def test_simulation_combined():
surface_1 = Tessem()
surface_2 = Telsem("/home/simon/Downloads")
surface = CombinedSurface(surface_1, surface_2)
atmosphere = Atmosphere1D(absorbers=[O2(), N2(), H2O()], surface=surface)
mwi = MWI()
mwi.sensor_line_of_sight = np.array([[135.0]])
mwi.sensor_position = np.array([[600e3]])
data_provider = DataProvider()
data_provider.surface_temperature = 280.0 * np.ones((1, 1))
data_provider.surface_latitude = 58.0
data_provider.surface_longitude = 12.0
data_provider.surface_type = 0.0
simulation = ArtsSimulation(atmosphere=atmosphere,
data_provider=data_provider,
sensors=[mwi])
simulation.setup()
simulation.run()
y = np.copy(mwi.y)
atmosphere_r = Atmosphere1D(absorbers=[O2(), N2(), H2O()],
surface=surface_1)
simulation_r = ArtsSimulation(atmosphere=atmosphere_r,
data_provider=data_provider,
sensors=[mwi])
simulation_r.setup()
simulation_r.run()
y_r = np.copy(mwi.y)
assert (np.allclose(y, y_r))
data_provider.surface_type = 1.0
simulation.setup()
simulation.run()
y = np.copy(mwi.y)
atmosphere_r = Atmosphere1D(absorbers=[O2(), N2(), H2O()],
surface=surface_2)
simulation_r = ArtsSimulation(atmosphere=atmosphere_r,
data_provider=data_provider,
sensors=[mwi])
simulation_r.setup()
simulation_r.run()
y_r = np.copy(mwi.y)
assert (np.allclose(y, y_r))
def __init__(self, data_provider, ice_shape="8-ColumnAggregate"):
sensor = CloudSat()
DataProviderBase.__init__(self)
self.add(IceAPriori())
self.add(RainAPriori())
self.add(ObservationErrors())
self.add(data_provider)
Simulation.__init__(self, sensor, self, ice_shape=ice_shape)
self.atmosphere.absorbers += [O2(model="PWR98")]
scatterers = self.atmosphere.scatterers
self.atmosphere._surface = Tessem()
# Add first moment ice to retrieval and set transform
ice = [s for s in scatterers if s.name == "ice"][0]
self.retrieval.add(ice.moments[0])
ice.moments[0].transformation = Log10()
self._ice_water_content = ice.moments[0]
# Add first moment of rain PSD to retrieval and set transform
rain = [s for s in scatterers if s.name == "rain"][0]
self.retrieval.add(rain.moments[0])
rain.moments[0].transformation = Log10()
self._rain_water_content = rain.moments[0]
self.retrieval.settings["stop_dx"] = 1e-6
self.cache_index = None
self.iwc = None
self.rwc = None
def test_simulation_scattering_combined(scattering_solver):
ice = ScatteringSpecies("ice", D14(-1.0, 2.0),
scattering_data = scattering_data,
scattering_meta_data = scattering_meta)
ice.psd.t_min = 0.0
ice.psd.t_max = 275.0
ici = ICI(channel_indices = [0, -1], stokes_dimension = 1)
ici.sensor_line_of_sight = np.array([[135.0]])
ici.sensor_position = np.array([[600e3]])
cs = CloudSat(stokes_dimension = 1)
cs.range_bins = np.linspace(0, 30e3, 31)
cs.sensor_line_of_sight = np.array([[135.0]])
cs.sensor_position = np.array([[600e3]])
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
scatterers = [ice],
surface = Tessem())
simulation = ArtsSimulation(atmosphere = atmosphere,
data_provider = DataProvider(),
sensors = [ici, cs])
simulation.scattering_solver = scattering_solver()
simulation.setup()
simulation.run()
y = np.copy(simulation.workspace.y)
return y
def __init__(self,
hydrometeors,
sensors,
data_provider,
include_cloud_water=False):
"""
Arguments:
hydrometeors(list): List of the hydrometeors to use in the simulation.
sensors(list): List of sensors for which to simulate observations.
data_provider: Data provider object providing the simulation data.
include_cloud_water(bool): Whether or not to include cloud water
"""
self.include_cloud_water = include_cloud_water
self.hydrometeors = hydrometeors
absorbers = [
O2(model="TRE05", from_catalog=False),
N2(model="SelfContStandardType", from_catalog=False),
H2O(model=["SelfContCKDMT320", "ForeignContCKDMT320"],
lineshape="VP",
normalization="VVH",
cutoff=750e9)
]
absorbers = [O2(), N2(), H2O()]
if self.include_cloud_water:
absorbers.insert(2, CloudWater(model="ELL07", from_catalog=False))
scatterers = hydrometeors
surface = Tessem()
atmosphere = Atmosphere1D(absorbers, scatterers, surface)
self.simulation = ArtsSimulation(atmosphere,
sensors=sensors,
scattering_solver=Disort(nstreams=16))
self.sensors = sensors
self.data_provider = data_provider
self.simulation.data_provider = self.data_provider
def setup_retrieval_simulation(retrieval_type = "passive",
scattering = False):
"""
Setup up a retrieval simulation with or without
scattering.
