_units = 'm'
long_name = 'height above ground level'
pts = coord.values
if coord.name == 'altitude':
coord_units = 'm'
long_name = 'altitude above sea level'
pts = coord.values
if coord.name == 'air_pressure':
coord_units = 'Pa'
pts = coord.values
if coord.name == 'flight_level':
pts = coord.values
long_name = 'flight_level'
coord_units = _parse_units('FL')
if coord.name == 'time':
coord_units = time_unit
pts = time_unit.date2num(coord.values)
if coord.dimension is not None:
if coord.name == 'longitude':
circular = iris.util._is_circular(pts, 360.0)
else:
circular = False
if coord.name == 'flight_level':
icoord = DimCoord(points=pts,
units=coord_units,
long_name=long_name,)
else:
icoord = DimCoord(points=pts,
standard_name=coord.name,
units=coord_units,
coord_system=coord_sys,
circular=circular)
if coord.name == 'height' or coord.name == 'altitude':
icoord.long_name = long_name
if coord.name == 'time' and 'Av or Int period' in \
field_headings:
dt = coord.values - \
field_headings['Av or Int period']
bnds = time_unit.date2num(
np.vstack((dt, coord.values)).T)
icoord.bounds = bnds
else:
icoord.guess_bounds()
cube.add_dim_coord(icoord, coord.dimension)
else:
icoord = AuxCoord(points=pts[i],
standard_name=coord.name,
coord_system=coord_sys,
units=coord_units)
if coord.name == 'time' and 'Av or Int period' in \
field_headings:
dt = coord.values - \
field_headings['Av or Int period']
bnds = time_unit.date2num(
np.vstack((dt, coord.values)).T)
icoord.bounds = bnds[i, :]
cube.add_aux_coord(icoord)
# Headings/column headings which are encoded elsewhere.
headings = ['X', 'Y', 'Z', 'Time', 'T', 'Units',
'Av or Int period',
'... from [Z]', '... to [Z]',
'X grid origin', 'Y grid origin',
'X grid size', 'Y grid size',
'X grid resolution', 'Y grid resolution',
'Number of field cols', 'Number of preliminary cols',
'Number of fields', 'Number of series',
'Output format', ]
# Add the Main Headings as attributes.
for key, value in six.iteritems(header):
if value is not None and value != '' and \
key not in headings:
cube.attributes[key] = value
# Add the Column Headings as attributes
for key, value in six.iteritems(field_headings):
if value is not None and value != '' and \
key not in headings:
cube.attributes[key] = value
if cell_methods is not None:
cube.add_cell_method(cell_methods[i])
yield cube
def setUp(self):
super(TestGraphicStringCoord, self).setUp()
self.cube = simple_2d(with_bounds=True)
self.cube.add_aux_coord(AuxCoord(list('abcd'), long_name='str_coord'),
1)
def _convert_vertical_coords(lbcode,
lbvc,
blev,
lblev,
stash,
bhlev,
bhrlev,
brsvd1,
brsvd2,
brlev,
dim=None):
"""
Encode scalar or vector vertical level values from PP headers as CM data
components.
Args:
* lbcode:
Scalar field :class:`iris.fileformats.pp.SplittableInt` value.
* lbvc:
Scalar field value.
* blev:
Scalar field value or :class:`numpy.ndarray` vector of field values.
* lblev:
Scalar field value or :class:`numpy.ndarray` vector of field values.
* stash:
Scalar field :class:`iris.fileformats.pp.STASH` value.
* bhlev:
Scalar field value or :class:`numpy.ndarray` vector of field values.
* bhrlev:
Scalar field value or :class:`numpy.ndarray` vector of field values.
* brsvd1:
Scalar field value or :class:`numpy.ndarray` vector of field values.
* brsvd2:
Scalar field value or :class:`numpy.ndarray` vector of field values.
* brlev:
Scalar field value or :class:`numpy.ndarray` vector of field values.
Kwargs:
* dim:
Associated dimension of the vertical coordinate. Defaults to None.
Returns:
A tuple containing a list of coords_and_dims, and a list of factories.
"""
factories = []
coords_and_dims = []
# See Word no. 33 (LBLEV) in section 4 of UM Model Docs (F3).
BASE_RHO_LEVEL_LBLEV = 9999
model_level_number = np.atleast_1d(lblev)
model_level_number[model_level_number == BASE_RHO_LEVEL_LBLEV] = 0
# Ensure to vectorise these arguments as arrays, as they participate
# in the conditions of convert rules.
blev = np.atleast_1d(blev)
brsvd1 = np.atleast_1d(brsvd1)
brlev = np.atleast_1d(brlev)
# Height.
if (lbvc == 1) and \
str(stash) not in STASHCODE_IMPLIED_HEIGHTS and \
np.all(blev != -1):
coord = _dim_or_aux(blev,
standard_name='height',
units='m',
attributes={'positive': 'up'})
coords_and_dims.append((coord, dim))
if str(stash) in STASHCODE_IMPLIED_HEIGHTS:
height = STASHCODE_IMPLIED_HEIGHTS[str(stash)]
coord = DimCoord(height,
standard_name='height',
units='m',
attributes={'positive': 'up'})
coords_and_dims.append((coord, None))
# Model level number.
if (len(lbcode) != 5) and \
(lbvc == 2):
coord = _dim_or_aux(model_level_number,
standard_name='model_level_number',
attributes={'positive': 'down'})
coords_and_dims.append((coord, dim))
# Depth - unbound.
if (len(lbcode) != 5) and \
(lbvc == 2) and \
np.all(brsvd1 == brlev):
coord = _dim_or_aux(blev,
standard_name='depth',
units='m',
attributes={'positive': 'down'})
coords_and_dims.append((coord, dim))
# Depth - bound.
if (len(lbcode) != 5) and \
(lbvc == 2) and \
np.all(brsvd1 != brlev):
coord = _dim_or_aux(blev,
standard_name='depth',
units='m',
bounds=np.vstack((brsvd1, brlev)).T,
attributes={'positive': 'down'})
coords_and_dims.append((coord, dim))
# Depth - unbound and bound (mixed).
if (len(lbcode) != 5) and \
(lbvc == 2) and \
(np.any(brsvd1 == brlev) and np.any(brsvd1 != brlev)):
lower = np.where(brsvd1 == brlev, blev, brsvd1)
upper = np.where(brsvd1 == brlev, blev, brlev)
coord = _dim_or_aux(blev,
standard_name='depth',
units='m',
bounds=np.vstack((lower, upper)).T,
attributes={'positive': 'down'})
coords_and_dims.append((coord, dim))
# Soil level/depth.
if len(lbcode) != 5 and lbvc == 6:
if np.all(brsvd1 == 0) and np.all(brlev == 0):
# UM populates lblev, brsvd1 and brlev metadata INCORRECTLY,
# so continue to treat as a soil level.
coord = _dim_or_aux(model_level_number,
long_name='soil_model_level_number',
attributes={'positive': 'down'})
coords_and_dims.append((coord, dim))
elif np.any(brsvd1 != brlev):
# UM populates metadata CORRECTLY,
# so treat it as the expected (bounded) soil depth.
coord = _dim_or_aux(blev,
standard_name='depth',
units='m',
bounds=np.vstack((brsvd1, brlev)).T,
attributes={'positive': 'down'})
coords_and_dims.append((coord, dim))
# Pressure.
if (lbvc == 8) and \
(len(lbcode) != 5 or (len(lbcode) == 5 and
1 not in [lbcode.ix, lbcode.iy])):
coord = _dim_or_aux(blev, long_name='pressure', units='hPa')
coords_and_dims.append((coord, dim))
