def test_relative_vorticity_distance(self):
x_min = 0.0
x_max = 100.0
dx = 1.0
x_1d = numpy.arange(x_min, x_max, dx)
size = x_1d.size
data_1d = x_1d * 2.0 + 1.0
data_2d = numpy.broadcast_to(data_1d[numpy.newaxis, :], (size, size))
dim_x = cf.DimensionCoordinate(
data=cf.Data(x_1d, "m"), properties={"axis": "X"}
)
dim_y = cf.DimensionCoordinate(
data=cf.Data(x_1d, "m"), properties={"axis": "Y"}
)
u = cf.Field()
X = u.set_construct(cf.DomainAxis(size=dim_x.data.size))
Y = u.set_construct(cf.DomainAxis(size=dim_y.data.size))
u.set_construct(dim_x, axes=[X])
u.set_construct(dim_y, axes=[Y])
u.set_data(cf.Data(data_2d, "m/s"), axes=("Y", "X"))
v = cf.Field()
v.set_construct(cf.DomainAxis(size=dim_x.data.size))
v.set_construct(cf.DomainAxis(size=dim_y.data.size))
v.set_construct(dim_x, axes=[X])
v.set_construct(dim_y, axes=[Y])
v.set_data(cf.Data(data_2d, "m/s"), axes=("X", "Y"))
rv = cf.relative_vorticity(u, v, one_sided_at_boundary=True)
self.assertTrue((rv.array == 0.0).all())
def test_relative_vorticity_distance(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
returncf
x_min = 0.0
x_max = 100.0
dx = 1.0
x_1d = numpy.arange(x_min, x_max, dx)
size = x_1d.size
data_1d = x_1d * 2.0 + 1.0
data_2d = numpy.broadcast_to(data_1d[numpy.newaxis, :], (size, size))
dim_x = cf.DimensionCoordinate(data=cf.Data(x_1d, 'm'),
properties={'axis': 'X'})
dim_y = cf.DimensionCoordinate(data=cf.Data(x_1d, 'm'),
properties={'axis': 'Y'})
u = cf.Field()
X = u.set_construct(cf.DomainAxis(size=dim_x.data.size))
Y = u.set_construct(cf.DomainAxis(size=dim_y.data.size))
u.set_construct(dim_x, axes=[X])
u.set_construct(dim_y, axes=[Y])
u.set_data(cf.Data(data_2d, 'm/s'), axes=('Y', 'X'))
v = cf.Field()
v.set_construct(cf.DomainAxis(size=dim_x.data.size))
v.set_construct(cf.DomainAxis(size=dim_y.data.size))
v.set_construct(dim_x, axes=[X])
v.set_construct(dim_y, axes=[Y])
v.set_data(cf.Data(data_2d, 'm/s'), axes=('X', 'Y'))
rv = cf.relative_vorticity(u, v, one_sided_at_boundary=True)
self.assertTrue((rv.array == 0.0).all())
def test_relative_vorticity_latlong(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
lat_min = -90.0
lat_max = 90.0
dlat = 1.0
lat_1d = numpy.arange(lat_min, lat_max, dlat)
lat_size = lat_1d.size
lon_min = 0.0
lon_max = 359.0
dlon = 1.0
lon_1d = numpy.arange(lon_min, lon_max, dlon)
lon_size = lon_1d.size
u_1d = lat_1d * 2.0 + 1.0
u_2d = numpy.broadcast_to(lat_1d[numpy.newaxis, :],
(lon_size, lat_size))
v_1d = lon_1d * 2.0 + 1.0
v_2d = numpy.broadcast_to(lon_1d[:, numpy.newaxis],
(lon_size, lat_size))
v_2d = v_2d * numpy.cos(lat_1d * numpy.pi / 180.0)[numpy.newaxis, :]
rv_array = (u_2d / cf.Data(6371229.0, 'meters') *
numpy.tan(lat_1d * numpy.pi / 180.0)[numpy.newaxis, :])
dim_x = cf.DimensionCoordinate(data=cf.Data(lon_1d, 'degrees_east'),
properties={'axis': 'X'})
dim_y = cf.DimensionCoordinate(data=cf.Data(lat_1d, 'degrees_north'),
properties={'axis': 'Y'})
u = cf.Field()
u.set_construct(cf.DomainAxis(size=lon_1d.size))
u.set_construct(cf.DomainAxis(size=lat_1d.size))
u.set_construct(dim_x)
u.set_construct(dim_y)
u.set_data(cf.Data(u_2d, 'm/s'), axes=('X', 'Y'))
u.cyclic('X', period=360.0)
v = cf.Field()
v.set_construct(cf.DomainAxis(size=lon_1d.size))
v.set_construct(cf.DomainAxis(size=lat_1d.size))
v.set_construct(dim_x)
v.set_construct(dim_y)
v.set_data(cf.Data(v_2d, 'm/s'), axes=('X', 'Y'))
v.cyclic('X', period=360.0)
rv = cf.relative_vorticity(u, v, wrap=True)
self.assertTrue(numpy.allclose(rv.array, rv_array))
def test_relative_vorticity_latlong(self):
lat_min = -90.0
lat_max = 90.0
dlat = 1.0
lat_1d = numpy.arange(lat_min, lat_max, dlat)
lat_size = lat_1d.size
lon_min = 0.0
lon_max = 359.0
dlon = 1.0
lon_1d = numpy.arange(lon_min, lon_max, dlon)
lon_size = lon_1d.size
u_1d = lat_1d * 2.0 + 1.0
u_2d = numpy.broadcast_to(u_1d[numpy.newaxis, :], (lon_size, lat_size))
v_1d = lon_1d * 2.0 + 1.0
v_2d = numpy.broadcast_to(v_1d[:, numpy.newaxis], (lon_size, lat_size))
v_2d = v_2d * numpy.cos(lat_1d * numpy.pi / 180.0)[numpy.newaxis, :]
rv_array = (
u_2d
/ cf.Data(6371229.0, "meters")
* numpy.tan(lat_1d * numpy.pi / 180.0)[numpy.newaxis, :]
)
dim_x = cf.DimensionCoordinate(
data=cf.Data(lon_1d, "degrees_east"), properties={"axis": "X"}
)
dim_y = cf.DimensionCoordinate(
data=cf.Data(lat_1d, "degrees_north"), properties={"axis": "Y"}
)
u = cf.Field()
u.set_construct(cf.DomainAxis(size=lon_1d.size))
u.set_construct(cf.DomainAxis(size=lat_1d.size))
u.set_construct(dim_x)
u.set_construct(dim_y)
u.set_data(cf.Data(u_2d, "m/s"), axes=("X", "Y"))
u.cyclic("X", period=360.0)
v = cf.Field()
v.set_construct(cf.DomainAxis(size=lon_1d.size))
v.set_construct(cf.DomainAxis(size=lat_1d.size))
v.set_construct(dim_x)
v.set_construct(dim_y)
v.set_data(cf.Data(v_2d, "m/s"), axes=("X", "Y"))
v.cyclic("X", period=360.0)
