class _ARTS:
def __init__(self,
ws=None,
threads=None,
nstreams=4,
scale_vmr=True,
verbosity=0):
"""Initialize a wrapper for an ARTS workspace.
Parameters:
ws (pyarts.workspace.Workspace): An ARTS workspace.
threads (int): Number of threads to use.
Default is all available threads.
nstreams (int): Number of viewing angles to base the radiative
flux calculation on.
scale_vmr (bool): Control whether dry volume mixing ratios are
scaled with the water-vapor concentration (default is `False.`)
verbosity (int): Control the ARTS verbosity from 0 (quiet) to 2.
"""
from pyarts.workspace import Workspace, arts_agenda
self.nstreams = nstreams
self.scale_vmr = scale_vmr
if ws is None:
self.ws = Workspace(verbosity=verbosity)
self.ws.execute_controlfile("general/general.arts")
self.ws.execute_controlfile("general/continua.arts")
self.ws.execute_controlfile("general/agendas.arts")
self.ws.execute_controlfile("general/planet_earth.arts")
# Agenda settings
self.ws.Copy(self.ws.abs_xsec_agenda, self.ws.abs_xsec_agenda__noCIA)
self.ws.Copy(self.ws.iy_main_agenda, self.ws.iy_main_agenda__Emission)
self.ws.Copy(self.ws.iy_space_agenda,
self.ws.iy_space_agenda__CosmicBackground)
self.ws.Copy(self.ws.iy_surface_agenda,
self.ws.iy_surface_agenda__UseSurfaceRtprop)
self.ws.Copy(
self.ws.propmat_clearsky_agenda,
self.ws.propmat_clearsky_agenda__LookUpTable,
)
self.ws.Copy(self.ws.ppath_agenda,
self.ws.ppath_agenda__FollowSensorLosPath)
self.ws.Copy(self.ws.ppath_step_agenda,
self.ws.ppath_step_agenda__GeometricPath)
@arts_agenda
def p_eq_agenda(workspace):
workspace.water_p_eq_fieldMK05()
self.ws.Copy(self.ws.water_p_eq_agenda, p_eq_agenda)
@arts_agenda
def cloudbox_agenda(workspace):
workspace.iyInterpCloudboxField()
self.ws.Copy(self.ws.iy_cloudbox_agenda, cloudbox_agenda)
# Number of Stokes components to be computed
self.ws.IndexSet(self.ws.stokes_dim, 1)
self.ws.jacobianOff() # No jacobian calculation
self.ws.cloudboxOff() # Clearsky = No scattering
# Set Absorption Species
self.ws.abs_speciesSet(species=[
"O2, O2-CIAfunCKDMT100",
"H2O, H2O-SelfContCKDMT252, H2O-ForeignContCKDMT252",
"O3",
"CO2, CO2-CKDMT252",
"N2, N2-CIAfunCKDMT252, N2-CIArotCKDMT252",
"N2O",
"CH4",
"CO",
])
# Surface handling
self.ws.VectorSetConstant(self.ws.surface_scalar_reflectivity, 1, 0.0)
self.ws.Copy(
self.ws.surface_rtprop_agenda,
self.ws.
surface_rtprop_agenda__Specular_NoPol_ReflFix_SurfTFromt_surface,
)
# Read lookup table
abs_lookup = os.getenv("KONRAD_LOOKUP_TABLE",
join(dirname(__file__), "data/abs_lookup.xml"))
if not isfile(abs_lookup):
raise FileNotFoundError(
"Could not find ARTS absorption lookup table.\n"
"To perform ARTS calculations you have to download the lookup "
"table at:\n\n https://doi.org/10.5281/zenodo.3885410\n\n"
"Afterwards, use the following environment variable to tell "
"konrad where to find it:\n\n"
" $ export KONRAD_LOOKUP_TABLE='/path/to/abs_lookup.xml'")
self.ws.ReadXML(self.ws.abs_lookup, abs_lookup)
self.ws.f_gridFromGasAbsLookup()
self.ws.abs_lookupAdapt()
# Sensor settings
self.ws.sensorOff() # No sensor properties
# Atmosphere
self.ws.AtmosphereSet1D()
# Set number of OMP threads
if threads is not None:
self.ws.SetNumberOfThreads(threads)
def calc_lookup_table(self, filename=None, fnum=2**15, wavenumber=None):
"""Calculate an absorption lookup table.
