def test_t1_list_t2_scalar(self):
# lbtim ia = 0, ib = 1, ic = 1
# with a single forecast reference time (t2) and a series
# of validity times (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=1, ic=1)
forecast_period_in_hours = np.array([0, 3, 6, 9, 12])
# Validity time - vector of different values
t1 = [nc_datetime(1970, 1, 9, hour=(3 + fp)) for fp in
forecast_period_in_hours]
t1_dims = (0,)
# Forecast reference time - scalar
t2 = nc_datetime(1970, 1, 9, hour=3)
lbft = None # Not used.
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
fp_coord = DimCoord(forecast_period_in_hours,
standard_name='forecast_period',
units='hours')
time_coord = DimCoord((24 * 8) + 3 + forecast_period_in_hours,
standard_name='time',
units=_EPOCH_HOURS_UNIT)
fref_time_coord = DimCoord((24 * 8) + 3,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0,)),
(time_coord, (0,)),
(fref_time_coord, None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def test_t1_list(self):
# lbtim ia = 0, ib = 0, ic = 1
# with a series of times (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=0, ic=1)
hours = np.array([0, 3, 6, 9, 12])
# Validity time - vector of different values
t1 = [nc_datetime(1970, 1, 9, hour=3 + hour) for hour in hours]
t1_dims = (0, )
# Forecast reference time - scalar (not used)
t2 = nc_datetime(1970, 1, 9, hour=3)
lbft = None
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
time_coord = DimCoord((24 * 8) + 3 + hours,
standard_name='time',
units=_EPOCH_HOURS_UNIT)
expected = [(time_coord, (0, ))]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def _check_yearly(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=3, ic=1)
# Start time
t1 = nc_datetime(1970, 1, 9, hour=9, minute=0, second=0)
# End time
t2 = nc_datetime(1972, 1, 11, hour=9, minute=0, second=0)
lbft = 3.0 # sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
if expect_match:
t1_hours = 24 * 8.375
t2_hours = 24 * (10.375 + 2 * 365)
period_hours = 24.0 * (2 * 365 + 2)
expect_result = [(DimCoord([t2_hours - lbft],
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None),
(DimCoord(standard_name='forecast_period',
units='hours',
points=[lbft],
bounds=[lbft - period_hours,
lbft]), None),
(DimCoord(standard_name='time',
units=_EPOCH_HOURS_UNIT,
points=[t2_hours],
bounds=[t1_hours, t2_hours]), None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def _check_period(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=2, ic=1)
# Start time
t1 = nc_datetime(1970, 1, 9, hour=3, minute=0, second=0)
# End time
t2 = nc_datetime(1970, 1, 10, hour=3, minute=0, second=0)
lbft = 2.0 # sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
if expect_match:
expect_result = [(DimCoord(24 * 9.125 - 2.0,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None),
(DimCoord(standard_name='forecast_period',
units='hours',
points=[-10.0],
bounds=[-22.0, 2.0]), None),
(DimCoord(standard_name='time',
units=_EPOCH_HOURS_UNIT,
points=[24 * 8.625],
bounds=[24 * 8.125, 24 * 9.125]), None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def _check_forecast(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=1, ic=1)
# Validity time
t1 = nc_datetime(1970, 1, 10, hour=6, minute=0, second=0)
# Forecast time
t2 = nc_datetime(1970, 1, 9, hour=3, minute=0, second=0)
lbft = None # unused
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
if expect_match:
expect_result = [(DimCoord(24 * 1.125,
standard_name='forecast_period',
units='hours'), None),
(DimCoord(24 * 9.25,
standard_name='time',
units=_EPOCH_HOURS_UNIT), None),
(DimCoord(24 * 8.125,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def _check_yearly(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=3, ic=1)
# Start time
t1 = nc_datetime(1970, 1, 9, hour=9, minute=0, second=0)
# End time
t2 = nc_datetime(1972, 1, 11, hour=9, minute=0, second=0)
lbft = 3.0 # sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
if expect_match:
t1_hours = 24 * 8.375
t2_hours = 24 * (10.375 + 2 * 365)
period_hours = 24.0 * (2 * 365 + 2)
expect_result = [
(DimCoord([t2_hours - lbft],
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None),
(DimCoord(standard_name='forecast_period', units='hours',
points=[lbft], bounds=[lbft - period_hours, lbft]),
None),
(DimCoord(standard_name='time', units=_EPOCH_HOURS_UNIT,
points=[t2_hours],
bounds=[t1_hours, t2_hours]), None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def _check_forecast(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=1, ic=1)
# Validity time
t1 = nc_datetime(1970, 1, 10, hour=6, minute=0, second=0)