rv = cf.relative_vorticity(u, v, wrap=False)
self.assertTrue(numpy.allclose(rv.array, rv_array))
def test_write_reference_datetime(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
for reference_datetime in ('1751-2-3', '1492-12-30'):
for chunksize in self.chunk_sizes:
cf.chunksize(chunksize)
f = cf.read(self.filename)[0]
t = cf.DimensionCoordinate(
data=cf.Data([123], 'days since 1750-1-1')
)
t.standard_name = 'time'
axisT = f.set_construct(cf.DomainAxis(1))
f.set_construct(t, axes=[axisT])
cf.write(f, tmpfile, fmt='NETCDF4',
reference_datetime=reference_datetime)
g = cf.read(tmpfile)[0]
t = g.dimension_coordinate('T')
self.assertEqual(
t.Units, cf.Units('days since ' + reference_datetime),
('Units written were ' + repr(t.Units.reftime)
+ ' not ' + repr(reference_datetime)))
# --- End: for
cf.chunksize(self.original_chunksize)
def test_write_reference_datetime(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
for reference_datetime in ("1751-2-3", "1492-12-30"):
for chunksize in self.chunk_sizes:
cf.chunksize(chunksize)
f = cf.read(self.filename)[0]
t = cf.DimensionCoordinate(
data=cf.Data([123], "days since 1750-1-1"))
t.standard_name = "time"
axisT = f.set_construct(cf.DomainAxis(1))
f.set_construct(t, axes=[axisT])
cf.write(
f,
tmpfile,
fmt="NETCDF4",
reference_datetime=reference_datetime,
)
g = cf.read(tmpfile)[0]
t = g.dimension_coordinate("T")
self.assertEqual(
t.Units,
cf.Units("days since " + reference_datetime),
("Units written were " + repr(t.Units.reftime) + " not " +
repr(reference_datetime)),
)
# --- End: for
cf.chunksize(self.original_chunksize)
def test_DomainAxis(self):
x = cf.DomainAxis(size=111)
x.nc_set_dimension("tas")
self.assertEqual(x.size, 111)
del x.size
self.assertIsNone(getattr(x, "size", None))
x.size = 56
self.assertEqual(x.size, 56)
self.assertEqual(x, 56)
x += 1
self.assertEqual(x.size, 57)
x -= 1
self.assertEqual(x.size, 56)
y = x + 1
self.assertEqual(y.size, 57)
y = x - 1
self.assertEqual(y.size, 55)
y = 1 + x
self.assertEqual(y.size, 57)
self.assertEqual(int(x), 56)
self.assertGreater(x, 1)
self.assertLess(x, 100)
self.assertGreaterEqual(x, 1)
self.assertLessEqual(x, 100)
self.assertNotEqual(x, 100)
hash(x)
data=cf.Data(numpy.array([0, 0, 2], dtype='int8')))
fa
p = cf.Field()
p
p.set_property('standard_name', 'precipitation_flux')
p
dc = cf.DimensionCoordinate()
dc
dc.set_property('long_name', 'Longitude')
dc.set_data(cf.Data([1, 2, 3.]))
dc
fa = cf.FieldAncillary(data=cf.Data(numpy.array([0, 0, 2], dtype='int8')))
fa
fa.set_property('standard_name', 'precipitation_flux status_flag')
fa
longitude_axis = p.set_construct(cf.DomainAxis(3))
longitude_axis
key = p.set_construct(dc, axes=longitude_axis)
key
cm = cf.CellMethod(axes=longitude_axis, method='minimum')
p.set_construct(cm)
import numpy
import cf
# Initialise the field construct with properties
Q = cf.Field(properties={
'project': 'research',
'standard_name': 'specific_humidity',
'units': '1'
})
def test_GATHERING_create(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
# Define the gathered values
gathered_array = numpy.array([[280, 282.5, 281], [279, 278, 277.5]],
dtype='float32')
# Define the list array values
list_array = [1, 4, 5]
# Initialise the list variable
list_variable = cf.List(data=cf.Data(list_array))
# Initialise the gathered array object
array = cf.GatheredArray(compressed_array=cf.Data(gathered_array),
compressed_dimension=1,
shape=(2, 3, 2),
size=12,
ndim=3,
list_variable=list_variable)
# Create the field construct with the domain axes and the
# gathered array
tas = cf.Field(properties={
'standard_name': 'air_temperature',
'units': 'K'
})
# Create the domain axis constructs for the uncompressed array
T = tas.set_construct(cf.DomainAxis(2))
Y = tas.set_construct(cf.DomainAxis(3))
X = tas.set_construct(cf.DomainAxis(2))
uncompressed_array = numpy.ma.masked_array(data=[[[1, 280.0], [1, 1],
[282.5, 281.0]],
[[1, 279.0], [1, 1],
[278.0, 277.5]]],
mask=[[[True, False],
[True, True],
[False, False]],
[[True, False],
[True, True],
[False, False]]],
fill_value=1e+20,
dtype='float32')
for chunksize in (1000000, ):
cf.chunksize(chunksize)
message = 'chunksize=' + str(chunksize)
# Set the data for the field
tas.set_data(cf.Data(array), axes=[T, Y, X])
self.assertTrue((tas.data.array == uncompressed_array).all(),
message)
self.assertEqual(tas.data.get_compression_type(), 'gathered',
message)
self.assertTrue(
(tas.data.compressed_array == numpy.array(
[[280., 282.5, 281.], [279., 278., 277.5]],
dtype='float32')).all(), message)
self.assertTrue(
(tas.data.get_list().data.array == numpy.array([1, 4,
5])).all(),
message)
def _formula_terms(standard_name):
"""Return a field construct with a vertical CRS, its computed non-
parametric coordinates, and the computed standard name."""