# Air potential temperature.
if (len(lbcode) != 5) and \
(lbvc == 19):
coord = _dim_or_aux(blev,
standard_name='air_potential_temperature',
units='K',
attributes={'positive': 'up'})
coords_and_dims.append((coord, dim))
# Hybrid pressure levels.
if lbvc == 9:
model_level_number = _dim_or_aux(model_level_number,
standard_name='model_level_number',
attributes={'positive': 'up'})
level_pressure = _dim_or_aux(bhlev,
long_name='level_pressure',
units='Pa',
bounds=np.vstack((bhrlev, brsvd2)).T)
sigma = AuxCoord(blev,
long_name='sigma',
bounds=np.vstack((brlev, brsvd1)).T)
coords_and_dims.extend([(model_level_number, dim),
(level_pressure, dim), (sigma, dim)])
factories.append(
Factory(HybridPressureFactory,
[{
'long_name': 'level_pressure'
}, {
'long_name': 'sigma'
},
Reference('surface_air_pressure')]))
# Hybrid height levels.
if lbvc == 65:
model_level_number = _dim_or_aux(model_level_number,
standard_name='model_level_number',
attributes={'positive': 'up'})
level_height = _dim_or_aux(blev,
long_name='level_height',
units='m',
bounds=np.vstack((brlev, brsvd1)).T,
attributes={'positive': 'up'})
sigma = AuxCoord(bhlev,
long_name='sigma',
bounds=np.vstack((bhrlev, brsvd2)).T)
coords_and_dims.extend([(model_level_number, dim), (level_height, dim),
(sigma, dim)])
factories.append(
Factory(HybridHeightFactory, [{
'long_name': 'level_height'
}, {
'long_name': 'sigma'
},
Reference('orography')]))
return coords_and_dims, factories
def load_NAMEIII_trajectory(filename):
"""
Load a NAME III trajectory file returning a
generator of :class:`iris.cube.Cube` instances.
Args:
* filename (string):
Name of file to load.
Returns:
A generator :class:`iris.cube.Cube` instances.
"""
time_unit = cf_units.Unit('hours since epoch',
calendar=cf_units.CALENDAR_GREGORIAN)
with open(filename, 'r') as infile:
header = read_header(infile)
# read the column headings
for line in infile:
if line.startswith(" "):
break
headings = [heading.strip() for heading in line.split(",")]
# read the columns
columns = [[] for i in range(len(headings))]
for line in infile:
values = [v.strip() for v in line.split(",")]
for c, v in enumerate(values):
if "UTC" in v:
v = v.replace(":00 ", " ") # Strip out milliseconds.
v = datetime.datetime.strptime(v, NAMEIII_DATETIME_FORMAT)
else:
try:
v = float(v)
except ValueError:
pass
columns[c].append(v)
# Where's the Z column?
z_column = None
for i, heading in enumerate(headings):
if heading.startswith("Z "):
z_column = i
break
if z_column is None:
raise TranslationError("Expected a Z column")
# Every column up to Z becomes a coordinate.
coords = []
for name, values in zip(headings[:z_column+1], columns[:z_column+1]):
values = np.array(values)
if np.all(np.array(values) == values[0]):
values = [values[0]]
standard_name = long_name = units = None
if isinstance(values[0], datetime.datetime):
values = time_unit.date2num(values)
units = time_unit
if name == "Time":
name = "time"
elif " (Lat-Long)" in name:
if name.startswith("X"):
name = "longitude"
elif name.startswith("Y"):
name = "latitude"
units = "degrees"
elif name == "Z (m asl)":
name = "altitude"
units = "m"
long_name = "altitude above sea level"
elif name == "Z (m agl)":
name = 'height'
units = "m"
long_name = "height above ground level"
elif name == "Z (FL)":
name = "flight_level"
long_name = name
try:
coord = DimCoord(values, units=units)
except ValueError:
coord = AuxCoord(values, units=units)
coord.rename(name)
if coord.long_name is None and long_name is not None:
coord.long_name = long_name
coords.append(coord)
# Every numerical column after the Z becomes a cube.
for name, values in zip(headings[z_column+1:], columns[z_column+1:]):
try:
float(values[0])
except ValueError:
continue
# units embedded in column heading?
name, units = _split_name_and_units(name)
cube = iris.cube.Cube(values, units=units)
cube.rename(name)
for coord in coords:
dim = 0 if len(coord.points) > 1 else None
if isinstance(coord, DimCoord) and coord.name() == "time":
cube.add_dim_coord(coord.copy(), dim)
else:
cube.add_aux_coord(coord.copy(), dim)
yield cube
def test_coord_long_name(self):
token = "long_name"
coord = AuxCoord(1, long_name=token)
self._check(token, coord)
def test_coord_long_name_default(self):
token = "long name" # includes space
coord = AuxCoord(1, long_name=token)
self._check(token, coord, default=True)
def get_cube(name, lat=((0, 1), (2, 3)), lon=((0, 1), (2, 3))):
cube = Cube(np.ones((2, 2)), name)
cube.add_aux_coord(AuxCoord(lat, 'latitude'), (0, 1))
cube.add_aux_coord(AuxCoord(lon, 'longitude'), (0, 1))
return cube
def test_coord_standard_name(self):
token = "air_temperature"
coord = AuxCoord(1, standard_name=token)
self._check(token, coord)
def test_get_allvars_fix():
"""Test getting of fix."""
fix = Fix.get_fixes('CMIP5', 'FGOALS-s2', 'Amon', 'tas')
assert fix == [AllVars(None)]
LAT_COORD = DimCoord(
[-20.0, 0.0, 10.0],
bounds=[[-30.0, -10.0], [-10.0, 5.0], [5.0, 20.0]],
var_name='lat',
standard_name='latitude',
)
LAT_COORD_MULT = AuxCoord(
[[-20.0], [0.0], [10.0]],
bounds=[[[-30.0, -10.0]], [[-10.0, 5.0]], [[5.0, 20.0]]],
var_name='lat',
standard_name='latitude',
)
LAT_COORD_SMALL = DimCoord([0.0],
bounds=[-45.0, 45.0],
var_name='lat',
standard_name='latitude')
def test_allvars_fix_metadata():
"""Test ``fix_metadata`` for all variables."""
cubes = CubeList([
Cube([1, 2, 3], dim_coords_and_dims=[(LAT_COORD.copy(), 0)]),
Cube([[1], [2], [3]],
aux_coords_and_dims=[(LAT_COORD_MULT.copy(), (0, 1))]),
Cube([1], dim_coords_and_dims=[(LAT_COORD_SMALL.copy(), 0)]),
def test_coord_with_irregular_step(self):
name = "latitude"
coord = AuxCoord(np.array([2, 5, 1, 4]), standard_name=name)
exp_emsg = "{} is not regular".format(name)
with self.assertRaisesRegex(CoordinateNotRegularError, exp_emsg):
regular_step(coord)
def test_2d_coord(self):
coord = AuxCoord(np.arange(8).reshape(2, 4))
exp_emsg = "Expected 1D coord"
with self.assertRaisesRegex(CoordinateMultiDimError, exp_emsg):
regular_step(coord)
def _make_cube_3d(x, y, z, data, aux=None, offset=0):
"""
A convenience test function that creates a custom 3D cube.
Args:
* x:
A (start, stop, step) tuple for specifying the
x-axis dimensional coordinate points. Bounds are
automatically guessed.