# Forecast time
t2 = nc_datetime(1970, 1, 9, hour=3, minute=0, second=0)
lbft = None # unused
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
if expect_match:
expect_result = [
(DimCoord(24 * 1.125,
standard_name='forecast_period', units='hours'),
None),
(DimCoord(24 * 9.25,
standard_name='time', units=_EPOCH_HOURS_UNIT),
None),
(DimCoord(24 * 8.125,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT),
None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def test_unrecognised(self):
lbtim = _lbtim(ib=4, ic=1)
t1 = nc_datetime(0, 0, 0)
t2 = nc_datetime(0, 0, 0)
lbft = None
lbcode = _lbcode(0)
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
self.assertEqual(coords_and_dims, [])
def test_not_exact_hours(self):
lbtim = _lbtim(ib=1, ic=1)
t1 = nc_datetime(2015, 1, 20, hour=7, minute=10, second=0)
t2 = nc_datetime(2015, 1, 20, hour=0, minute=0, second=0)
coords_and_dims = _convert_time_coords(
lbcode=_lbcode(1), lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=None)
(fp, _), (t, _), (frt, _) = coords_and_dims
self.assertEqual(fp.points[0], 7.1666666641831398)
self.assertEqual(t.points[0], 394927.16666666418)
def test_(self):
lbtim = _lbtim(ib=2, ic=1)
t1 = nc_datetime(0, 1, 1)
t2 = nc_datetime(0, 1, 31, 23, 59, 00)
lbft = 0
lbcode = _lbcode(1)
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
self.assertEqual(coords_and_dims, [])
def test_exact_hours(self):
lbtim = _lbtim(ib=1, ic=1)
t1 = nc_datetime(2015, 1, 20, hour=7, minute=0, second=0)
t2 = nc_datetime(2015, 1, 20, hour=0, minute=0, second=0)
coords_and_dims = _convert_time_coords(
lbcode=_lbcode(1), lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=None)
(fp, _), (t, _), (frt, _) = coords_and_dims
# These should both be exact whole numbers.
self.assertEqual(fp.points[0], 7)
self.assertEqual(t.points[0], 394927)
def test_(self):
lbtim = _lbtim(ib=2, ic=1)
t1 = nc_datetime(0, 1, 1)
t2 = nc_datetime(0, 1, 31, 23, 59, 00)
lbft = 0
lbcode = _lbcode(1)
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
self.assertEqual(coords_and_dims, [])
def test(self):
lbcode = _lbcode(value=31323)
lbtim = _lbtim(ib=2, ic=2)
t1 = nc_datetime(1970, 1, 3, hour=0, minute=0, second=0)
t2 = nc_datetime(1970, 1, 4, hour=0, minute=0, second=0)
lbft = 24 * 4
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
t2_hours = 24 * 3
expected_result = [(DimCoord([t2_hours-lbft],
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected_result)
def test_unrecognised(self):
lbtim = _lbtim(ib=4, ic=1)
t1 = nc_datetime(0, 0, 0)
t2 = nc_datetime(0, 0, 0)
lbft = None
lbcode = _lbcode(0)
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
self.assertEqual(coords_and_dims, [])
def test_not_exact_hours(self):
lbtim = _lbtim(ib=1, ic=1)
t1 = nc_datetime(2015, 1, 20, hour=7, minute=10, second=0)
t2 = nc_datetime(2015, 1, 20, hour=0, minute=0, second=0)
coords_and_dims = _convert_time_coords(
lbcode=_lbcode(1),
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=None)
(fp, _), (t, _), (frt, _) = coords_and_dims
self.assertEqual(fp.points[0], 7.1666666641831398)
self.assertEqual(t.points[0], 394927.16666666418)
def test_exact_hours(self):
lbtim = _lbtim(ib=1, ic=1)
t1 = nc_datetime(2015, 1, 20, hour=7, minute=0, second=0)
t2 = nc_datetime(2015, 1, 20, hour=0, minute=0, second=0)
coords_and_dims = _convert_time_coords(
lbcode=_lbcode(1),
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=None)
(fp, _), (t, _), (frt, _) = coords_and_dims
# These should both be exact whole numbers.
self.assertEqual(fp.points[0], 7)
self.assertEqual(t.points[0], 394927)
def _check_timepoint(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=0, ic=1)
t1 = nc_datetime(1970, 1, 1, hour=6, minute=0, second=0)
t2 = nc_datetime(0, 0, 0) # not used in result
lbft = None # unused
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
if expect_match:
expect_result = [
(DimCoord(24 * 0.25, standard_name='time',
units=_EPOCH_HOURS_UNIT),
None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def test_t1_and_t2_orthogonal_lists(self):
# lbtim ia = 0, ib = 1, ic = 1
# with a single repeated forecast reference time (t2) and a series
# of validity times (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=1, ic=1)
years = np.array([1970, 1971, 1972])
hours = np.array([3, 6, 9, 12])
# Validity time - vector of different values
t1 = [nc_datetime(year, 1, 9, hour=12) for year in years]
t1_dims = (0, )
# Forecast reference time - vector of different values
t2 = [nc_datetime(1970, 1, 9, hour=hour) for hour in hours]
t2_dims = (1, )
lbft = None # Not used.