The lookup table is constructed to cover surface temperatures
between 200 and 400 K, and water vapor mixing ratio up to 40%.
The frequency grid covers the whole outgoing longwave spectrum
from 10 to 3,250 cm^-1.
References:
An absorption lookup table can be found at
https://doi.org/10.5281/zenodo.3885410
Parameters:
filename (str): (Optional) path to an ARTS XML file
to store the lookup table.
fnum (int): Number of frequencies in frequency grid.
Ignored if `wavenumber` is set.
wavenumber (ndarray): Wavenumber grid [m-1].
"""
# Create a frequency grid
if wavenumber is None:
wavenumber = np.linspace(10e2, 3_250e2, fnum)
self.ws.f_grid = ty.physics.wavenumber2frequency(wavenumber)
# Read line catagloge and create absorption lines.
self.ws.ReadSplitARTSCAT(
abs_lines=self.ws.abs_lines,
abs_species=self.ws.abs_species,
basename="hitran_split_artscat5/",
fmin=0.0,
fmax=1e99,
globalquantumnumbers="",
localquantumnumbers="",
ignore_missing=0,
)
# Set line shape and cut off.
self.ws.abs_linesSetLineShapeType(self.ws.abs_lines, "VP")
self.ws.abs_linesSetNormalization(self.ws.abs_lines, "VVH")
self.ws.abs_linesSetCutoff(self.ws.abs_lines, "ByLine", 750e9)
self.ws.abs_lines_per_speciesCreateFromLines()
self.ws.abs_lines_per_speciesCompact()
# Create a standard atmosphere
p_grid = get_quadratic_pgrid(1_200e2, 0.5, 80)
atmosphere = Atmosphere(p_grid)
atmosphere["T"][
-1, :] = 300.0 + 5.0 * np.log(atmosphere["plev"] / 1000e2)
atmosphere.tracegases_rcemip()
atmosphere["O2"][:] = 0.2095
atmosphere["CO2"][:] = 1.5 * 348e-6
h2o = 0.01 * (p_grid / 1000e2)**0.2
atmosphere["H2O"][:] = h2o[:-1]
# Convert the konrad atmosphere into an ARTS atm_fields_compact.
atm_fields_compact = atmosphere.to_atm_fields_compact()
self.ws.atm_fields_compact = atm_fields_compact
self.ws.atm_fields_compactAddConstant(
atm_fields_compact=self.ws.atm_fields_compact,
name="abs_species-N2",
value=0.7808,
condensibles=["abs_species-H2O"],
)
# Setup the lookup table calculation
self.ws.AtmFieldsAndParticleBulkPropFieldFromCompact()
self.ws.vmr_field.value = self.ws.vmr_field.value.clip(min=0.0)
self.ws.atmfields_checkedCalc()
self.ws.abs_lookupSetup(p_step=1.0) # Do not refine p_grid
self.ws.abs_t_pert = np.arange(-160, 61, 20)
nls_idx = [
i for i, tag in enumerate(self.ws.abs_species.value)
if "H2O" in tag[0]
]
self.ws.abs_speciesSet(
abs_species=self.ws.abs_nls,
species=[", ".join(self.ws.abs_species.value[nls_idx[0]])],
)
self.ws.abs_nls_pert = np.array(
[10**x for x in [-9, -7, -5, -3, -1, 0, 0.5, 1, 1.5, 2]])
# Run checks
self.ws.abs_xsec_agenda_checkedCalc()
self.ws.lbl_checkedCalc()
# Calculate actual lookup table.
self.ws.abs_lookupCalc()
if filename is not None:
self.ws.WriteXML("binary", self.ws.abs_lookup, filename)
def set_atmospheric_state(self, atmosphere, t_surface):
"""Set and check the atmospheric fields."""