* y:
A (start, stop, step) tuple for specifying the
y-axis dimensional coordinate points. Bounds are
automatically guessed.
* z:
A (start, stop, step) tuple for specifying the
z-axis dimensional coordinate points. Bounds are
automatically guessed.
* data:
The data payload for the cube.
Kwargs:
* aux:
A CSV string specifying which points only auxiliary
coordinates to create. Accepts either of 'x', 'y', 'z',
'xy', 'xz', 'yz', 'xyz'.
* offset:
Offset value to be added to non-1D auxiliary coordinate
points.
Returns:
The newly created 3D :class:`iris.cube.Cube`.
"""
x_range = np.arange(*x, dtype=np.float32)
y_range = np.arange(*y, dtype=np.float32)
z_range = np.arange(*z, dtype=np.float32)
x_size, y_size, z_size = len(x_range), len(y_range), len(z_range)
cube_data = np.empty((x_size, y_size, z_size), dtype=np.float32)
cube_data[:] = data
cube = iris.cube.Cube(cube_data)
coord = DimCoord(z_range, long_name='z')
coord.guess_bounds()
cube.add_dim_coord(coord, 0)
coord = DimCoord(y_range, long_name='y')
coord.guess_bounds()
cube.add_dim_coord(coord, 1)
coord = DimCoord(x_range, long_name='x')
coord.guess_bounds()
cube.add_dim_coord(coord, 2)
if aux is not None:
aux = aux.split(',')
if 'z' in aux:
coord = AuxCoord(z_range * 10, long_name='z-aux')
cube.add_aux_coord(coord, (0, ))
if 'y' in aux:
coord = AuxCoord(y_range * 10, long_name='y-aux')
cube.add_aux_coord(coord, (1, ))
if 'x' in aux:
coord = AuxCoord(x_range * 10, long_name='x-aux')
cube.add_aux_coord(coord, (2, ))
if 'xy' in aux:
payload = np.arange(x_size * y_size,
dtype=np.float32).reshape(y_size, x_size)
coord = AuxCoord(payload + offset, long_name='xy-aux')
cube.add_aux_coord(coord, (1, 2))
if 'xz' in aux:
payload = np.arange(x_size * z_size,
dtype=np.float32).reshape(z_size, x_size)
coord = AuxCoord(payload * 10 + offset, long_name='xz-aux')
cube.add_aux_coord(coord, (0, 2))
if 'yz' in aux:
payload = np.arange(y_size * z_size,
dtype=np.float32).reshape(z_size, y_size)
coord = AuxCoord(payload * 100 + offset, long_name='yz-aux')
cube.add_aux_coord(coord, (0, 1))
if 'xyz' in aux:
payload = np.arange(x_size * y_size * z_size,
dtype=np.float32).reshape(
z_size, y_size, x_size)
coord = AuxCoord(payload * 1000 + offset, long_name='xyz-aux')
cube.add_aux_coord(coord, (0, 1, 2))
return cube
def test_coord_var_name(self):
token = "var_name"
coord = AuxCoord(1, var_name=token)
self._check(token, coord)
def _make_cube(x, y, data, aux=None, offset=0, scalar=None):
"""
A convenience test function that creates a custom 2D cube.
Args:
* x:
A (start, stop, step) tuple for specifying the
x-axis dimensional coordinate points. Bounds are
automatically guessed.
* y:
A (start, stop, step) tuple for specifying the
y-axis dimensional coordinate points. Bounds are
automatically guessed.
* data:
The data payload for the cube.
Kwargs:
* aux:
A CSV string specifying which points only auxiliary
coordinates to create. Accepts either of 'x', 'y', 'xy'.
* offset:
Offset value to be added to the 'xy' auxiliary coordinate
points.
* scalar:
Create a 'height' scalar coordinate with the given value.
Returns:
The newly created 2D :class:`iris.cube.Cube`.
"""
x_range = np.arange(*x, dtype=np.float32)
y_range = np.arange(*y, dtype=np.float32)
x_size = len(x_range)
y_size = len(y_range)
cube_data = np.empty((y_size, x_size), dtype=np.float32)
cube_data[:] = data
cube = iris.cube.Cube(cube_data)
coord = DimCoord(y_range, long_name='y')
coord.guess_bounds()
cube.add_dim_coord(coord, 0)
coord = DimCoord(x_range, long_name='x')
coord.guess_bounds()
cube.add_dim_coord(coord, 1)
if aux is not None:
aux = aux.split(',')
if 'y' in aux:
coord = AuxCoord(y_range * 10, long_name='y-aux')
cube.add_aux_coord(coord, (0, ))
if 'x' in aux:
coord = AuxCoord(x_range * 10, long_name='x-aux')
cube.add_aux_coord(coord, (1, ))
if 'xy' in aux:
payload = np.arange(y_size * x_size,
dtype=np.float32).reshape(y_size, x_size)
coord = AuxCoord(payload * 100 + offset, long_name='xy-aux')
cube.add_aux_coord(coord, (0, 1))
if scalar is not None:
data = np.array([scalar], dtype=np.float32)
coord = AuxCoord(data, long_name='height', units='m')
cube.add_aux_coord(coord, ())
return cube
def test_coord_var_name_fail(self):
token = "var name" # includes space
emsg = "is not a valid NetCDF variable name"
with self.assertRaisesRegex(ValueError, emsg):
AuxCoord(1, var_name=token)
def _all_other_rules(f):
"""
This deals with all the other rules that have not been factored into any of
the other convert_scalar_coordinate functions above.
"""
references = []
standard_name = None
long_name = None
units = None
attributes = {}
cell_methods = []
dim_coords_and_dims = []
aux_coords_and_dims = []
# Season coordinates (--> scalar coordinates)
if (f.lbtim.ib == 3 and f.lbtim.ic in [1, 2, 4]
and (len(f.lbcode) != 5 or
(len(f.lbcode) == 5 and
(f.lbcode.ix not in [20, 21, 22, 23]
and f.lbcode.iy not in [20, 21, 22, 23]))) and f.lbmon == 12
and f.lbdat == 1 and f.lbhr == 0 and f.lbmin == 0 and f.lbmond == 3
and f.lbdatd == 1 and f.lbhrd == 0 and f.lbmind == 0):
aux_coords_and_dims.append((AuxCoord('djf',
long_name='season',
units='no_unit'), None))
if (f.lbtim.ib == 3 and f.lbtim.ic in [1, 2, 4]
and ((len(f.lbcode) != 5) or
(len(f.lbcode) == 5 and f.lbcode.ix not in [20, 21, 22, 23]
and f.lbcode.iy not in [20, 21, 22, 23])) and f.lbmon == 3
and f.lbdat == 1 and f.lbhr == 0 and f.lbmin == 0 and f.lbmond == 6
and f.lbdatd == 1 and f.lbhrd == 0 and f.lbmind == 0):
aux_coords_and_dims.append((AuxCoord('mam',
long_name='season',
units='no_unit'), None))
if (f.lbtim.ib == 3 and f.lbtim.ic in [1, 2, 4]
and ((len(f.lbcode) != 5) or
(len(f.lbcode) == 5 and f.lbcode.ix not in [20, 21, 22, 23]
and f.lbcode.iy not in [20, 21, 22, 23])) and f.lbmon == 6
and f.lbdat == 1 and f.lbhr == 0 and f.lbmin == 0 and f.lbmond == 9
and f.lbdatd == 1 and f.lbhrd == 0 and f.lbmind == 0):
aux_coords_and_dims.append((AuxCoord('jja',
long_name='season',
units='no_unit'), None))
if (f.lbtim.ib == 3 and f.lbtim.ic in [1, 2, 4]
and ((len(f.lbcode) != 5) or
(len(f.lbcode) == 5 and f.lbcode.ix not in [20, 21, 22, 23]
and f.lbcode.iy not in [20, 21, 22, 23])) and f.lbmon == 9
and f.lbdat == 1 and f.lbhr == 0 and f.lbmin == 0
and f.lbmond == 12 and f.lbdatd == 1 and f.lbhrd == 0
and f.lbmind == 0):
aux_coords_and_dims.append((AuxCoord('son',
long_name='season',
units='no_unit'), None))