# field: air_temperature
field = cf.Field()
field.set_properties({"standard_name": "air_temperature", "units": "K"})
data = cf.Data([0, 1, 2], units="K", dtype="f8")
# domain_axis: Z
c = cf.DomainAxis()
c.set_size(3)
c.nc_set_dimension("z")
axisZ = field.set_construct(c, key="domainaxis1", copy=False)
field.set_data(data)
# coordinate_reference:
coordref = cf.CoordinateReference()
coordref.coordinate_conversion.set_parameter(
"standard_name", standard_name
)
aux = cf.AuxiliaryCoordinate()
aux.long_name = "Computed from parametric {} vertical coordinates".format(
standard_name
)
if standard_name == "atmosphere_ln_pressure_coordinate":
computed_standard_name = "air_pressure"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([700, 500, 300], "hPa", dtype="f8")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[800, 600], [600, 400], [400, 200]], "hPa", dtype="f8")
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: p0
p0 = cf.DomainAncillary()
p0.standard_name = (
"reference_air_pressure_for_atmosphere_vertical_coordinate"
)
data = cf.Data(1000.0, units="hPa", dtype="f8")
p0.set_data(data)
p0_key = field.set_construct(p0, axes=(), copy=False)
# domain_ancillary: Z
lev = cf.DomainAncillary()
lev.standard_name = standard_name
data = -(aux.data / p0.data).log()
lev.set_data(data)
bounds = cf.Bounds()
data = -(aux.bounds.data / p0.data).log()
bounds.set_data(data)
lev.set_bounds(bounds)
lev_key = field.set_construct(lev, axes=axisZ, copy=False)
# dimension_coordinate: Z
levc = cf.DimensionCoordinate(source=lev)
levc_key = field.set_construct(levc, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({levc_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{"p0": p0_key, "lev": lev_key}
)
field.set_construct(coordref)
elif standard_name == "atmosphere_sigma_coordinate":
computed_standard_name = "air_pressure"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([700, 500, 300], "hPa", dtype="f8")
aux.set_data(data)
b = cf.Bounds()
data = cf.Data([[800, 600], [600, 400], [400, 200]], "hPa", dtype="f8")
b.set_data(data)
aux.set_bounds(b)
# domain_ancillary: ps
ps = cf.DomainAncillary()
ps.standard_name = "surface_air_pressure"
data = cf.Data(1000, units="hPa", dtype="f8")
ps.set_data(data)
ps_key = field.set_construct(ps, axes=(), copy=False)
# domain_ancillary: ptop
ptop = cf.DomainAncillary()
ptop.standard_name = "air_pressure_at_top_of_atmosphere_model"
data = cf.Data(10, units="hPa", dtype="f8")
ptop.set_data(data)
ptop_key = field.set_construct(ptop, axes=(), copy=False)
# domain_ancillary: sigma
sigma = cf.DomainAncillary()
sigma.standard_name = standard_name
data = cf.Data([0.6969697, 0.49494949, 0.29292929])
sigma.set_data(data)
b = cf.Bounds()
data = cf.Data(
[
[0.7979798, 0.5959596],
[0.5959596, 0.39393939],
[0.39393939, 0.19191919],
]
)
b.set_data(data)
sigma.set_bounds(b)
sigma_key = field.set_construct(sigma, axes=axisZ, copy=False)
# dimension_coordinate: sigma
sigmac = cf.DimensionCoordinate(source=sigma)
sigmac_key = field.set_construct(sigmac, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sigmac_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{"ptop": ptop_key, "ps": ps_key, "sigma": sigma_key}
)
field.set_construct(coordref)
elif standard_name == "atmosphere_hybrid_sigma_pressure_coordinate":
computed_standard_name = "air_pressure"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([700, 500, 300], "hPa", dtype="f8")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[800, 600], [600, 400], [400, 200]], "hPa", dtype="f8")
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: ps
ps = cf.DomainAncillary()
ps.standard_name = "surface_air_pressure"
data = cf.Data(1000, units="hPa", dtype="f8")
ps.set_data(data)
ps_key = field.set_construct(ps, axes=(), copy=False)
# domain_ancillary: p0
p0 = cf.DomainAncillary()
data = cf.Data(1000, units="hPa", dtype="f8")
p0.set_data(data)
p0_key = field.set_construct(p0, axes=(), copy=False)
# domain_ancillary: a
a = cf.DomainAncillary()
data = cf.Data([0.6, 0.3, 0], dtype="f8")
a.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.75, 0.45], [0.45, 0.15], [0.15, 0]])
bounds.set_data(data)
a.set_bounds(bounds)
a_key = field.set_construct(a, axes=axisZ, copy=False)
# domain_ancillary: b
b = cf.DomainAncillary()
data = cf.Data([0.1, 0.2, 0.3], dtype="f8")
b.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.05, 0.15], [0.15, 0.25], [0.25, 0.2]])
bounds.set_data(data)
b.set_bounds(bounds)
b_key = field.set_construct(b, axes=axisZ, copy=False)
# dimension_coordinate: sigma
sigma = cf.DimensionCoordinate()
sigma.standard_name = standard_name
data = cf.Data([0.6969697, 0.49494949, 0.29292929])
sigma.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[
[0.7979798, 0.5959596],
[0.5959596, 0.39393939],
[0.39393939, 0.19191919],
]
)
bounds.set_data(data)
sigma.set_bounds(bounds)
sigma_key = field.set_construct(sigma, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sigma_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{"p0": p0_key, "a": a_key, "b": b_key, "ps": ps_key}
)
field.set_construct(coordref)
elif standard_name == "atmosphere_sleve_coordinate":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([100, 200, 300], "m", dtype="f8")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[50, 150], [150, 250], [250, 350]], "m", dtype="f8")
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: ztop
ztop = cf.DomainAncillary()
ztop.standard_name = "altitude_at_top_of_atmosphere_model"
data = cf.Data(1000, units="m", dtype="f8")
ztop.set_data(data)
ztop_key = field.set_construct(ztop, axes=(), copy=False)
# domain_ancillary: zsurf1
zsurf1 = cf.DomainAncillary()
data = cf.Data(90, units="m", dtype="f8")
zsurf1.set_data(data)
zsurf1_key = field.set_construct(zsurf1, axes=(), copy=False)
# domain_ancillary: zsurf2
zsurf2 = cf.DomainAncillary()
data = cf.Data(0.1, units="m", dtype="f8")
zsurf2.set_data(data)
zsurf2_key = field.set_construct(zsurf2, axes=(), copy=False)
# domain_ancillary: b1
b1 = cf.DomainAncillary()