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft,
t1_dims=t1_dims,
t2_dims=t2_dims)
# Expected coords.
points = [[(year - 1970) * 365 * 24 + 12 - hour for hour in hours]
for year in years]
fp_coord = AuxCoord(points,
standard_name='forecast_period',
units='hours')
points = (years - 1970) * 24 * 365 + (24 * 8) + 12
time_coord = DimCoord(points,
standard_name='time',
units=_EPOCH_HOURS_UNIT)
points = (24 * 8) + hours
fref_time_coord = DimCoord(points,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [
(fp_coord, (0, 1)), # Spans dims 0 and 1.
(time_coord, (0, )),
(fref_time_coord, (1, ))
]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def test(self):
lbcode = _lbcode(value=31323)
lbtim = _lbtim(ib=2, ic=2)
t1 = nc_datetime(1970, 1, 3, hour=0, minute=0, second=0)
t2 = nc_datetime(1970, 1, 4, hour=0, minute=0, second=0)
lbft = 24 * 4
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
t2_hours = 24 * 3
expected_result = [(DimCoord([t2_hours - lbft],
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected_result)
def test_t1_multi_dim_list_t2_scalar(self):
# Another case of lbtim ia = 0, ib = 1, ic = 1 but
# with a changing forecast reference time (t2) and
# validity time (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=1, ic=1)
forecast_period_in_hours = np.array([0, 3, 6, 9, 12])
years = np.array([1970, 1971, 1972])
# Validity time - 2d array of different values
t1 = [[
nc_datetime(year, 1, 9, hour=(3 + fp))
for fp in forecast_period_in_hours
] for year in years]
t1_dims = (0, 1)
# Forecast reference time - vector of different values
t2 = nc_datetime(1970, 1, 9, hour=3)
lbft = None # Not used.
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
fp_coord = AuxCoord([
forecast_period_in_hours + (year - 1970) * 365 * 24
for year in years
],
standard_name='forecast_period',
units='hours')
time_coord = AuxCoord([(24 * 8) + 3 + forecast_period_in_hours +
(year - 1970) * 365 * 24 for year in years],
standard_name='time',
units=_EPOCH_HOURS_UNIT)
fref_time_coord = DimCoord((24 * 8) + 3,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0, 1)), (time_coord, (0, 1)),
(fref_time_coord, None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def test_t1_and_t2_nparrays(self):
# lbtim ia = 0, ib = 1, ic = 1
# with a single repeated forecast reference time (t2) and a series
# of validity times (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=1, ic=1)
forecast_period_in_hours = np.array([0, 3, 6, 9, 12])
# Validity time - vector of different values
t1 = np.array([
nc_datetime(1970, 1, 9, hour=(3 + fp))
for fp in forecast_period_in_hours
])
t1_dims = (0, )
# Forecast reference time - vector of same values
t2 = np.array([
nc_datetime(1970, 1, 9, hour=3) for _ in forecast_period_in_hours
])
t2_dims = (0, )
lbft = None # Not used.
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft,
t1_dims=t1_dims,
t2_dims=t2_dims)
# Expected coords.
fp_coord = DimCoord(forecast_period_in_hours,
standard_name='forecast_period',
units='hours')
time_coord = DimCoord((24 * 8) + 3 + forecast_period_in_hours,
standard_name='time',
units=_EPOCH_HOURS_UNIT)
fref_time_coord = DimCoord((24 * 8) + 3,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0, )), (time_coord, (0, )),
(fref_time_coord, None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def _check_timepoint(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=0, ic=1)
t1 = nc_datetime(1970, 1, 1, hour=6, minute=0, second=0)
t2 = nc_datetime(0, 0, 0) # not used in result
lbft = None # unused
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft)
if expect_match:
expect_result = [(DimCoord(24 * 0.25,
standard_name='time',
units=_EPOCH_HOURS_UNIT), None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def test_t1_list_t2_scalar(self):
lbtim = _lbtim(ib=2, ic=1)
lbcode = _lbcode(1)
hours = np.array([0, 3, 6, 9])
# Start times - vector
t1 = [nc_datetime(1970, 1, 9, hour=9 + hour) for hour in hours]
t1_dims = (0, )
# End time - scalar
t2 = nc_datetime(1970, 1, 11, hour=9)
lbft = 3.0 # Sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
points = lbft - (48 - hours) / 2.0
bounds = np.array([lbft - (48 - hours),
np.ones_like(hours) * lbft]).transpose()
fp_coord = AuxCoord(points,
standard_name='forecast_period',
units='hours',
bounds=bounds)
points = 9 * 24 + 9 + (hours / 2.0)
bounds = np.array(
[8 * 24 + 9 + hours,
np.ones_like(hours) * 10 * 24 + 9]).transpose()
time_coord = AuxCoord(points,
standard_name='time',
units=_EPOCH_HOURS_UNIT,
bounds=bounds)
points = 10 * 24 + 9 - lbft
fref_time_coord = DimCoord(points,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0, )), (time_coord, (0, )),
(fref_time_coord, None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def test_t1_scalar_t2_list(self):
lbtim = _lbtim(ib=3, ic=1)
lbcode = _lbcode(1)
years = np.array([1972, 1973, 1974])
# Start times - scalar
t1 = nc_datetime(1970, 1, 9, hour=9)
# End time - vector
t2 = [nc_datetime(year, 1, 11, hour=9) for year in years]
t2_dims = (0, )
lbft = 3.0 # Sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode,
lbtim=lbtim,
epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1,
t2=t2,
lbft=lbft,
t2_dims=t2_dims)