# Special case where year is zero and months match.
# Month coordinates (--> scalar coordinates)
if (f.lbtim.ib == 2 and f.lbtim.ic in [1, 2, 4]
and ((len(f.lbcode) != 5) or
(len(f.lbcode) == 5 and f.lbcode.ix not in [20, 21, 22, 23]
and f.lbcode.iy not in [20, 21, 22, 23])) and f.lbyr == 0
and f.lbyrd == 0 and f.lbmon == f.lbmond):
aux_coords_and_dims.append((AuxCoord(f.lbmon,
long_name='month_number'), None))
aux_coords_and_dims.append((AuxCoord(calendar.month_abbr[f.lbmon],
long_name='month',
units='no_unit'), None))
aux_coords_and_dims.append((DimCoord(points=f.lbft,
standard_name='forecast_period',
units='hours'), None))
# "Normal" (i.e. not cross-sectional) lats+lons (--> vector coordinates)
if (f.bdx != 0.0 and f.bdx != f.bmdi and len(f.lbcode) != 5
and f.lbcode[0] == 1):
dim_coords_and_dims.append(
(DimCoord.from_regular(f.bzx,
f.bdx,
f.lbnpt,
standard_name=f._x_coord_name(),
units='degrees',
circular=(f.lbhem in [0, 4]),
coord_system=f.coord_system()), 1))
if (f.bdx != 0.0 and f.bdx != f.bmdi and len(f.lbcode) != 5
and f.lbcode[0] == 2):
dim_coords_and_dims.append(
(DimCoord.from_regular(f.bzx,
f.bdx,
f.lbnpt,
standard_name=f._x_coord_name(),
units='degrees',
circular=(f.lbhem in [0, 4]),
coord_system=f.coord_system(),
with_bounds=True), 1))
if (f.bdy != 0.0 and f.bdy != f.bmdi and len(f.lbcode) != 5
and f.lbcode[0] == 1):
dim_coords_and_dims.append(
(DimCoord.from_regular(f.bzy,
f.bdy,
f.lbrow,
standard_name=f._y_coord_name(),
units='degrees',
coord_system=f.coord_system()), 0))
if (f.bdy != 0.0 and f.bdy != f.bmdi and len(f.lbcode) != 5
and f.lbcode[0] == 2):
dim_coords_and_dims.append(
(DimCoord.from_regular(f.bzy,
f.bdy,
f.lbrow,
standard_name=f._y_coord_name(),
units='degrees',
coord_system=f.coord_system(),
with_bounds=True), 0))
if ((f.bdy == 0.0 or f.bdy == f.bmdi) and
(len(f.lbcode) != 5 or (len(f.lbcode) == 5 and f.lbcode.iy == 10))):
dim_coords_and_dims.append(
(DimCoord(f.y,
standard_name=f._y_coord_name(),
units='degrees',
bounds=f.y_bounds,
coord_system=f.coord_system()), 0))
if ((f.bdx == 0.0 or f.bdx == f.bmdi) and
(len(f.lbcode) != 5 or (len(f.lbcode) == 5 and f.lbcode.ix == 11))):
dim_coords_and_dims.append(
(DimCoord(f.x,
standard_name=f._x_coord_name(),
units='degrees',
bounds=f.x_bounds,
circular=(f.lbhem in [0, 4]),
coord_system=f.coord_system()), 1))
# Cross-sectional vertical level types (--> vector coordinates)
if (len(f.lbcode) == 5 and f.lbcode.iy == 2
and (f.bdy == 0 or f.bdy == f.bmdi)):
dim_coords_and_dims.append((DimCoord(f.y,
standard_name='height',
units='km',
bounds=f.y_bounds,
attributes={'positive':
'up'}), 0))
if (len(f.lbcode) == 5 and f.lbcode[-1] == 1 and f.lbcode.iy == 4):
dim_coords_and_dims.append((DimCoord(f.y,
standard_name='depth',
units='m',
bounds=f.y_bounds,
attributes={'positive':
'down'}), 0))
if (len(f.lbcode) == 5 and f.lbcode.ix == 10 and f.bdx != 0
and f.bdx != f.bmdi):
dim_coords_and_dims.append(
(DimCoord.from_regular(f.bzx,
f.bdx,
f.lbnpt,
standard_name=f._y_coord_name(),
units='degrees',
coord_system=f.coord_system()), 1))
if (len(f.lbcode) == 5 and f.lbcode.iy == 1
and (f.bdy == 0 or f.bdy == f.bmdi)):
dim_coords_and_dims.append((DimCoord(f.y,
long_name='pressure',
units='hPa',
bounds=f.y_bounds), 0))
if (len(f.lbcode) == 5 and f.lbcode.ix == 1
and (f.bdx == 0 or f.bdx == f.bmdi)):
dim_coords_and_dims.append((DimCoord(f.x,
long_name='pressure',
units='hPa',
bounds=f.x_bounds), 1))
# Cross-sectional time values (--> vector coordinates)
if (len(f.lbcode) == 5 and f.lbcode[-1] == 1 and f.lbcode.iy == 23):
dim_coords_and_dims.append(
(DimCoord(f.y,
standard_name='time',
units=cf_units.Unit('days since 0000-01-01 00:00:00',
calendar=cf_units.CALENDAR_360_DAY),
bounds=f.y_bounds), 0))
if (len(f.lbcode) == 5 and f.lbcode[-1] == 1 and f.lbcode.ix == 23):
dim_coords_and_dims.append(
(DimCoord(f.x,
standard_name='time',
units=cf_units.Unit('days since 0000-01-01 00:00:00',
calendar=cf_units.CALENDAR_360_DAY),
bounds=f.x_bounds), 1))
if (len(f.lbcode) == 5 and f.lbcode[-1] == 3 and f.lbcode.iy == 23
and f.lbtim.ib == 2 and f.lbtim.ic == 2):
epoch_days_unit = cf_units.Unit('days since 0000-01-01 00:00:00',
calendar=cf_units.CALENDAR_360_DAY)
t1_epoch_days = epoch_days_unit.date2num(f.t1)
t2_epoch_days = epoch_days_unit.date2num(f.t2)
# The end time is exclusive, not inclusive.
dim_coords_and_dims.append((DimCoord(np.linspace(t1_epoch_days,
t2_epoch_days,
f.lbrow,
endpoint=False),
standard_name='time',
units=epoch_days_unit,
bounds=f.y_bounds), 0))
# Site number (--> scalar coordinate)
if (len(f.lbcode) == 5 and f.lbcode[-1] == 1 and f.lbcode.ix == 13
and f.bdx != 0):
dim_coords_and_dims.append(
(DimCoord.from_regular(f.bzx,
f.bdx,
f.lbnpt,
long_name='site_number',
units='1'), 1))