data = cf.Data([0.05, 0.04, 0.03], dtype="f8")
b1.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.055, 0.045], [0.045, 0.035], [0.035, 0.025]])
bounds.set_data(data)
b1.set_bounds(bounds)
b1_key = field.set_construct(b1, axes=axisZ, copy=False)
# domain_ancillary: b2
b2 = cf.DomainAncillary()
data = cf.Data([0.5, 0.4, 0.3])
b2.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.55, 0.45], [0.45, 0.35], [0.35, 0.25]])
bounds.set_data(data)
b2.set_bounds(bounds)
b2_key = field.set_construct(b2, axes=axisZ, copy=False)
# domain_ancillary: a
a = cf.DomainAncillary()
data = cf.Data([0.09545, 0.19636, 0.29727])
a.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[[0.044995, 0.145905], [0.145905, 0.246815], [0.246815, 0.347725]]
)
bounds.set_data(data)
a.set_bounds(bounds)
a_key = field.set_construct(a, axes=axisZ, copy=False)
# coordinate_reference:
coordref.coordinate_conversion.set_domain_ancillaries(
{
"zsurf1": zsurf1_key,
"a": a_key,
"b1": b1_key,
"b2": b2_key,
"zsurf2": zsurf2_key,
"ztop": ztop_key,
}
)
field.set_construct(coordref)
elif standard_name == "ocean_sigma_coordinate":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([10, 20, 30], "m", dtype="f8")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[5, 15], [15, 25], [25, 35]], "m", dtype="f8")
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: depth
depth = cf.DomainAncillary()
depth.standard_name = "sea_floor_depth_below_geoid"
data = cf.Data(-1000.0, units="m")
depth.set_data(data)
depth_key = field.set_construct(depth, axes=(), copy=False)
# domain_ancillary: eta
eta = cf.DomainAncillary()
eta.standard_name = "sea_surface_height_above_geoid"
data = cf.Data(100.0, units="m")
eta.set_data(data)
eta_key = field.set_construct(eta, axes=(), copy=False)
# domain_ancillary: sigma
sigma = cf.DomainAncillary()
sigma.standard_name = standard_name
data = cf.Data([0.1, 0.08888888888888889, 0.07777777777777778])
sigma.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[
[0.10555556, 0.09444444],
[0.09444444, 0.08333333],
[0.08333333, 0.07222222],
]
)
bounds.set_data(data)
sigma.set_bounds(bounds)
sigma_key = field.set_construct(sigma, axes=axisZ, copy=False)
# dimension_coordinate: sigma
sigmac = cf.DimensionCoordinate(source=sigma)
sigmac_key = field.set_construct(sigmac, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sigmac_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{"depth": depth_key, "eta": eta_key, "sigma": sigma_key}
)
field.set_construct(coordref)
elif standard_name == "ocean_s_coordinate":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([15.01701191, 31.86034296, 40.31150319], units="m")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[
[15.01701191, 23.42877638],
[23.42877638, 31.86034296],
[31.86034296, 40.31150319],
],
units="m",
)
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: depth
depth = cf.DomainAncillary()
depth.standard_name = "sea_floor_depth_below_geoid"
data = cf.Data(-1000.0, units="m")
depth.set_data(data)
depth_key = field.set_construct(depth, axes=(), copy=False)
# domain_ancillary: eta
eta = cf.DomainAncillary()
eta.standard_name = "sea_surface_height_above_geoid"
data = cf.Data(100.0, units="m")
eta.set_data(data)
eta_key = field.set_construct(eta, axes=(), copy=False)
# domain_ancillary: depth_c
depth_c = cf.DomainAncillary()
data = cf.Data(10.0, units="m")
depth_c.set_data(data)
depth_c_key = field.set_construct(depth_c, axes=(), copy=False)
# domain_ancillary: a
a = cf.DomainAncillary()
data = cf.Data(0.5)
a.set_data(data)
a_key = field.set_construct(a, axes=(), copy=False)
# domain_ancillary: b
b = cf.DomainAncillary()
data = cf.Data(0.75)
b.set_data(data)
b_key = field.set_construct(b, axes=(), copy=False)
# domain_ancillary: s
s = cf.DomainAncillary()
s.standard_name = standard_name
data = cf.Data([0.1, 0.08, 0.07])
s.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.10, 0.09], [0.09, 0.08], [0.08, 0.07]])
bounds.set_data(data)
s.set_bounds(bounds)
s_key = field.set_construct(s, axes=axisZ, copy=False)
# dimension_coordinate: s
sc = cf.DimensionCoordinate(source=s)
sc_key = field.set_construct(sc, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sc_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{
"depth": depth_key,
"eta": eta_key,
"depth_c": depth_c_key,
"a": a_key,
"b": b_key,
"s": s_key,
}
)
field.set_construct(coordref)
elif standard_name == "ocean_s_coordinate_g1":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([555.4, 464.32, 373.33], units="m")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[[600.85, 509.86], [509.86, 418.87], [418.87, 327.88]], units="m"
)
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: depth
depth = cf.DomainAncillary()
depth.standard_name = "sea_floor_depth_below_geoid"
data = cf.Data(-1000.0, units="m")
depth.set_data(data)
depth_key = field.set_construct(depth, axes=(), copy=False)
# domain_ancillary: eta
eta = cf.DomainAncillary()
eta.standard_name = "sea_surface_height_above_geoid"
data = cf.Data(100.0, units="m")
eta.set_data(data)
eta_key = field.set_construct(eta, axes=(), copy=False)
# domain_ancillary: depth_c
depth_c = cf.DomainAncillary()
data = cf.Data(10.0, units="m")
depth_c.set_data(data)
depth_c_key = field.set_construct(depth_c, axes=(), copy=False)
# domain_ancillary: C
C = cf.DomainAncillary()
data = cf.Data([-0.5, -0.4, -0.3])
C.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[-0.55, -0.45], [-0.45, -0.35], [-0.35, -0.25]])
bounds.set_data(data)
C.set_bounds(bounds)
C_key = field.set_construct(C, axes=axisZ, copy=False)
# domain_ancillary: s
s = cf.DomainAncillary()
s.standard_name = standard_name
data = cf.Data([0.1, 0.08, 0.07])
s.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.10, 0.09], [0.09, 0.08], [0.08, 0.07]])
bounds.set_data(data)
s.set_bounds(bounds)
s_key = field.set_construct(s, axes=axisZ, copy=False)
# dimension_coordinate: s
sc = cf.DimensionCoordinate(source=s)
sc_key = field.set_construct(sc, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sc_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{