import pyarts
atm_fields_compact = atmosphere.to_atm_fields_compact()
# Scale dry-air VMRs with H2O and CO2 content.
if self.scale_vmr:
variable_vmrs = (atm_fields_compact.get("abs_species-H2O")[0] +
atm_fields_compact.get("abs_species-CO2")[0])
else:
t3_shape = atm_fields_compact.get("abs_species-H2O")[0].shape
variable_vmrs = np.zeros(t3_shape)
for species in atm_fields_compact.grids[0]:
if (species.startswith("abs_species-") and "H2O" not in species
and "CO2" not in species):
atm_fields_compact.scale(species, 1 - variable_vmrs)
# Compute the N2 VMR as a residual of the full atmosphere composition.
n2 = pyarts.types.GriddedField3(
grids=atm_fields_compact.grids[1:],
data=0.7808 * (1 - variable_vmrs),
)
self.ws.atm_fields_compact = atm_fields_compact
self.ws.atm_fields_compactAddSpecies(
atm_fields_compact=self.ws.atm_fields_compact,
name="abs_species-N2",
value=n2,
)
self.ws.AtmFieldsAndParticleBulkPropFieldFromCompact()
self.ws.vmr_field = self.ws.vmr_field.value.clip(min=0)
# Surface & TOA
# Add pressure layers to the surface and top-of-the-atmosphere to
# ensure consistent atmosphere boundaries between ARTS and RRTMG.
self.ws.t_surface = np.array([[t_surface]])
self.ws.z_surface = np.array([[0.0]])
self.ws.z_field.value[0, 0, 0] = 0.0
# Perform configuration and atmosphere checks
self.ws.atmfields_checkedCalc()
self.ws.propmat_clearsky_agenda_checkedCalc()
self.ws.atmgeom_checkedCalc()
self.ws.cloudbox_checkedCalc()
def calc_spectral_irradiance_field(self, atmosphere, t_surface):
"""Calculate the spectral irradiance field."""
self.set_atmospheric_state(atmosphere, t_surface)
# get the zenith angle grid and the integrations weights
self.ws.AngularGridsSetFluxCalc(N_za_grid=self.nstreams,
N_aa_grid=1,
za_grid_type="double_gauss")
# calculate intensity field
self.ws.Tensor3Create("trans_field")
self.ws.spectral_radiance_fieldClearskyPlaneParallel(
trans_field=self.ws.trans_field,
use_parallel_za=0,
)
self.ws.spectral_irradiance_fieldFromSpectralRadianceField()
return (
self.ws.f_grid.value.copy(),
self.ws.p_grid.value.copy(),
self.ws.spectral_irradiance_field.value.copy(),
self.ws.trans_field.value[:, 1:, 0].copy().prod(axis=1),
)
def calc_optical_thickness(self, atmosphere, t_surface):
"""Calculate the spectral irradiance field."""
self.set_atmospheric_state(atmosphere, t_surface)
self.ws.propmat_clearsky_fieldCalc()
tau = np.trapz(
y=self.ws.propmat_clearsky_field.value[:, :, 0, 0, :, 0, 0],
x=self.ws.z_field.value[:, 0, 0],
axis=-1,
)
return self.ws.f_grid.value.copy(), tau
@staticmethod
def integrate_spectral_irradiance(frequency, irradiance):
"""Integrate the spectral irradiance field over the frequency.
Parameters:
frequency (ndarray): Frequency [Hz].
irradiance (ndarray): Spectral irradiance [W m^-2 / Hz].
Returns:
ndarray, ndarray: Downward flux, upward, flux [W m^-2]
"""
F = np.trapz(irradiance, frequency, axis=0)[:, 0, 0, :]
# Fluxes
lw_down = -F[:, 0]
lw_up = F[:, 1]
return lw_down, lw_up
def calc_spectral_olr(self, atmosphere, surface):
"""Calculate the outgoing longwave radiation as function of wavenumber.
Parameters:
atmosphere (konrad.atmosphere.Atmosphere): Atmosphere model.
surface (konrad.surface.Surface): Surface model.
Returns:
ndarray: Outgoing longwave radiation [W m^-2 / cm^-1]
"""
f, _, irradiance_field, _ = self.calc_spectral_irradiance_field(
atmosphere=atmosphere, t_surface=surface["temperature"][0])
return f, irradiance_field[:, -1, 0, 0, 1]
class TestVariables:
"""
Tests the manipulation of workspace variables.