# Expected coords.
points = np.ones_like(years) * lbft
bounds = np.array(
[lbft - ((years - 1970) * 365 * 24 + 2 * 24), points]).transpose()
fp_coord = AuxCoord(points,
standard_name='forecast_period',
units='hours',
bounds=bounds)
points = (years - 1970) * 365 * 24 + 10 * 24 + 9
bounds = np.array([np.ones_like(points) * (8 * 24 + 9),
points]).transpose()
# The time coordinate is an AuxCoord as the lower bound for each
# cell is the same so it does not meet the monotonicity requirement.
time_coord = AuxCoord(points,
standard_name='time',
units=_EPOCH_HOURS_UNIT,
bounds=bounds)
fref_time_coord = DimCoord(points - lbft,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0, )), (time_coord, (0, )),
(fref_time_coord, (0, ))]
def test_t1_scalar_t2_list(self):
lbtim = _lbtim(ib=3, ic=1)
lbcode = _lbcode(1)
years = np.array([1972, 1973, 1974])
# Start times - scalar
t1 = nc_datetime(1970, 1, 9, hour=9)
# End time - vector
t2 = [nc_datetime(year, 1, 11, hour=9) for
year in years]
t2_dims = (0,)
lbft = 3.0 # Sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft,
t2_dims=t2_dims)
# Expected coords.
points = np.ones_like(years) * lbft
bounds = np.array([lbft - ((years - 1970) * 365 * 24 + 2 * 24),
points]).transpose()
fp_coord = AuxCoord(points,
standard_name='forecast_period',
units='hours',
bounds=bounds)
points = (years - 1970) * 365 * 24 + 10 * 24 + 9
bounds = np.array([np.ones_like(points) * (8 * 24 + 9),
points]).transpose()
# The time coordinate is an AuxCoord as the lower bound for each
# cell is the same so it does not meet the monotonicity requirement.
time_coord = AuxCoord(points,
standard_name='time',
units=_EPOCH_HOURS_UNIT,
bounds=bounds)
fref_time_coord = DimCoord(points - lbft,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0,)),
(time_coord, (0,)),
(fref_time_coord, (0,))]
def test_t1_list_t2_scalar(self):
lbtim = _lbtim(ib=2, ic=1)
lbcode = _lbcode(1)
hours = np.array([0, 3, 6, 9])
# Start times - vector
t1 = [nc_datetime(1970, 1, 9, hour=9 + hour) for
hour in hours]
t1_dims = (0,)
# End time - scalar
t2 = nc_datetime(1970, 1, 11, hour=9)
lbft = 3.0 # Sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
points = lbft - (48 - hours) / 2.0
bounds = np.array([lbft - (48 - hours),
np.ones_like(hours) * lbft]).transpose()
fp_coord = AuxCoord(points,
standard_name='forecast_period',
units='hours',
bounds=bounds)
points = 9 * 24 + 9 + (hours / 2.0)
bounds = np.array([8 * 24 + 9 + hours,
np.ones_like(hours) * 10 * 24 + 9]).transpose()
time_coord = AuxCoord(points,
standard_name='time',
units=_EPOCH_HOURS_UNIT,
bounds=bounds)
points = 10 * 24 + 9 - lbft
fref_time_coord = DimCoord(points,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0,)),
(time_coord, (0,)),
(fref_time_coord, None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def test_t1_and_t2_orthogonal_lists(self):
# lbtim ia = 0, ib = 1, ic = 1
# with a single repeated forecast reference time (t2) and a series
# of validity times (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=1, ic=1)
years = np.array([1970, 1971, 1972])
hours = np.array([3, 6, 9, 12])
# Validity time - vector of different values
t1 = [nc_datetime(year, 1, 9, hour=12) for year in years]
t1_dims = (0,)
# Forecast reference time - vector of different values
t2 = [nc_datetime(1970, 1, 9, hour=hour) for hour in hours]
t2_dims = (1,)
lbft = None # Not used.
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft,
t1_dims=t1_dims, t2_dims=t2_dims)
# Expected coords.
points = [[(year - 1970) * 365 * 24 + 12 - hour for hour
in hours] for year in years]
fp_coord = AuxCoord(points,
standard_name='forecast_period',
units='hours')
points = (years - 1970) * 24 * 365 + (24 * 8) + 12
time_coord = DimCoord(points,
standard_name='time',
units=_EPOCH_HOURS_UNIT)
points = (24 * 8) + hours
fref_time_coord = DimCoord(points,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0, 1)), # Spans dims 0 and 1.