"depth": depth_key,
"eta": eta_key,
"depth_c": depth_c_key,
"C": C_key,
"s": s_key,
}
)
field.set_construct(coordref)
elif standard_name == "ocean_s_coordinate_g2":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([555.45454545, 464.36363636, 373.36363636], units="m")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[
[600.90909091, 509.90909091],
[509.90909091, 418.90909091],
[418.90909091, 327.90909091],
],
units="m",
)
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: depth
depth = cf.DomainAncillary()
depth.standard_name = "sea_floor_depth_below_geoid"
data = cf.Data(-1000.0, units="m")
depth.set_data(data)
depth_key = field.set_construct(depth, axes=(), copy=False)
# domain_ancillary: eta
eta = cf.DomainAncillary()
eta.standard_name = "sea_surface_height_above_geoid"
data = cf.Data(100.0, units="m")
eta.set_data(data)
eta_key = field.set_construct(eta, axes=(), copy=False)
# domain_ancillary: depth_c
depth_c = cf.DomainAncillary()
data = cf.Data(10.0, units="m")
depth_c.set_data(data)
depth_c_key = field.set_construct(depth_c, axes=(), copy=False)
# domain_ancillary: C
C = cf.DomainAncillary()
data = cf.Data([-0.5, -0.4, -0.3])
C.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[-0.55, -0.45], [-0.45, -0.35], [-0.35, -0.25]])
bounds.set_data(data)
C.set_bounds(bounds)
C_key = field.set_construct(C, axes=axisZ, copy=False)
# domain_ancillary: s
s = cf.DomainAncillary()
s.standard_name = standard_name
data = cf.Data([0.1, 0.08, 0.07])
s.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.10, 0.09], [0.09, 0.08], [0.08, 0.07]])
bounds.set_data(data)
s.set_bounds(bounds)
s_key = field.set_construct(s, axes=axisZ, copy=False)
# dimension_coordinate: s
sc = cf.DimensionCoordinate(source=s)
sc_key = field.set_construct(sc, axes=axisZ, copy=False)
# coordinat
# coordinate_reference:
coordref.set_coordinates({sc_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{
"depth": depth_key,
"eta": eta_key,
"depth_c": depth_c_key,
"C": C_key,
"s": s_key,
}
)
field.set_construct(coordref)
elif standard_name == "ocean_sigma_z_coordinate":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data([10.0, 30.0, 40.0], "m", dtype="f8")
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[[10.0, 19.0], [25.0, 35.0], [35.0, 45.0]], "m", dtype="f8"
)
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: depth
depth = cf.DomainAncillary()
depth.standard_name = "sea_floor_depth_below_geoid"
data = cf.Data(-1000.0, units="m")
depth.set_data(data)
depth_key = field.set_construct(depth, axes=(), copy=False)
# domain_ancillary: eta
eta = cf.DomainAncillary()
eta.standard_name = "sea_surface_height_above_geoid"
data = cf.Data(100.0, units="m")
eta.set_data(data)
eta_key = field.set_construct(eta, axes=(), copy=False)
# domain_ancillary: depth_c
depth_c = cf.DomainAncillary()
data = cf.Data(10.0, units="m")
depth_c.set_data(data)
depth_c_key = field.set_construct(depth_c, axes=(), copy=False)
# domain_ancillary: nsigma
nsigma = cf.DomainAncillary()
data = cf.Data(1)
nsigma.set_data(data)
nsigma_key = field.set_construct(nsigma, axes=(), copy=False)
# domain_ancillary: zlev
zlev = cf.DomainAncillary()
zlev.standard_name = "altitude"
data = cf.Data([20, 30, 40], units="m", dtype="f8")
zlev.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[15, 25], [25, 35], [35, 45]], units="m", dtype="f8")
bounds.set_data(data)
zlev.set_bounds(bounds)
zlev_key = field.set_construct(zlev, axes=axisZ, copy=False)
# domain_ancillary: sigma
sigma = cf.DomainAncillary()
sigma.standard_name = standard_name
data = cf.Data([0.1, 0.08, 0.07])
sigma.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.10, 0.09], [0.09, 0.08], [0.08, 0.07]])
bounds.set_data(data)
sigma.set_bounds(bounds)
sigma_key = field.set_construct(sigma, axes=axisZ, copy=False)
# dimension_coordinate: sigma
sigmac = cf.DimensionCoordinate(source=sigma)
sigmac_key = field.set_construct(sigmac, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sigmac_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{
"depth": depth_key,
"eta": eta_key,
"depth_c": depth_c_key,
"nsigma": nsigma_key,
"zlev": zlev_key,
"sigma": sigma_key,
}
)
field.set_construct(coordref)
elif standard_name == "ocean_double_sigma_coordinate":
computed_standard_name = "altitude"
# Computed vertical corodinates
aux.standard_name = computed_standard_name
data = cf.Data(
[0.15000000000000002, 0.12, 932.895], units="m", dtype="f8"
)
aux.set_data(data)
bounds = cf.Bounds()
data = cf.Data(
[
[1.50000e-01, 1.35000e-01],
[1.35000e-01, 1.20000e-01],
[9.22880e02, 9.32895e02],
],
units="m",
dtype="f8",
)
bounds.set_data(data)
aux.set_bounds(bounds)
# domain_ancillary: depth
depth = cf.DomainAncillary()
depth.standard_name = "sea_floor_depth_below_geoid"
data = cf.Data(-1000.0, units="m")
depth.set_data(data)
depth_key = field.set_construct(depth, axes=(), copy=False)
# domain_ancillary: z1
z1 = cf.DomainAncillary()
data = cf.Data(2, units="m")
z1.set_data(data)
z1_key = field.set_construct(z1, axes=(), copy=False)
# domain_ancillary: z2
z2 = cf.DomainAncillary()
data = cf.Data(1.5, units="m")
z2.set_data(data)
z2_key = field.set_construct(z2, axes=(), copy=False)
# domain_ancillary: a
a = cf.DomainAncillary()
data = cf.Data(2.5, units="m")
a.set_data(data)
a_key = field.set_construct(a, axes=(), copy=False)
# domain_ancillary: href
href = cf.DomainAncillary()
data = cf.Data(10.5, units="m")
href.set_data(data)
href_key = field.set_construct(href, axes=(), copy=False)
# domain_ancillary: k_c
k_c = cf.DomainAncillary()
data = cf.Data(1)
k_c.set_data(data)
k_c_key = field.set_construct(k_c, axes=(), copy=False)
# dimension_coordinate: sigma
sigma = cf.DomainAncillary()
sigma.standard_name = standard_name
data = cf.Data([0.1, 0.08, 0.07])
sigma.set_data(data)
bounds = cf.Bounds()
data = cf.Data([[0.10, 0.09], [0.09, 0.08], [0.08, 0.07]])
bounds.set_data(data)
sigma.set_bounds(bounds)
sigma_key = field.set_construct(sigma, axes=axisZ, copy=False)