# Site number cross-sections (???)
if (len(f.lbcode) == 5 and 13 in [f.lbcode.ix, f.lbcode.iy]
and 11 not in [f.lbcode.ix, f.lbcode.iy]
and hasattr(f, 'lower_x_domain') and hasattr(f, 'upper_x_domain')
and all(f.lower_x_domain != -1.e+30)
and all(f.upper_x_domain != -1.e+30)):
aux_coords_and_dims.append((AuxCoord(
(f.lower_x_domain + f.upper_x_domain) / 2.0,
standard_name=f._x_coord_name(),
units='degrees',
bounds=np.array([f.lower_x_domain, f.upper_x_domain]).T,
coord_system=f.coord_system()), 1 if f.lbcode.ix == 13 else 0))
if (len(f.lbcode) == 5 and 13 in [f.lbcode.ix, f.lbcode.iy]
and 10 not in [f.lbcode.ix, f.lbcode.iy]
and hasattr(f, 'lower_y_domain') and hasattr(f, 'upper_y_domain')
and all(f.lower_y_domain != -1.e+30)
and all(f.upper_y_domain != -1.e+30)):
aux_coords_and_dims.append((AuxCoord(
(f.lower_y_domain + f.upper_y_domain) / 2.0,
standard_name=f._y_coord_name(),
units='degrees',
bounds=np.array([f.lower_y_domain, f.upper_y_domain]).T,
coord_system=f.coord_system()), 1 if f.lbcode.ix == 13 else 0))
# LBPROC codings (--> cell method + attributes)
unhandled_lbproc = True
zone_method = None
time_method = None
if f.lbproc == 0:
unhandled_lbproc = False
elif f.lbproc == 64:
zone_method = 'mean'
elif f.lbproc == 128:
time_method = 'mean'
elif f.lbproc == 4096:
time_method = 'minimum'
elif f.lbproc == 8192:
time_method = 'maximum'
elif f.lbproc == 192:
time_method = 'mean'
zone_method = 'mean'
if time_method is not None:
if f.lbtim.ia != 0:
intervals = '{} hour'.format(f.lbtim.ia)
else:
intervals = None
if f.lbtim.ib == 2:
# Aggregation over a period of time.
cell_methods.append(
CellMethod(time_method, coords='time', intervals=intervals))
unhandled_lbproc = False
elif f.lbtim.ib == 3 and f.lbproc == 128:
# Aggregation over a period of time within a year, over a number
# of years.
# Only mean (lbproc of 128) is handled as the min/max
# interpretation is ambiguous e.g. decadal mean of daily max,
# decadal max of daily mean, decadal mean of max daily mean etc.
cell_methods.append(
CellMethod('{} within years'.format(time_method),
coords='time',
intervals=intervals))
cell_methods.append(
CellMethod('{} over years'.format(time_method), coords='time'))
unhandled_lbproc = False
else:
# Generic cell method to indicate a time aggregation.
cell_methods.append(CellMethod(time_method, coords='time'))
unhandled_lbproc = False
if zone_method is not None:
if f.lbcode == 1:
cell_methods.append(CellMethod(zone_method, coords='longitude'))
for coord, _dim in dim_coords_and_dims:
if coord.standard_name == 'longitude':
if len(coord.points) == 1:
coord.bounds = np.array([0., 360.], dtype=np.float32)
else:
coord.guess_bounds()
unhandled_lbproc = False
elif f.lbcode == 101:
cell_methods.append(
CellMethod(zone_method, coords='grid_longitude'))
for coord, _dim in dim_coords_and_dims:
if coord.standard_name == 'grid_longitude':
if len(coord.points) == 1:
coord.bounds = np.array([0., 360.], dtype=np.float32)
else:
coord.guess_bounds()
unhandled_lbproc = False
else:
unhandled_lbproc = True
if unhandled_lbproc:
attributes["ukmo__process_flags"] = tuple(
sorted([
name for value, name in six.iteritems(LBPROC_MAP)
if isinstance(value, int) and f.lbproc & value
]))
if (f.lbsrce % 10000) == 1111:
attributes['source'] = 'Data from Met Office Unified Model'
# Also define MO-netCDF compliant UM version.
um_major = (f.lbsrce // 10000) // 100
if um_major != 0:
um_minor = (f.lbsrce // 10000) % 100
attributes['um_version'] = '{:d}.{:d}'.format(um_major, um_minor)
if (f.lbuser[6] != 0 or (f.lbuser[3] // 1000) != 0
or (f.lbuser[3] % 1000) != 0):
attributes['STASH'] = f.stash
if str(f.stash) in STASH_TO_CF:
standard_name = STASH_TO_CF[str(f.stash)].standard_name
units = STASH_TO_CF[str(f.stash)].units
long_name = STASH_TO_CF[str(f.stash)].long_name
if (not f.stash.is_valid and f.lbfc in LBFC_TO_CF):
standard_name = LBFC_TO_CF[f.lbfc].standard_name
units = LBFC_TO_CF[f.lbfc].units
long_name = LBFC_TO_CF[f.lbfc].long_name
# Orography reference field (--> reference target)
if f.lbuser[3] == 33:
references.append(ReferenceTarget('orography', None))
# Surface pressure reference field (--> reference target)
if f.lbuser[3] == 409 or f.lbuser[3] == 1:
references.append(ReferenceTarget('surface_air_pressure', None))
return (references, standard_name, long_name, units, attributes,
cell_methods, dim_coords_and_dims, aux_coords_and_dims)
def test_coord_stash(self):
token = "stash"
coord = AuxCoord(1, attributes=dict(STASH=token))
self._check(token, coord, default=True)
def _cf_height_from_name(z_coord, lower_bound=None, upper_bound=None):
"""
Parser for the z component of field headings.
This parse is specifically for handling the z component of NAME field
headings, which include height above ground level, height above sea level
and flight level etc. This function returns an iris coordinate
representing this field heading.
Args:
* z_coord (list):
A field heading, specifically the z component.
Returns:
An instance of :class:`iris.coords.AuxCoord` representing the
interpretation of the supplied field heading.
"""
# NAMEII - integer/float support.
# Match against height agl, asl and Pa.
pattern = re.compile(r'^From\s*'
'(?P<lower_bound>[0-9]+(\.[0-9]+)?)'
'\s*-\s*'
'(?P<upper_bound>[0-9]+(\.[0-9]+)?)'
'\s*(?P<type>m\s*asl|m\s*agl|Pa)'
'(?P<extra>.*)')
# Match against flight level.
pattern_fl = re.compile(r'^From\s*'
'(?P<type>FL)'
'(?P<lower_bound>[0-9]+(\.[0-9]+)?)'
'\s*-\s*FL'
'(?P<upper_bound>[0-9]+(\.[0-9]+)?)'
'(?P<extra>.*)')
# NAMEIII - integer/float support.
# Match scalar against height agl, asl, Pa, FL
pattern_scalar = re.compile(r'Z\s*=\s*'
'(?P<point>[0-9]+(\.[0-9]+)?([eE][+-]?\d+)?)'