(time_coord, (0,)),
(fref_time_coord, (1,))]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def _check_period(self, lbcode, expect_match=True):
lbtim = _lbtim(ib=2, ic=1)
# Start time
t1 = nc_datetime(1970, 1, 9, hour=3, minute=0, second=0)
# End time
t2 = nc_datetime(1970, 1, 10, hour=3, minute=0, second=0)
lbft = 2.0 # sample period
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft)
if expect_match:
expect_result = [
(DimCoord(24 * 9.125 - 2.0,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT), None),
(DimCoord(standard_name='forecast_period', units='hours',
points=[-10.0], bounds=[-22.0, 2.0]), None),
(DimCoord(standard_name='time', units=_EPOCH_HOURS_UNIT,
points=[24 * 8.625],
bounds=[24 * 8.125, 24 * 9.125]), None)]
else:
expect_result = []
self.assertCoordsAndDimsListsMatch(coords_and_dims, expect_result)
def test_t1_multi_dim_list_t2_scalar(self):
# Another case of lbtim ia = 0, ib = 1, ic = 1 but
# with a changing forecast reference time (t2) and
# validity time (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=1, ic=1)
forecast_period_in_hours = np.array([0, 3, 6, 9, 12])
years = np.array([1970, 1971, 1972])
# Validity time - 2d array of different values
t1 = [[nc_datetime(year, 1, 9, hour=(3 + fp)) for fp in
forecast_period_in_hours] for year in years]
t1_dims = (0, 1)
# Forecast reference time - vector of different values
t2 = nc_datetime(1970, 1, 9, hour=3)
lbft = None # Not used.
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
fp_coord = AuxCoord([forecast_period_in_hours +
(year - 1970) * 365 * 24 for year in years],
standard_name='forecast_period',
units='hours')
time_coord = AuxCoord([(24 * 8) + 3 + forecast_period_in_hours +
(year - 1970) * 365 * 24 for year in years],
standard_name='time',
units=_EPOCH_HOURS_UNIT)
fref_time_coord = DimCoord((24 * 8) + 3,
standard_name='forecast_reference_time',
units=_EPOCH_HOURS_UNIT)
expected = [(fp_coord, (0, 1)),
(time_coord, (0, 1)),
(fref_time_coord, None)]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def test_t1_list(self):
# lbtim ia = 0, ib = 0, ic = 1
# with a series of times (t1).
lbcode = _lbcode(1)
lbtim = _lbtim(ia=0, ib=0, ic=1)
hours = np.array([0, 3, 6, 9, 12])
# Validity time - vector of different values
t1 = [nc_datetime(1970, 1, 9, hour=3 + hour) for hour in hours]
t1_dims = (0,)
# Forecast reference time - scalar (not used)
t2 = nc_datetime(1970, 1, 9, hour=3)
lbft = None
coords_and_dims = _convert_time_coords(
lbcode=lbcode, lbtim=lbtim, epoch_hours_unit=_EPOCH_HOURS_UNIT,
t1=t1, t2=t2, lbft=lbft,
t1_dims=t1_dims)
# Expected coords.
time_coord = DimCoord((24 * 8) + 3 + hours,
standard_name='time',
units=_EPOCH_HOURS_UNIT)
expected = [(time_coord, (0,))]
self.assertCoordsAndDimsListsMatch(coords_and_dims, expected)
def _convert_collation(collation):
"""
Converts a FieldCollation into the corresponding items of Cube
metadata.
Args:
* collation:
A FieldCollation object.
Returns:
A :class:`iris.fileformats.rules.ConversionMetadata` object.
"""
# For all the scalar conversions all fields in the collation will
# give the same result, so the choice is arbitrary.
field = collation.fields[0]
# All the "other" rules.
(references, standard_name, long_name, units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims) = _all_other_rules(field)
# Adjust any dimension bindings to account for the extra leading
# dimensions added by the collation.
if collation.vector_dims_shape:
n_collation_dims = len(collation.vector_dims_shape)
dim_coords_and_dims = _adjust_dims(dim_coords_and_dims,
n_collation_dims)
aux_coords_and_dims = _adjust_dims(aux_coords_and_dims,
n_collation_dims)