# dimension_coordinate: sigma
sigmac = cf.DimensionCoordinate(source=sigma)
sigmac_key = field.set_construct(sigmac, axes=axisZ, copy=False)
# coordinate_reference:
coordref.set_coordinates({sigmac_key})
coordref.coordinate_conversion.set_domain_ancillaries(
{
"depth": depth_key,
"a": a_key,
"k_c": k_c_key,
"z1": z1_key,
"z2": z2_key,
"href": href_key,
"sigma": sigma_key,
}
)
field.set_construct(coordref)
else:
raise ValueError(
"Bad standard name: {}, "
"not an element of FormulaTerms.standard_names".format(
standard_name
)
)
return (field, aux, computed_standard_name)
def test_DSG_contiguous(self):
f = cf.read(self.contiguous, verbose=0)
self.assertEqual(len(f), 2)
# Select the specific humidity field
q = [
g
for g in f
if g.get_property("standard_name") == "specific_humidity"
][0]
self.assertTrue(q._equals(q.data.array.mask, self.a.mask))
self.assertTrue(
q._equals(self.a, q.data.array),
"\nself.a=\n" + str(self.a) + "\nq.array=\n" + str(q.array),
)
cf.write(f, tmpfile, verbose=0)
g = cf.read(tmpfile)
self.assertEqual(len(g), len(f))
for i in range(len(f)):
self.assertTrue(g[i].equals(f[i], verbose=2))
# ------------------------------------------------------------
# Test creation
# ------------------------------------------------------------
# Define the ragged array values
ragged_array = numpy.array(
[280, 282.5, 281, 279, 278, 279.5], dtype="float32"
)
# Define the count array values
count_array = [2, 4]
# Create the count variable
count_variable = cf.Count(data=cf.Data(count_array))
count_variable.set_property(
"long_name", "number of obs for this timeseries"
)
# Create the contiguous ragged array object
array = cf.RaggedContiguousArray(
compressed_array=cf.Data(ragged_array),
shape=(2, 4),
size=8,
ndim=2,
count_variable=count_variable,
)
# Create the field construct with the domain axes and the ragged
# array
tas = cf.Field()
tas.set_properties(
{
"standard_name": "air_temperature",
"units": "K",
"featureType": "timeSeries",
}
)
# Create the domain axis constructs for the uncompressed array
X = tas.set_construct(cf.DomainAxis(4))
Y = tas.set_construct(cf.DomainAxis(2))
# Set the data for the field
tas.set_data(cf.Data(array), axes=[Y, X])
cf.write(tas, tmpfile)
def create(dat):
"""creates cf-python Field object
:param dict dat: calpost_reader generated dict of data
:return: cf.Field
"""
v = cf.Field(
properties={
'standard_name': 'mass_concentration_of_methane_in_air',
'units': 'kg m-3',
})
v.set_data(dat['v'] / 1000)
v.nc_set_variable('methane')
if len(dat['v'].shape) == 4:
nt, nz, ny, nx = dat['v'].shape
has_z = True
print(nt, nz, ny, nx)
else:
nt, ny, nx = dat['v'].shape
has_z = False
print('a')
domain_axisT = cf.DomainAxis(nt)
domain_axisT.nc_set_unlimited(True)
domain_axisY = cf.DomainAxis(ny)
domain_axisX = cf.DomainAxis(nx)
domain_axisT.nc_set_dimension('time')
domain_axisY.nc_set_dimension('y')
domain_axisX.nc_set_dimension('x')
axisT = v.set_construct(domain_axisT)
axisY = v.set_construct(domain_axisY)
axisX = v.set_construct(domain_axisX)
if has_z:
domain_axisZ = cf.DomainAxis(nz)
domain_axisZ.nc_set_dimension('z')
axisZ = v.set_construct(domain_axisZ)
print(type(domain_axisY))
print(dir(domain_axisY))
print(domain_axisY.identity())
print('b')
x = dat['x']
y = dat['y']
dimX = cf.DimensionCoordinate(data=x * 1000,
properties={
'standard_name':
'projection_x_coordinate',
'units': 'meters'
})
dimY = cf.DimensionCoordinate(data=y * 1000,
properties={
'standard_name':
'projection_y_coordinate',
'units': 'meters'
})
dimT = cf.DimensionCoordinate(data=dat['ts'], )
dimT.nc_set_variable('time')
dimY.nc_set_variable('y')
dimX.nc_set_variable('x')
if has_z:
z = dat['z']
dimZ = cf.DimensionCoordinate(data=z,
properties={
'standard_name': 'height',
'units': 'meters'
})
dimZ.nc_set_variable('z')
print('c')
dim_t = v.set_construct(dimT, axes=domain_axisT.identity())
dim_y = v.set_construct(dimY, axes=domain_axisY.identity())
dim_x = v.set_construct(dimX, axes=domain_axisX.identity())
if has_z:
v.set_construct(dimZ, axes=domain_axisZ.identity())
print('d')
if has_z:
v.set_data_axes([axisT, axisZ, axisY, axisX])
else:
v.set_data_axes([axisT, axisY, axisX])
datum = cf.Datum(parameters={'earth_radius': 637000.0})
coordinate_conversion_h = cf.CoordinateConversion(
parameters={
'grid_mapping_name': 'lambert_conformal_conic',
'standard_parallel': (38.5, 38.5),
'longitude_of_central_meridian': -97.5,
'latitude_of_projection_origin': 38.5,
})
horizontal_crs = cf.CoordinateReference(
datum=datum,
coordinate_conversion=coordinate_conversion_h,
coordinates=[dim_x, dim_y])
v.set_construct(horizontal_crs)
return v
fa
p = cf.Field()
p
p.set_property('standard_name', 'precipitation_flux')
p
dc = cf.DimensionCoordinate()
dc
dc.set_property('long_name', 'Longitude')
dc.set_data(cf.Data([1, 2, 3.]))
dc
fa = cf.FieldAncillary(
data=cf.Data(numpy.array([0, 0, 2], dtype='int8')))
fa
fa.set_property('standard_name', 'precipitation_flux status_flag')
fa
longitude_axis = p.set_construct(cf.DomainAxis(3))
longitude_axis
key = p.set_construct(dc, axes=longitude_axis)
key
cm = cf.CellMethod(axes=longitude_axis, method='minimum')
p.set_construct(cm)
raise Exception("To proceeed, insert code block 1")
Q.dump()
raise Exception("To proceeed, insert code block 2")
print(tas)
q, t = cf.read('file.nc')
print(q.creation_commands())
import netCDF4
nc = netCDF4.Dataset('file.nc', 'r')
v = nc.variables['ta']
netcdf_array = cf.NetCDFArray(filename='file.nc', ncvar='ta',
def test_create_field(self):
# Dimension coordinates
dim1 = cf.DimensionCoordinate(
data=cf.Data(numpy.arange(10.), 'degrees'))
dim1.standard_name = 'grid_latitude'
dim0 = cf.DimensionCoordinate(
data=cf.Data(numpy.arange(9.) + 20, 'degrees'))
dim0.standard_name = 'grid_longitude'
dim0.data[-1] += 5
bounds = cf.Data(numpy.array(
[dim0.data.array-0.5, dim0.data.array+0.5]).transpose((1, 0)))
bounds[-2, 1] = 30
bounds[-1, :] = [30, 36]
dim0.set_bounds(cf.Bounds(data=bounds))
dim2 = cf.DimensionCoordinate(
data=cf.Data([1.5]),
bounds=cf.Bounds(data=cf.Data([[1, 2.]]))