'\s*(?P<type>m\s*agl|m\s*asl|FL|Pa)'
'(?P<extra>.*)')
type_name = {'magl': 'height', 'masl': 'altitude', 'FL': 'flight_level',
'Pa': 'air_pressure'}
patterns = [pattern, pattern_fl, pattern_scalar]
units = 'no-unit'
points = z_coord
bounds = None
standard_name = None
long_name = 'z'
if upper_bound is not None and lower_bound is not None:
match_ub = pattern_scalar.match(upper_bound)
match_lb = pattern_scalar.match(lower_bound)
for pattern in patterns:
match = pattern.match(z_coord)
if match:
match = match.groupdict()
# Do not interpret if there is additional information to the match
if match['extra']:
break
units = match['type'].replace(' ', '')
name = type_name[units]
# Interpret points if present.
if 'point' in match:
points = float(match['point'])
if upper_bound is not None and lower_bound is not None:
bounds = np.array([float(match_lb.groupdict()['point']),
float(match_ub.groupdict()['point'])])
# Interpret points from bounds.
else:
bounds = np.array([float(match['lower_bound']),
float(match['upper_bound'])])
points = bounds.sum() / 2.
long_name = None
if name == 'altitude':
units = units[0]
standard_name = name
long_name = 'altitude above sea level'
elif name == 'height':
units = units[0]
standard_name = name
long_name = 'height above ground level'
elif name == 'air_pressure':
standard_name = name
elif name == 'flight_level':
long_name = name
units = _parse_units(units)
break
coord = AuxCoord(points, units=units, standard_name=standard_name,
long_name=long_name, bounds=bounds)
return coord
def test_coord_stash_default(self):
token = "_stash" # includes leading underscore
coord = AuxCoord(1, attributes=dict(STASH=token))
self._check(token, coord, default=True)
def convert(grib):
"""
Converts a GRIB message into the corresponding items of Cube metadata.
Args:
* grib:
A :class:`~iris.fileformats.grib.GribWrapper` object.
Returns:
A :class:`iris.fileformats.rules.ConversionMetadata` object.
"""
factories = []
references = []
standard_name = None
long_name = None
units = None
attributes = {}
cell_methods = []
dim_coords_and_dims = []
aux_coords_and_dims = []
# deprecation warning for this code path for edition 2 messages
if grib.edition == 2:
msg = ('This GRIB loader is deprecated and will be removed in '
'a future release. Please consider using the new '
'GRIB loader by setting the :class:`iris.Future` '
'option `strict_grib_load` to True; e.g.:\n'
'iris.FUTURE.strict_grib_load = True\n'
'Please report issues you experience to:\n'
'https://groups.google.com/forum/#!topic/scitools-iris-dev/'
'lMsOusKNfaU')
warn_deprecated(msg)
if \
(grib.gridType=="reduced_gg"):
aux_coords_and_dims.append(
(AuxCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 0))
aux_coords_and_dims.append(
(AuxCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system), 0))
if \
(grib.gridType=="regular_ll") and \
(grib.jPointsAreConsecutive == 0):
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 0))
dim_coords_and_dims.append((DimCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system,
circular=grib._x_circular), 1))
if \
(grib.gridType=="regular_ll") and \
(grib.jPointsAreConsecutive == 1):
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 1))
dim_coords_and_dims.append((DimCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system,
circular=grib._x_circular), 0))
if \
(grib.gridType=="regular_gg") and \
(grib.jPointsAreConsecutive == 0):
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 0))
dim_coords_and_dims.append((DimCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system,
circular=grib._x_circular), 1))
if \
(grib.gridType=="regular_gg") and \
(grib.jPointsAreConsecutive == 1):
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 1))
dim_coords_and_dims.append((DimCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system,
circular=grib._x_circular), 0))
if \
(grib.gridType=="rotated_ll") and \
(grib.jPointsAreConsecutive == 0):
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 0))
dim_coords_and_dims.append((DimCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system,
circular=grib._x_circular), 1))
if \
(grib.gridType=="rotated_ll") and \
(grib.jPointsAreConsecutive == 1):
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units='degrees',
coord_system=grib._coord_system), 1))
dim_coords_and_dims.append((DimCoord(grib._x_points,
grib._x_coord_name,
units='degrees',
coord_system=grib._coord_system,
circular=grib._x_circular), 0))
if grib.gridType in ["polar_stereographic", "lambert"]:
dim_coords_and_dims.append(
(DimCoord(grib._y_points,
grib._y_coord_name,
units="m",
coord_system=grib._coord_system), 0))
dim_coords_and_dims.append(
(DimCoord(grib._x_points,
grib._x_coord_name,
units="m",
coord_system=grib._coord_system), 1))
if \
(grib.edition == 1) and \
(grib.table2Version < 128) and \
(grib.indicatorOfParameter == 11) and \
(grib._cf_data is None):
standard_name = "air_temperature"
units = "kelvin"
if \
(grib.edition == 1) and \
(grib.table2Version < 128) and \
(grib.indicatorOfParameter == 33) and \
(grib._cf_data is None):
standard_name = "x_wind"
units = "m s-1"
if \
(grib.edition == 1) and \
(grib.table2Version < 128) and \
(grib.indicatorOfParameter == 34) and \
(grib._cf_data is None):
standard_name = "y_wind"
units = "m s-1"
if \
(grib.edition == 1) and \
(grib._cf_data is not None):
standard_name = grib._cf_data.standard_name
long_name = grib._cf_data.standard_name or grib._cf_data.long_name
units = grib._cf_data.units
if \
(grib.edition == 1) and \
(grib.table2Version >= 128) and \
(grib._cf_data is None):
long_name = "UNKNOWN LOCAL PARAM " + str(
grib.indicatorOfParameter) + "." + str(grib.table2Version)
units = "???"
if \
(grib.edition == 1) and \
(grib.table2Version == 1) and \
(grib.indicatorOfParameter >= 128):
long_name = "UNKNOWN LOCAL PARAM " + str(
grib.indicatorOfParameter) + "." + str(grib.table2Version)
units = "???"