"""
def setup_method(self):
"""
This ensures a new Workspace for every test.
"""
self.dir = os.path.dirname(os.path.realpath(__file__))
self.ws = Workspace(verbosity=0)
self.setup_workspace()
def setup_workspace(self):
ws = self.ws
ws.atmosphere_dim = 1
ws.p_grid = np.linspace(1e5, 1e3, 21)
ws.Touch(ws.lat_grid)
ws.Touch(ws.lon_grid)
ws.f_grid = 183.0e9 * np.ones(1)
ws.stokes_dim = 1
ws.sensor_los = 180.0 * np.ones((1, 1))
ws.sensor_pos = 830e3 * np.ones((1, 1))
ws.sensorOff()
def test_index_transfer(self):
"""
Create and set Index WSV.
"""
self.ws.IndexCreate("index_variable")
i = np.random.randint(0, 100)
self.ws.index_variable = i
assert self.ws.index_variable.value == i
def test_string_transfer(self):
"""
Create and set String WSV.
"""
self.ws.StringCreate("string_variable")
s = "some random string."
self.ws.string_variable = s
assert self.ws.string_variable.value == s
def test_array_of_index_transfer(self):
"""
Create and set ArrayOfIndex WSV.
"""
self.ws.ArrayOfIndexCreate("array_of_index_variable")
i = [np.random.randint(0, 100) for j in range(10)]
self.ws.array_of_index_variable = i
assert self.ws.array_of_index_variable.value == i
self.ws.array_of_index_variable = []
assert self.ws.array_of_index_variable.value == []
def test_array_of_vector_transfer(self):
"""
Create and set ArrayOfVector WSV.
"""
self.ws.ArrayOfVectorCreate("array_of_vector_variable")
aov = pyarts.xml.load(
os.path.join(self.dir, "../xml/reference/arrayofvector.xml"))
self.ws.array_of_vector_variable = aov
assert self.ws.array_of_vector_variable.value == aov
def test_vector_transfer(self):
"""
Create and set Vector WSV.
"""
self.ws.VectorCreate("vector_variable")
v = np.random.rand(10)
self.ws.vector_variable = v
assert all(self.ws.vector_variable.value == v)
def test_matrix_transfer(self):
"""
Create and set Matrix WSV.
"""
self.ws.MatrixCreate("matrix_variable")
m = np.random.rand(10, 10)
self.ws.matrix_variable = m
assert all(self.ws.matrix_variable.value.ravel() == m.ravel())
def test_sparse_transfer(self):
"""
Create and set Sparse WSV.
"""
n = 100
d2 = np.ones(n - 2)
d1 = np.ones(n - 1)
d = np.ones(n)
m = sp.sparse.diags(diagonals=[d2, d1, d, d1, d2],
offsets=[2, 1, 0, -1, -2])
self.ws.sensor_response = m
assert np.all(m.toarray() == self.ws.sensor_response.value.toarray())
def test_tensor_3(self):
"""
Create and set Tensor3 variable.
"""
t_0 = np.random.rand(*([3] * 3))
self.ws.Tensor3Create("tensor_3")
self.ws.tensor_3 = t_0
assert np.all(t_0 == self.ws.tensor_3.value)
def test_tensor_4(self):
"""
Create and set Tensor4 variable.
"""
t_0 = np.random.rand(*([3] * 4))
t_1 = self.ws.Tensor4Create("tensor_4")
self.ws.tensor_4 = t_0
assert np.all(t_0 == self.ws.tensor_4.value)
def test_tensor_5(self):
"""
Create and set Tensor5 variable.
"""
t_0 = np.random.rand(*([3] * 5))
t_1 = self.ws.Tensor5Create("tensor_5")
self.ws.tensor_5 = t_0
assert np.all(t_0 == self.ws.tensor_5.value)
def test_tensor_6(self):
"""
Create and set Tensor6 variable.