)
dim2.standard_name = 'atmosphere_hybrid_height_coordinate'
# Auxiliary coordinates
ak = cf.DomainAncillary(data=cf.Data([10.], 'm'))
ak.id = 'atmosphere_hybrid_height_coordinate_ak'
bounds = cf.Bounds(data=cf.Data([[5, 15.]], units=ak.Units))
ak.set_bounds(bounds)
bk = cf.DomainAncillary(data=cf.Data([20.]))
bk.id = 'atmosphere_hybrid_height_coordinate_bk'
bounds = cf.Bounds(data=cf.Data([[14, 26.]]))
bk.set_bounds(bounds)
aux2 = cf.AuxiliaryCoordinate(
data=cf.Data(numpy.arange(-45, 45, dtype='int32').reshape(10, 9),
units='degree_N'))
aux2.standard_name = 'latitude'
aux3 = cf.AuxiliaryCoordinate(
data=cf.Data(numpy.arange(60, 150, dtype='int32').reshape(9, 10),
units='degreesE'))
aux3.standard_name = 'longitude'
aux4 = cf.AuxiliaryCoordinate(
data=cf.Data(numpy.array(
['alpha', 'beta', 'gamma', 'delta', 'epsilon',
'zeta', 'eta', 'theta', 'iota', 'kappa'],
dtype='S'
))
)
aux4.standard_name = 'greek_letters'
aux4[0] = cf.masked
# Cell measures
msr0 = cf.CellMeasure(
data=cf.Data(1+numpy.arange(90.).reshape(9, 10)*1234, 'km 2'))
msr0.measure = 'area'
# Data
data = cf.Data(numpy.arange(90.).reshape(10, 9), 'm s-1')
properties = {'standard_name': 'eastward_wind'}
f = cf.Field(properties=properties)
axisX = f.set_construct(cf.DomainAxis(9))
axisY = f.set_construct(cf.DomainAxis(10))
axisZ = f.set_construct(cf.DomainAxis(1))
f.set_data(data)
x = f.set_construct(dim0)
y = f.set_construct(dim1, axes=[axisY])
z = f.set_construct(dim2, axes=[axisZ])
lat = f.set_construct(aux2)
lon = f.set_construct(aux3, axes=['X', axisY])
f.set_construct(aux4, axes=['Y'])
ak = f.set_construct(ak, axes=['Z'])
bk = f.set_construct(bk, axes=[axisZ])
# Coordinate references
coordinate_conversion = cf.CoordinateConversion(
parameters={'grid_mapping_name': 'rotated_latitude_longitude',
'grid_north_pole_latitude': 38.0,
'grid_north_pole_longitude': 190.0})
ref0 = cf.CoordinateReference(
coordinate_conversion=coordinate_conversion,
coordinates=[x, y, lat, lon]
)
f.set_construct(msr0, axes=[axisX, 'Y'])
f.set_construct(ref0)
orog = cf.DomainAncillary()
orog.standard_name = 'surface_altitude'
orog.set_data(cf.Data(f.array*2, 'm'))
orog.transpose([1, 0], inplace=True)
orog_key = f.set_construct(orog, axes=['X', axisY])
coordinate_conversion = cf.CoordinateConversion(
parameters={
'standard_name': 'atmosphere_hybrid_height_coordinate'
},
domain_ancillaries={
'orog': orog_key,
'a': ak,
'b': bk
}
)
ref1 = cf.CoordinateReference(
coordinate_conversion=coordinate_conversion, coordinates=[z])
f.set_construct(ref1)
# Field ancillary variables
g = cf.FieldAncillary()
g.set_data(f.data)
g.transpose([1, 0], inplace=True)
g.standard_name = 'ancillary0'
g *= 0.01
f.set_construct(g)
g = cf.FieldAncillary()
g.set_data(f.data)
g.standard_name = 'ancillary1'
g *= 0.01
f.set_construct(g)
g = cf.FieldAncillary()
g.set_data(f[0, :].data)
g.squeeze(inplace=True)
g.standard_name = 'ancillary2'
g *= 0.001
f.set_construct(g)
g = cf.FieldAncillary()
g.set_data(f[:, 0].data)
g.squeeze(inplace=True)
g.standard_name = 'ancillary3'
g *= 0.001
f.set_construct(g)
f.flag_values = [1, 2, 4]
f.flag_meanings = ['a', 'bb', 'ccc']
for cm in cf.CellMethod.create(
'grid_longitude: mean grid_latitude: max'):
f.set_construct(cm)
# Write the file, and read it in
cf.write(f, self.filename, verbose=0, string=True)
g = cf.read(self.filename, squeeze=True, verbose=0)[0]
self.assertTrue(g.equals(f, verbose=0),
"Field not equal to itself read back in")
x = g.dump(display=False)
x = f.dump(display=False)
def test_create_field(self):
# Dimension coordinates
dim1 = cf.DimensionCoordinate(
data=cf.Data(numpy.arange(10.0), "degrees"))
dim1.standard_name = "grid_latitude"
dim0 = cf.DimensionCoordinate(
data=cf.Data(numpy.arange(9.0) + 20, "degrees"))
dim0.standard_name = "grid_longitude"
dim0.data[-1] += 5
bounds = cf.Data(
numpy.array([dim0.data.array - 0.5,
dim0.data.array + 0.5]).transpose((1, 0)))
bounds[-2, 1] = 30
bounds[-1, :] = [30, 36]
dim0.set_bounds(cf.Bounds(data=bounds))
dim2 = cf.DimensionCoordinate(
data=cf.Data([1.5]), bounds=cf.Bounds(data=cf.Data([[1, 2.0]])))
dim2.standard_name = "atmosphere_hybrid_height_coordinate"
# Auxiliary coordinates
ak = cf.DomainAncillary(data=cf.Data([10.0], "m"))
ak.id = "atmosphere_hybrid_height_coordinate_ak"
bounds = cf.Bounds(data=cf.Data([[5, 15.0]], units=ak.Units))
ak.set_bounds(bounds)
bk = cf.DomainAncillary(data=cf.Data([20.0]))
bk.id = "atmosphere_hybrid_height_coordinate_bk"
bounds = cf.Bounds(data=cf.Data([[14, 26.0]]))
bk.set_bounds(bounds)
aux2 = cf.AuxiliaryCoordinate(data=cf.Data(
numpy.arange(-45, 45, dtype="int32").reshape(10, 9),
units="degree_N",
))
aux2.standard_name = "latitude"
aux3 = cf.AuxiliaryCoordinate(data=cf.Data(
numpy.arange(60, 150, dtype="int32").reshape(9, 10),
units="degreesE",
))
aux3.standard_name = "longitude"
aux4 = cf.AuxiliaryCoordinate(data=cf.Data(
numpy.array(
[
"alpha",
"beta",
"gamma",
"delta",
"epsilon",
"zeta",
"eta",
"theta",
"iota",
"kappa",
],
dtype="S",
)))
aux4.standard_name = "greek_letters"
aux4[0] = cf.masked
# Cell measures
msr0 = cf.CellMeasure(
data=cf.Data(1 + numpy.arange(90.0).reshape(9, 10) * 1234, "km 2"))
msr0.measure = "area"
# Data
data = cf.Data(numpy.arange(90.0).reshape(10, 9), "m s-1")
properties = {"standard_name": "eastward_wind"}
f = cf.Field(properties=properties)
axisX = f.set_construct(cf.DomainAxis(9))
axisY = f.set_construct(cf.DomainAxis(10))
axisZ = f.set_construct(cf.DomainAxis(1))
f.set_data(data)
x = f.set_construct(dim0)
y = f.set_construct(dim1, axes=[axisY])
z = f.set_construct(dim2, axes=[axisZ])