if \
(grib.edition == 2) and \
(grib._cf_data is not None):
standard_name = grib._cf_data.standard_name
long_name = grib._cf_data.long_name
units = grib._cf_data.units
if \
(grib.edition == 1) and \
(grib._phenomenonDateTime != -1.0):
aux_coords_and_dims.append(
(DimCoord(points=grib.startStep,
standard_name='forecast_period',
units=grib._forecastTimeUnit), None))
aux_coords_and_dims.append(
(DimCoord(points=grib.phenomenon_points('hours'),
standard_name='time',
units=Unit('hours since epoch',
CALENDAR_GREGORIAN)), None))
def add_bounded_time_coords(aux_coords_and_dims, grib):
t_bounds = grib.phenomenon_bounds('hours')
period = Unit('hours').convert(t_bounds[1] - t_bounds[0],
grib._forecastTimeUnit)
aux_coords_and_dims.append(
(DimCoord(standard_name='forecast_period',
units=grib._forecastTimeUnit,
points=grib._forecastTime + 0.5 * period,
bounds=[grib._forecastTime,
grib._forecastTime + period]), None))
aux_coords_and_dims.append(
(DimCoord(standard_name='time',
units=Unit('hours since epoch', CALENDAR_GREGORIAN),
points=0.5 * (t_bounds[0] + t_bounds[1]),
bounds=t_bounds), None))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 2):
add_bounded_time_coords(aux_coords_and_dims, grib)
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 3):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 4):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("sum", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 5):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("_difference", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 51):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 113):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 114):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("sum", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 115):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 116):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("sum", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 117):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 118):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("_covariance", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 123):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 124):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("sum", coords="time"))
if \
(grib.edition == 1) and \
(grib.timeRangeIndicator == 125):
add_bounded_time_coords(aux_coords_and_dims, grib)
cell_methods.append(CellMethod("standard_deviation", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in [0, 1]):
aux_coords_and_dims.append(
(DimCoord(points=Unit(grib._forecastTimeUnit).convert(
np.int32(grib._forecastTime), "hours"),
standard_name='forecast_period',
units="hours"), None))
aux_coords_and_dims.append(
(DimCoord(points=grib.phenomenon_points('hours'),
standard_name='time',
units=Unit('hours since epoch',
CALENDAR_GREGORIAN)), None))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 9, 11)):
add_bounded_time_coords(aux_coords_and_dims, grib)
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (1, 11)) and \
(grib.perturbationNumber is not None):
cell_methods.append(
CellMethod('realization',
coords=('realization', ),
intervals=('1', ),
comments=(' ENS', )))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 0):
cell_methods.append(CellMethod("mean", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 1):
cell_methods.append(CellMethod("sum", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 2):
cell_methods.append(CellMethod("maximum", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 3):
cell_methods.append(CellMethod("minimum", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 4):
cell_methods.append(CellMethod("_difference", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 5):
cell_methods.append(CellMethod("_root_mean_square", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 6):
cell_methods.append(CellMethod("standard_deviation", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 7):
cell_methods.append(CellMethod("_convariance", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 8):
cell_methods.append(CellMethod("_difference", coords="time"))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in (8, 11)) and \
(grib.typeOfStatisticalProcessing == 9):
cell_methods.append(CellMethod("_ratio", coords="time"))
if \
(grib.edition == 1) and \
(grib.levelType == 'pl'):
aux_coords_and_dims.append((DimCoord(points=grib.level,
long_name="pressure",
units="hPa"), None))
if \
(grib.edition == 1) and \
(grib.levelType == 'sfc'):
if (grib._cf_data is not None) and \
(grib._cf_data.set_height is not None):
aux_coords_and_dims.append(
(DimCoord(points=grib._cf_data.set_height,
long_name="height",
units="m",
attributes={'positive': 'up'}), None))
elif grib.typeOfLevel == 'heightAboveGround': # required for NCAR
aux_coords_and_dims.append((DimCoord(points=grib.level,
long_name="height",
units="m",
attributes={'positive':
'up'}), None))
if \
(grib.edition == 1) and \
(grib.levelType == 'ml') and \
(hasattr(grib, 'pv')):
aux_coords_and_dims.append(
(AuxCoord(grib.level,
standard_name='model_level_number',
attributes={'positive': 'up'}), None))
aux_coords_and_dims.append((DimCoord(grib.pv[grib.level],
long_name='level_pressure',
units='Pa'), None))
aux_coords_and_dims.append((AuxCoord(
grib.pv[grib.numberOfCoordinatesValues // 2 + grib.level],
long_name='sigma'), None))
factories.append(
Factory(HybridPressureFactory, [{
'long_name': 'level_pressure'
}, {
'long_name': 'sigma'
},
Reference('surface_pressure')]))
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface != grib.typeOfSecondFixedSurface):
warnings.warn("Different vertical bound types not yet handled.")
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface == 103) and \
(grib.typeOfSecondFixedSurface == 255):
aux_coords_and_dims.append(
(DimCoord(points=grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface),
standard_name="height",
units="m"), None))
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface == 103) and \
(grib.typeOfSecondFixedSurface != 255):
aux_coords_and_dims.append((DimCoord(
points=0.5 * (grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface) +
grib.scaledValueOfSecondFixedSurface /
(10.0**grib.scaleFactorOfSecondFixedSurface)),
standard_name="height",
units="m",
bounds=[
grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface),
grib.scaledValueOfSecondFixedSurface /
(10.0**grib.scaleFactorOfSecondFixedSurface)
]), None))
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface == 100) and \
(grib.typeOfSecondFixedSurface == 255):
aux_coords_and_dims.append(
(DimCoord(points=grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface),
long_name="pressure",
units="Pa"), None))
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface == 100) and \
(grib.typeOfSecondFixedSurface != 255):
aux_coords_and_dims.append((DimCoord(
points=0.5 * (grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface) +
grib.scaledValueOfSecondFixedSurface /
(10.0**grib.scaleFactorOfSecondFixedSurface)),
long_name="pressure",
units="Pa",
bounds=[
grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface),
grib.scaledValueOfSecondFixedSurface /
(10.0**grib.scaleFactorOfSecondFixedSurface)
]), None))
# required for NCMRWF
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface == 106) and \
(grib.typeOfSecondFixedSurface != 255):
aux_coords_and_dims.append((DimCoord(
points=0.5 * (grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface) +
grib.scaledValueOfSecondFixedSurface /
(10.0**grib.scaleFactorOfSecondFixedSurface)),
standard_name="depth",
long_name="depth_below_land_surface",
units="m",
bounds=[
grib.scaledValueOfFirstFixedSurface /
(10.0**grib.scaleFactorOfFirstFixedSurface),
grib.scaledValueOfSecondFixedSurface /
(10.0**grib.scaleFactorOfSecondFixedSurface)
]), None))
if \
(grib.edition == 2) and \
(grib.typeOfFirstFixedSurface in [105, 119]) and \
(grib.numberOfCoordinatesValues > 0):
aux_coords_and_dims.append(
(AuxCoord(grib.scaledValueOfFirstFixedSurface,
standard_name='model_level_number',
attributes={'positive': 'up'}), None))
aux_coords_and_dims.append(
(DimCoord(grib.pv[grib.scaledValueOfFirstFixedSurface],
long_name='level_pressure',
units='Pa'), None))
aux_coords_and_dims.append(
(AuxCoord(grib.pv[grib.numberOfCoordinatesValues // 2 +
grib.scaledValueOfFirstFixedSurface],
long_name='sigma'), None))
factories.append(
Factory(HybridPressureFactory,
[{
'long_name': 'level_pressure'
}, {
'long_name': 'sigma'
},
Reference('surface_air_pressure')]))
if grib._originatingCentre != 'unknown':
aux_coords_and_dims.append((AuxCoord(points=grib._originatingCentre,
long_name='originating_centre',
units='no_unit'), None))
if \
(grib.edition == 2) and \
(grib.productDefinitionTemplateNumber in [1, 11]):
aux_coords_and_dims.append((DimCoord(points=grib.perturbationNumber,
standard_name='realization',
long_name='ensemble_member',
units='no_unit'), None))
if \
(grib.edition == 2) and \
grib.productDefinitionTemplateNumber not in (0, 1, 8, 11):
attributes["GRIB_LOAD_WARNING"] = (
"unsupported GRIB%d ProductDefinitionTemplate: #4.%d" %
(grib.edition, grib.productDefinitionTemplateNumber))
if \
(grib.edition == 2) and \
(grib.centre == 'ecmf') and \
(grib.discipline == 0) and \
(grib.parameterCategory == 3) and \
(grib.parameterNumber == 25) and \
(grib.typeOfFirstFixedSurface == 105):
references.append(
ReferenceTarget(
'surface_air_pressure', lambda cube: {
'standard_name': 'surface_air_pressure',
'units': 'Pa',
'data': np.exp(cube.data)
}))
return ConversionMetadata(factories, references, standard_name, long_name,
units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims)
def test_mixture(self):
token = "air_temperature"
coord = AuxCoord(1, standard_name=token)
result = CellMethod(self.method, coords=[coord, token])
expected = "{}: {}, {}".format(self.method, token, token)
self.assertEqual(str(result), expected)
def setUp(self):
self.cube1 = Cube([1, 2, 3], "air_temperature", units="K")
self.cube1.add_aux_coord(AuxCoord([0], "height", units="m"))
def test_mixture_default(self):
token = "air temperature" # includes space
coord = AuxCoord(1, long_name=token)
result = CellMethod(self.method, coords=[coord, token])
expected = "{}: unknown, unknown".format(self.method)
self.assertEqual(str(result), expected)
def test_multidim(self):