# "Normal" (non-cross-sectional) time values
vector_headers = collation.element_arrays_and_dims
# If the collation doesn't define a vector of values for a
# particular header then it must be constant over all fields in the
# collation. In which case it's safe to get the value from any field.
t1, t1_dims = vector_headers.get('t1', (field.t1, ()))
t2, t2_dims = vector_headers.get('t2', (field.t2, ()))
lbft, lbft_dims = vector_headers.get('lbft', (field.lbft, ()))
coords_and_dims = _convert_time_coords(field.lbcode, field.lbtim,
field.time_unit('hours'), t1, t2,
lbft, t1_dims, t2_dims, lbft_dims)
dim_coord_dims = set()
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# "Normal" (non-cross-sectional) vertical levels
blev, blev_dims = vector_headers.get('blev', (field.blev, ()))
lblev, lblev_dims = vector_headers.get('lblev', (field.lblev, ()))
bhlev, bhlev_dims = vector_headers.get('bhlev', (field.bhlev, ()))
bhrlev, bhrlev_dims = vector_headers.get('bhrlev', (field.bhrlev, ()))
brsvd1, brsvd1_dims = vector_headers.get('brsvd1', (field.brsvd[0], ()))
brsvd2, brsvd2_dims = vector_headers.get('brsvd2', (field.brsvd[1], ()))
brlev, brlev_dims = vector_headers.get('brlev', (field.brlev, ()))
# Find all the non-trivial dimension values
dims = set(
filter(None, [
blev_dims, lblev_dims, bhlev_dims, bhrlev_dims, brsvd1_dims,
brsvd2_dims, brlev_dims
]))
if len(dims) > 1:
raise TranslationError('Unsupported multiple values for vertical '
'dimension.')
if dims:
v_dims = dims.pop()
if len(v_dims) > 1:
raise TranslationError('Unsupported multi-dimension vertical '
'headers.')
else:
v_dims = ()
coords_and_dims, factories = _convert_vertical_coords(
field.lbcode, field.lbvc, blev, lblev, field.stash, bhlev, bhrlev,
brsvd1, brsvd2, brlev, v_dims)
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# Realization (aka ensemble) (--> scalar coordinates)
aux_coords_and_dims.extend(
_convert_scalar_realization_coords(lbrsvd4=field.lbrsvd[3]))
# Pseudo-level coordinate (--> scalar coordinates)
aux_coords_and_dims.extend(
_convert_scalar_pseudo_level_coords(lbuser5=field.lbuser[4]))
return ConversionMetadata(factories, references, standard_name, long_name,
units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims)
def _convert_collation(collation):
"""
Converts a FieldCollation into the corresponding items of Cube
metadata.
Args:
* collation:
A FieldCollation object.
Returns:
A :class:`iris.fileformats.rules.ConversionMetadata` object.
.. note:
This is the 'loader.converter', in the control structure passed to the
generic rules code, :meth:`iris.fileformats.rules.load_cubes`.
"""
from iris.fileformats.rules import ConversionMetadata
from iris.fileformats.pp_rules import (_convert_time_coords,
_convert_vertical_coords,
_convert_scalar_realization_coords,
_convert_scalar_pseudo_level_coords,
_all_other_rules)
# For all the scalar conversions, all fields in the collation will
# give the same result, so the choice is arbitrary.
field = collation.fields[0]
# Call "all other" rules.
(references, standard_name, long_name, units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims) = _all_other_rules(field)
# Adjust any dimension bindings to account for the extra leading
# dimensions added by the collation.
if collation.vector_dims_shape:
def _adjust_dims(coords_and_dims, n_dims):
def adjust(dims):
if dims is not None:
dims += n_dims
return dims
return [(coord, adjust(dims)) for coord, dims in coords_and_dims]
n_collation_dims = len(collation.vector_dims_shape)
dim_coords_and_dims = _adjust_dims(dim_coords_and_dims,
n_collation_dims)
aux_coords_and_dims = _adjust_dims(aux_coords_and_dims,
n_collation_dims)
# Dimensions to which we've already assigned dimension coordinates.
dim_coord_dims = set()
# Helper call to choose which coords are dimensions and which auxiliary.
def _bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims):
def key_func(item):
return _HINTS.get(item[0].name(), len(_HINTS))
# Target the first DimCoord for a dimension at dim_coords,
# and target everything else at aux_coords.
for coord, dims in sorted(coords_and_dims, key=key_func):
if (isinstance(coord, DimCoord) and dims is not None
and len(dims) == 1 and dims[0] not in dim_coord_dims):
dim_coords_and_dims.append((coord, dims))
dim_coord_dims.add(dims[0])
else:
aux_coords_and_dims.append((coord, dims))
# Call "time" rules.
#
# For "normal" (non-cross-sectional) time values.
vector_headers = collation.element_arrays_and_dims
# If the collation doesn't define a vector of values for a
# particular header then it must be constant over all fields in the
# collation. In which case it's safe to get the value from any field.
t1, t1_dims = vector_headers.get('t1', (field.t1, ()))
t2, t2_dims = vector_headers.get('t2', (field.t2, ()))
lbft, lbft_dims = vector_headers.get('lbft', (field.lbft, ()))
coords_and_dims = _convert_time_coords(field.lbcode, field.lbtim,
field.time_unit('hours'), t1, t2,
lbft, t1_dims, t2_dims, lbft_dims)
# Bind resulting coordinates to dimensions, where suitable.
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# Call "vertical" rules.