lat = f.set_construct(aux2)
lon = f.set_construct(aux3, axes=["X", axisY])
f.set_construct(aux4, axes=["Y"])
ak = f.set_construct(ak, axes=["Z"])
bk = f.set_construct(bk, axes=[axisZ])
# Coordinate references
coordinate_conversion = cf.CoordinateConversion(
parameters={
"grid_mapping_name": "rotated_latitude_longitude",
"grid_north_pole_latitude": 38.0,
"grid_north_pole_longitude": 190.0,
})
ref0 = cf.CoordinateReference(
coordinate_conversion=coordinate_conversion,
coordinates=[x, y, lat, lon],
)
f.set_construct(msr0, axes=[axisX, "Y"])
f.set_construct(ref0)
orog = cf.DomainAncillary()
orog.standard_name = "surface_altitude"
orog.set_data(cf.Data(f.array * 2, "m"))
orog.transpose([1, 0], inplace=True)
orog_key = f.set_construct(orog, axes=["X", axisY])
coordinate_conversion = cf.CoordinateConversion(
parameters={
"standard_name": "atmosphere_hybrid_height_coordinate"
},
domain_ancillaries={
"orog": orog_key,
"a": ak,
"b": bk
},
)
ref1 = cf.CoordinateReference(
coordinate_conversion=coordinate_conversion, coordinates=[z])
f.set_construct(ref1)
# Field ancillary variables
g = cf.FieldAncillary()
g.set_data(f.data)
g.transpose([1, 0], inplace=True)
g.standard_name = "ancillary0"
g *= 0.01
f.set_construct(g)
g = cf.FieldAncillary()
g.set_data(f.data)
g.standard_name = "ancillary1"
g *= 0.01
f.set_construct(g)
g = cf.FieldAncillary()
g.set_data(f[0, :].data)
g.squeeze(inplace=True)
g.standard_name = "ancillary2"
g *= 0.001
f.set_construct(g)
g = cf.FieldAncillary()
g.set_data(f[:, 0].data)
g.squeeze(inplace=True)
g.standard_name = "ancillary3"
g *= 0.001
f.set_construct(g)
f.flag_values = [1, 2, 4]
f.flag_meanings = ["a", "bb", "ccc"]
for cm in cf.CellMethod.create(
"grid_longitude: mean grid_latitude: max"):
f.set_construct(cm)
# Write the file, and read it in
cf.write(f, self.filename, verbose=0, string=True)
g = cf.read(self.filename, squeeze=True, verbose=0)[0]
self.assertTrue(g.equals(f, verbose=0),
"Field not equal to itself read back in")
x = g.dump(display=False)
x = f.dump(display=False)
def test_GATHERING_create(self):
# Define the gathered values
gathered_array = numpy.array(
[[280, 282.5, 281], [279, 278, 277.5]], dtype="float32"
)
# Define the list array values
list_array = [1, 4, 5]
# Initialise the list variable
list_variable = cf.List(data=cf.Data(list_array))
# Initialise the gathered array object
array = cf.GatheredArray(
compressed_array=cf.Data(gathered_array),
compressed_dimension=1,
shape=(2, 3, 2),
size=12,
ndim=3,
list_variable=list_variable,
)
# Create the field construct with the domain axes and the
# gathered array
tas = cf.Field(
properties={"standard_name": "air_temperature", "units": "K"}
)
# Create the domain axis constructs for the uncompressed array
T = tas.set_construct(cf.DomainAxis(2))
Y = tas.set_construct(cf.DomainAxis(3))
X = tas.set_construct(cf.DomainAxis(2))
uncompressed_array = numpy.ma.masked_array(
data=[
[[1, 280.0], [1, 1], [282.5, 281.0]],
[[1, 279.0], [1, 1], [278.0, 277.5]],
],
mask=[
[[True, False], [True, True], [False, False]],
[[True, False], [True, True], [False, False]],
],
fill_value=1e20,
dtype="float32",
)
for chunksize in (1000000,):
cf.chunksize(chunksize)
message = "chunksize=" + str(chunksize)
# Set the data for the field
tas.set_data(cf.Data(array), axes=[T, Y, X])
self.assertTrue(
(tas.data.array == uncompressed_array).all(), message
)
self.assertEqual(
tas.data.get_compression_type(), "gathered", message
)
self.assertTrue(
(
tas.data.compressed_array
== numpy.array(
[[280.0, 282.5, 281.0], [279.0, 278.0, 277.5]],
dtype="float32",
)
).all(),
message,
)
self.assertTrue(
(
tas.data.get_list().data.array == numpy.array([1, 4, 5])
).all(),
message,
)
def test_DSG_contiguous(self):
if self.test_only and inspect.stack()[0][3] not in self.test_only:
return
f = cf.read(self.contiguous, verbose=0)
self.assertEqual(len(f), 2)
# Select the specific humidity field
q = [g for g in f
if g.get_property('standard_name') == 'specific_humidity'][0]
self.assertTrue(q._equals(q.data.array.mask, self.a.mask))
self.assertTrue(q._equals(self.a, q.data.array),
'\nself.a=\n'+str(self.a)+'\nq.array=\n'+str(q.array))
cf.write(f, tmpfile, verbose=0)
g = cf.read(tmpfile)
self.assertEqual(len(g), len(f))
for i in range(len(f)):
self.assertTrue(g[i].equals(f[i], verbose=2))
# ------------------------------------------------------------
# Test creation
# ------------------------------------------------------------
# Define the ragged array values
ragged_array = numpy.array([280, 282.5, 281, 279, 278, 279.5],
dtype='float32')
# Define the count array values
count_array = [2, 4]
# Create the count variable
count_variable = cf.Count(data=cf.Data(count_array))
count_variable.set_property(
'long_name', 'number of obs for this timeseries')
# Create the contiguous ragged array object
array = cf.RaggedContiguousArray(
compressed_array=cf.Data(ragged_array),
shape=(2, 4), size=8, ndim=2,
count_variable=count_variable)
# Create the field construct with the domain axes and the ragged
# array
tas = cf.Field()
tas.set_properties({'standard_name': 'air_temperature',
'units': 'K',
'featureType': 'timeSeries'})
# Create the domain axis constructs for the uncompressed array
X = tas.set_construct(cf.DomainAxis(4))
Y = tas.set_construct(cf.DomainAxis(2))
# Set the data for the field
tas.set_data(cf.Data(array), axes=[Y, X])
cf.write(tas, tmpfile)
def test_DomainAxis__repr__str(self):
x = cf.DomainAxis(size=56)
x.nc_set_dimension("tas")
repr(x)
str(x)
def test_DomainAxis__repr__str(self):
x = cf.DomainAxis(size=56)
x.nc_set_dimension('tas')
_ = repr(x)
_ = str(x)