# Testing with >2D data to demonstrate correct operation over
# additional non-XY dimensions (including data masking), which is
# handled by the PointInCell wrapper class.
# Define a simple target grid first, in plain latlon coordinates.
plain_latlon_cs = GeogCS(EARTH_RADIUS)
grid_x_coord = DimCoord(points=[15.0, 25.0, 35.0],
bounds=[[10.0, 20.0],
[20.0, 30.0],
[30.0, 40.0]],
standard_name='longitude',
units='degrees',
coord_system=plain_latlon_cs)
grid_y_coord = DimCoord(points=[-30.0, -50.0],
bounds=[[-20.0, -40.0], [-40.0, -60.0]],
standard_name='latitude',
units='degrees',
coord_system=plain_latlon_cs)
grid_cube = Cube(np.zeros((2, 3)))
grid_cube.add_dim_coord(grid_y_coord, 0)
grid_cube.add_dim_coord(grid_x_coord, 1)
# Define some key points in true-lat/lon thta have known positions
# First 3x2 points in the centre of each output cell.
x_centres, y_centres = np.meshgrid(grid_x_coord.points,
grid_y_coord.points)
# An extra point also falling in cell 1, 1
x_in11, y_in11 = 26.3, -48.2
# An extra point completely outside the target grid
x_out, y_out = 70.0, -40.0
# Define a rotated coord system for the source data
pole_lon, pole_lat = -125.3, 53.4
src_cs = RotatedGeogCS(grid_north_pole_latitude=pole_lat,
grid_north_pole_longitude=pole_lon,
ellipsoid=plain_latlon_cs)
# Concatenate all the testpoints in a flat array, and find the rotated
# equivalents.
xx = list(x_centres.flat[:]) + [x_in11, x_out]
yy = list(y_centres.flat[:]) + [y_in11, y_out]
xx, yy = rotate_pole(lons=np.array(xx),
lats=np.array(yy),
pole_lon=pole_lon,
pole_lat=pole_lat)
# Define handy index numbers for all these.
i00, i01, i02, i10, i11, i12, i_in, i_out = range(8)
# Build test data in the shape Z,YX = (3, 8)
data = [[1, 2, 3, 11, 12, 13, 7, 99],
[1, 2, 3, 11, 12, 13, 7, 99],
[7, 6, 5, 51, 52, 53, 12, 1]]
mask = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
src_data = np.ma.array(data, mask=mask, dtype=float)
# Make the source cube.
src_cube = Cube(src_data)
src_x = AuxCoord(xx,
standard_name='grid_longitude',
units='degrees',
coord_system=src_cs)
src_y = AuxCoord(yy,
standard_name='grid_latitude',
units='degrees',
coord_system=src_cs)
src_z = DimCoord(np.arange(3), long_name='z')
src_cube.add_dim_coord(src_z, 0)
src_cube.add_aux_coord(src_x, 1)
src_cube.add_aux_coord(src_y, 1)
# Add in some extra metadata, to ensure it gets copied over.
src_cube.add_aux_coord(DimCoord([0], long_name='extra_scalar_coord'))
src_cube.attributes['extra_attr'] = 12.3
# Define what the expected answers should be, shaped (3, 2, 3).
expected_result = [
[[1.0, 2.0, 3.0],
[11.0, 0.5 * (12 + 7), 13.0]],
[[1.0, -999, 3.0],
[11.0, 12.0, 13.0]],
[[7.0, 6.0, 5.0],
[51.0, 0.5 * (52 + 12), 53.0]],
]
expected_result = np.ma.masked_less(expected_result, 0)
# Perform the calculation with the regridder.
regridder = Regridder(src_cube, grid_cube)
# Check all is as expected.
result = regridder(src_cube)
self.assertEqual(result.coord('z'), src_cube.coord('z'))
self.assertEqual(result.coord('extra_scalar_coord'),
src_cube.coord('extra_scalar_coord'))
self.assertEqual(result.coord('longitude'),
grid_cube.coord('longitude'))
self.assertEqual(result.coord('latitude'),
grid_cube.coord('latitude'))
self.assertMaskedArrayAlmostEqual(result.data, expected_result)
def set_up_spot_cube(point_data,
validity_time=1487311200,
forecast_period=0,
number_of_sites=3):
"""Set up a spot data cube at a given validity time and forecast period for
a given number of sites.
Produces a cube with dimension coordinates of time, percentile
and index. There will be one point in the percentile and time
coordinates, and as many points in index coordinate as number_of_sites.
The output cube will also have auxillary coordinates for altitude,
wmo_site, forecast_period, and forecast_reference_time.
Args:
point_data (float):
The value for the data in the cube, which will be used for
every site.
Keyword Args:
validity_time (float):
The value for the validity time for your data, defaults to
1487311200 i.e. 2017-02-17 06:00:00
forecast_period (float):
The forecast period for your cube in hours.
number_of_sites (int):
The number of sites you want in your output cube.
Returns:
cube (iris.cube.Cube):
Example spot data cube.
"""
# Set up a data array with all the values the same as point_data.
data = np.ones((1, 1, number_of_sites)) * point_data
# Set up dimension coordinates.
time = DimCoord(np.array([validity_time]),
standard_name='time',
units=cf_units.Unit('seconds since 1970-01-01 00:00:00',
calendar='gregorian'))
percentile = DimCoord(np.array([50.]), long_name="percentile", units='%')
indices = np.arange(number_of_sites)
index = DimCoord(indices, units=cf_units.Unit('1'), long_name='index')
# Set up auxillary coordinates.
latitudes = np.ones(number_of_sites) * 54
latitude = AuxCoord(latitudes,
standard_name='latitude',
units='degrees',
coord_system=GeogCS(6371229.0))
longitudes = np.arange(number_of_sites)
longitude = AuxCoord(longitudes,
standard_name='longitude',
units='degrees',
coord_system=GeogCS(6371229.0))
altitudes = np.arange(number_of_sites) + 100
altitude = DimCoord(altitudes, standard_name='altitude', units='m')
wmo_sites = np.arange(number_of_sites) + 1000
wmo_site = AuxCoord(wmo_sites,
units=cf_units.Unit('1'),
long_name='wmo_site')
forecast_period_coord = AuxCoord(np.array(forecast_period * 3600),
standard_name='forecast_period',
units='seconds')
# Create cube
cube = Cube(data,
standard_name="air_temperature",
dim_coords_and_dims=[
(time, 0),
(percentile, 1),
(index, 2),
],
aux_coords_and_dims=[(latitude, 2), (longitude, 2),
(altitude, 2), (wmo_site, 2),
(forecast_period_coord, 0)],
units="K")
# Add scalar forecast_reference_time.
cycle_time = validity_time - forecast_period * 3600
forecast_reference_time = AuxCoord(np.array([cycle_time]),
standard_name='forecast_reference_time',
units=cf_units.Unit(
'seconds since 1970-01-01 00:00:00',
calendar='gregorian'))
cube.add_aux_coord(forecast_reference_time)
return cube
def test_numpy_simple(self):
points = np.arange(12).reshape(4, 3)
coord = AuxCoord(points)
result = AuxCoordFactory._nd_points(coord, (0, 1), 2)
expected = points
self.assertArrayEqual(result, expected)
def test_coord_with_irregular_step(self):
# Check that a `CoordinateNotRegularError` is captured.
coord = AuxCoord(np.array([2, 5, 1, 4]))
result = is_regular(coord)
self.assertFalse(result)