#
# "Normal" (non-cross-sectional) vertical levels
blev, blev_dims = vector_headers.get('blev', (field.blev, ()))
lblev, lblev_dims = vector_headers.get('lblev', (field.lblev, ()))
bhlev, bhlev_dims = vector_headers.get('bhlev', (field.bhlev, ()))
bhrlev, bhrlev_dims = vector_headers.get('bhrlev', (field.bhrlev, ()))
brsvd1, brsvd1_dims = vector_headers.get('brsvd1', (field.brsvd[0], ()))
brsvd2, brsvd2_dims = vector_headers.get('brsvd2', (field.brsvd[1], ()))
brlev, brlev_dims = vector_headers.get('brlev', (field.brlev, ()))
# Find all the non-trivial dimension values
dims = set(
filter(None, [
blev_dims, lblev_dims, bhlev_dims, bhrlev_dims, brsvd1_dims,
brsvd2_dims, brlev_dims
]))
if len(dims) > 1:
raise TranslationError('Unsupported multiple values for vertical '
'dimension.')
if dims:
v_dims = dims.pop()
if len(v_dims) > 1:
raise TranslationError('Unsupported multi-dimension vertical '
'headers.')
else:
v_dims = ()
coords_and_dims, factories = _convert_vertical_coords(
field.lbcode, field.lbvc, blev, lblev, field.stash, bhlev, bhrlev,
brsvd1, brsvd2, brlev, v_dims)
# Bind resulting coordinates to dimensions, where suitable.
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# Realization (aka ensemble) (--> scalar coordinates)
aux_coords_and_dims.extend(
_convert_scalar_realization_coords(lbrsvd4=field.lbrsvd[3]))
# Pseudo-level coordinate (--> scalar coordinates)
aux_coords_and_dims.extend(
_convert_scalar_pseudo_level_coords(lbuser5=field.lbuser[4]))
return ConversionMetadata(factories, references, standard_name, long_name,
units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims)
def _convert_collation(collation):
"""
Converts a FieldCollation into the corresponding items of Cube
metadata.
Args:
* collation:
A FieldCollation object.
Returns:
A :class:`iris.fileformats.rules.ConversionMetadata` object.
"""
# For all the scalar conversions all fields in the collation will
# give the same result, so the choice is arbitrary.
field = collation.fields[0]
# All the "other" rules.
(references, standard_name, long_name, units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims) = _all_other_rules(field)
# Adjust any dimension bindings to account for the extra leading
# dimensions added by the collation.
if collation.vector_dims_shape:
n_collation_dims = len(collation.vector_dims_shape)
dim_coords_and_dims = _adjust_dims(dim_coords_and_dims,
n_collation_dims)
aux_coords_and_dims = _adjust_dims(aux_coords_and_dims,
n_collation_dims)
# "Normal" (non-cross-sectional) time values
vector_headers = collation.element_arrays_and_dims
# If the collation doesn't define a vector of values for a
# particular header then it must be constant over all fields in the
# collation. In which case it's safe to get the value from any field.
t1, t1_dims = vector_headers.get('t1', (field.t1, ()))
t2, t2_dims = vector_headers.get('t2', (field.t2, ()))
lbft, lbft_dims = vector_headers.get('lbft', (field.lbft, ()))
coords_and_dims = _convert_time_coords(field.lbcode, field.lbtim,
field.time_unit('hours'),
t1, t2, lbft,
t1_dims, t2_dims, lbft_dims)
dim_coord_dims = set()
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# "Normal" (non-cross-sectional) vertical levels
blev, blev_dims = vector_headers.get('blev', (field.blev, ()))
lblev, lblev_dims = vector_headers.get('lblev', (field.lblev, ()))
bhlev, bhlev_dims = vector_headers.get('bhlev', (field.bhlev, ()))
bhrlev, bhrlev_dims = vector_headers.get('bhrlev', (field.bhrlev, ()))
brsvd1, brsvd1_dims = vector_headers.get('brsvd1', (field.brsvd[0], ()))
brsvd2, brsvd2_dims = vector_headers.get('brsvd2', (field.brsvd[1], ()))
brlev, brlev_dims = vector_headers.get('brlev', (field.brlev, ()))
# Find all the non-trivial dimension values
dims = set(filter(None, [blev_dims, lblev_dims, bhlev_dims, bhrlev_dims,
brsvd1_dims, brsvd2_dims, brlev_dims]))
if len(dims) > 1:
raise TranslationError('Unsupported multiple values for vertical '
'dimension.')
if dims:
v_dims = dims.pop()
if len(v_dims) > 1:
raise TranslationError('Unsupported multi-dimension vertical '
'headers.')
else:
v_dims = ()
coords_and_dims, factories = _convert_vertical_coords(field.lbcode,
field.lbvc,
blev, lblev,
field.stash,
bhlev, bhrlev,
brsvd1, brsvd2,
brlev, v_dims)
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# Realization (aka ensemble) (--> scalar coordinates)
aux_coords_and_dims.extend(_convert_scalar_realization_coords(
lbrsvd4=field.lbrsvd[3]))
# Pseudo-level coordinate (--> scalar coordinates)
aux_coords_and_dims.extend(_convert_scalar_pseudo_level_coords(
lbuser5=field.lbuser[4]))
return ConversionMetadata(factories, references, standard_name, long_name,
units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims)
def _convert_collation(collation):
"""
Converts a FieldCollation into the corresponding items of Cube
metadata.