"""
t_0 = np.random.rand(*([3] * 6))
t_1 = self.ws.Tensor6Create("tensor_6")
self.ws.tensor_6 = t_0
assert np.all(t_0 == self.ws.tensor_6.value)
def test_tensor_7(self):
"""
Create and set Tensor7 variable.
"""
t_0 = np.random.rand(*([3] * 7))
self.ws.Tensor7Create("tensor_7")
self.ws.tensor_7 = t_0
assert np.all(t_0 == self.ws.tensor_7.value)
def test_time(self):
"""
Create and set Time variable.
"""
times = ["2020-01-02 03:04:05", "2021-02-03 04:05:06"]
self.ws.ArrayOfTimeCreate("time_1")
self.ws.ArrayOfTimeNLinSpace(self.ws.time_1, 2, times[0], times[1])
assert (times[0] == str(self.ws.time_1.value[0])[0:19]
and times[1] == str(self.ws.time_1.value[1])[0:19])
def test_creation(self):
"""
Test creation of WSVs.
"""
self.ws.ArrayOfIndexCreate("array_of_index")
self.ws.ArrayOfIndexCreate("array_of_index")
with pytest.raises(Exception):
self.ws.VectorCreate("array_of_index")
def test_covariance_matrix(self):
"""
Test manipulation of CorvarianceMatrix objects.
"""
ws = self.ws
ws.jacobianInit()
ws.jacobianAddAbsSpecies(species="O3",
g1=ws.p_grid,
g2=ws.lat_grid,
g3=ws.lon_grid)
ws.jacobianAddAbsSpecies(species="H2O",
g1=ws.p_grid,
g2=ws.lat_grid,
g3=ws.lon_grid)
ws.jacobianClose()
ws.covmatDiagonal(out=ws.covmat_block,
out_inverse=ws.covmat_block,
vars=10.0 * np.ones(ws.p_grid.value.size))
ws.covmat_sxAddBlock(block=ws.covmat_block)
ws.covmatDiagonal(out=ws.covmat_block,
out_inverse=ws.covmat_block,
vars=20.0 * np.ones(ws.p_grid.value.size))
ws.covmat_sxAddBlock(block=ws.covmat_block)
def test_variable_creation(self):
"""
Test creation of named and unnambed WSVs.
"""
# Unnamed variable
wsv = self.ws.create_variable("Matrix", None)
self.ws.__setattr__(wsv.name, np.eye(5))
assert np.all(
np.isclose(np.eye(5),
self.ws.__getattr__(wsv.name).value))
# Named variable
wsv = self.ws.create_variable("Matrix", "matrix_wsv")
self.ws.matrix_wsv = np.eye(5)
assert np.all(np.isclose(np.eye(5), self.ws.matrix_wsv.value))
def test_variable_set_empty(self):
"""
Test initialization of workspace variables.
"""
self.ws.f_grid = np.array([94e9])
self.ws.f_grid = []
assert self.ws.f_grid.value.size == 0
def test_variable_create(self):
"""
Test initialization of workspace variables.
"""
self.ws = Workspace()
self.ws.IndexCreate("myindex")
with pytest.raises(Exception):
print(self.ws.myindex.value)
def test_convert(self):
"""
Test automatic conversion of Python types.
"""
v = WorkspaceVariable.convert("Index", 1.2)
assert (v == 1)
v = WorkspaceVariable.convert("String", "string")
assert (v == "string")
v = WorkspaceVariable.convert("Numeric", 1)
assert (type(v) == np.float64)
v = WorkspaceVariable.convert("Vector", 1.0)
assert (v.shape == (1, ))
v = WorkspaceVariable.convert("Matrix", 1.0)
assert (v.shape == (1, 1))
v = WorkspaceVariable.convert("Tensor3", 1.0)
assert (v.shape == (1, 1, 1))
v = WorkspaceVariable.convert("Tensor6", 1.0)
assert (v.shape == (1, 1, 1, 1, 1, 1))
v = WorkspaceVariable.convert("ArrayOfArrayOfIndex", 1.0)
assert (type(v) == list)
assert (type(v[0]) == list)
assert (type(v[0][0]) == int)
v = WorkspaceVariable.convert("ArrayOfArrayOfIndex", 1)
return v