Args:
* collation:
A FieldCollation object.
Returns:
A :class:`iris.fileformats.rules.ConversionMetadata` object.
.. note:
This is the 'loader.converter', in the control structure passed to the
generic rules code, :meth:`iris.fileformats.rules.load_cubes`.
"""
from iris.fileformats.rules import ConversionMetadata
from iris.fileformats.pp_rules import (_convert_time_coords,
_convert_vertical_coords,
_convert_scalar_realization_coords,
_convert_scalar_pseudo_level_coords,
_all_other_rules)
# For all the scalar conversions, all fields in the collation will
# give the same result, so the choice is arbitrary.
field = collation.fields[0]
# Call "all other" rules.
(references, standard_name, long_name, units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims) = _all_other_rules(field)
# Adjust any dimension bindings to account for the extra leading
# dimensions added by the collation.
if collation.vector_dims_shape:
def _adjust_dims(coords_and_dims, n_dims):
def adjust(dims):
if dims is not None:
dims += n_dims
return dims
return [(coord, adjust(dims)) for coord, dims in coords_and_dims]
n_collation_dims = len(collation.vector_dims_shape)
dim_coords_and_dims = _adjust_dims(dim_coords_and_dims,
n_collation_dims)
aux_coords_and_dims = _adjust_dims(aux_coords_and_dims,
n_collation_dims)
# Dimensions to which we've already assigned dimension coordinates.
dim_coord_dims = set()
# Helper call to choose which coords are dimensions and which auxiliary.
def _bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims):
def key_func(item):
return _HINTS.get(item[0].name(), len(_HINTS))
# Target the first DimCoord for a dimension at dim_coords,
# and target everything else at aux_coords.
for coord, dims in sorted(coords_and_dims, key=key_func):
if (isinstance(coord, DimCoord) and dims is not None and
len(dims) == 1 and dims[0] not in dim_coord_dims):
dim_coords_and_dims.append((coord, dims))
dim_coord_dims.add(dims[0])
else:
aux_coords_and_dims.append((coord, dims))
# Call "time" rules.
#
# For "normal" (non-cross-sectional) time values.
vector_headers = collation.element_arrays_and_dims
# If the collation doesn't define a vector of values for a
# particular header then it must be constant over all fields in the
# collation. In which case it's safe to get the value from any field.
t1, t1_dims = vector_headers.get('t1', (field.t1, ()))
t2, t2_dims = vector_headers.get('t2', (field.t2, ()))
lbft, lbft_dims = vector_headers.get('lbft', (field.lbft, ()))
coords_and_dims = _convert_time_coords(field.lbcode, field.lbtim,
field.time_unit('hours'),
t1, t2, lbft,
t1_dims, t2_dims, lbft_dims)
# Bind resulting coordinates to dimensions, where suitable.
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# Call "vertical" rules.
#
# "Normal" (non-cross-sectional) vertical levels
blev, blev_dims = vector_headers.get('blev', (field.blev, ()))
lblev, lblev_dims = vector_headers.get('lblev', (field.lblev, ()))
bhlev, bhlev_dims = vector_headers.get('bhlev', (field.bhlev, ()))
bhrlev, bhrlev_dims = vector_headers.get('bhrlev', (field.bhrlev, ()))
brsvd1, brsvd1_dims = vector_headers.get('brsvd1', (field.brsvd[0], ()))
brsvd2, brsvd2_dims = vector_headers.get('brsvd2', (field.brsvd[1], ()))
brlev, brlev_dims = vector_headers.get('brlev', (field.brlev, ()))
# Find all the non-trivial dimension values
dims = set(filter(None, [blev_dims, lblev_dims, bhlev_dims, bhrlev_dims,
brsvd1_dims, brsvd2_dims, brlev_dims]))
if len(dims) > 1:
raise TranslationError('Unsupported multiple values for vertical '
'dimension.')
if dims:
v_dims = dims.pop()
if len(v_dims) > 1:
raise TranslationError('Unsupported multi-dimension vertical '
'headers.')
else:
v_dims = ()
coords_and_dims, factories = _convert_vertical_coords(field.lbcode,
field.lbvc,
blev, lblev,
field.stash,
bhlev, bhrlev,
brsvd1, brsvd2,
brlev, v_dims)
# Bind resulting coordinates to dimensions, where suitable.
_bind_coords(coords_and_dims, dim_coord_dims, dim_coords_and_dims,
aux_coords_and_dims)
# Realization (aka ensemble) (--> scalar coordinates)
aux_coords_and_dims.extend(_convert_scalar_realization_coords(
lbrsvd4=field.lbrsvd[3]))
# Pseudo-level coordinate (--> scalar coordinates)
aux_coords_and_dims.extend(_convert_scalar_pseudo_level_coords(
lbuser5=field.lbuser[4]))
return ConversionMetadata(factories, references, standard_name, long_name,
units, attributes, cell_methods,
dim_coords_and_dims, aux_coords_and_dims)