"""
#
# Scattering
#
ice = ScatteringSpecies("ice", D14(-1.0, 2.0),
scattering_data = scattering_data,
scattering_meta_data = scattering_meta)
if scattering:
scatterers = [ice]
else:
scatterers = []
ice.psd.t_min = 0.0
ice.psd.t_max = 275.0
#
# Sensors
#
ici = ICI(stokes_dimension = 1)
ici.sensor_line_of_sight = np.array([[135.0]])
ici.sensor_position = np.array([[600e3]])
cs = CloudSat()
cs.range_bins = np.linspace(0, 30e3, 31)
cs.sensor_line_of_sight = np.array([[135.0]])
cs.sensor_position = np.array([[600e3]])
cs.y_min = -35.0
if retrieval_type == "active":
sensors = [cs]
elif retrieval_type == "passive":
sensors = [ici]
else:
sensors = [cs, ici]
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
scatterers = scatterers,
surface = Tessem())
simulation = ArtsSimulation(atmosphere = atmosphere,
sensors = sensors)
simulation.scattering_solver = Disort()
return simulation
def __init__(self, dimensions=1, surface="ocean"):
if not dimensions in [1]:
raise Exception("Currently only 1D simulations are supported.")
if not surface == "ocean":
raise Exception(
"Currently only simulations over ocean surfaces are supported."
)
super().__init__(dimensions=(0, ) * dimensions,
absorbers=[O2(), N2(), H2O()],
scatterers=[],
surface=Tessem())
def test_simulation_telsem():
atmosphere = Atmosphere1D(absorbers=[O2(), N2(), H2O()],
surface=Telsem("/home/simon/Downloads"))
mwi = MWI()
mwi.sensor_line_of_sight = np.array([[135.0]])
mwi.sensor_position = np.array([[600e3]])
data_provider = DataProvider()
data_provider.surface_temperature = 280.0 * np.ones((1, 1))
data_provider.latitude = 58.0
data_provider.longitude = 12.0
simulation = ArtsSimulation(atmosphere=atmosphere,
data_provider=data_provider,
sensors=[mwi])
simulation.setup()
simulation.run()
def test_simulation_tessem():
atmosphere = Atmosphere1D(absorbers=[O2(), N2(), H2O()], surface=Tessem())
mwi = MWI()
mwi.sensor_line_of_sight = np.array([[135.0]])
mwi.sensor_position = np.array([[600e3]])
simulation = ArtsSimulation(atmosphere=atmosphere,
data_provider=DataProvider(),
sensors=[mwi])
simulation.setup()
simulation.run()
y1 = np.copy(mwi.y)
simulation.run()
y2 = np.copy(mwi.y)
assert (np.all(np.isclose(y1, y2)))
def test_simulation_absorption_jacobian():
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
surface = Tessem())
o2, n2, h2o = atmosphere.absorbers
ici = ICI(channel_indices = [0, -1])
ici.sensor_line_of_sight = np.array([[135.0]])
ici.sensor_position = np.array([[600e3]])
simulation = ArtsSimulation(atmosphere = atmosphere,
data_provider = DataProvider(),
sensors = [ici])
simulation.jacobian.add(o2)
simulation.jacobian.add(n2)
simulation.jacobian.add(h2o)
simulation.setup()
simulation.run()
return np.copy(simulation.workspace.jacobian.value)
def test_simulation_multiview():
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
surface = Tessem())
lines_of_sight = np.array([[135.0],
[180.0]])
positions = np.array([[600e3],
[600e3]])
ici = ICI(lines_of_sight=lines_of_sight,
positions=positions)
simulation = ArtsSimulation(atmosphere = atmosphere,
data_provider = DataProvider(),
sensors = [ici])
simulation.setup()
simulation.run()
y = np.copy(ici.y)
assert(y.shape[0] == 2)
def test_simulation_scattering(scattering_solver):
ice = ScatteringSpecies("ice", D14(-1.0, 2.0),
scattering_data = scattering_data,
scattering_meta_data = scattering_meta)
ice.psd.t_min = 0.0
ice.psd.t_max = 275.0
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
scatterers = [ice],
surface = Tessem())
ici = ICI(stokes_dimension = 1, channel_indices = [1, -1])
ici.sensor_line_of_sight = np.array([[135.0]])
ici.sensor_position = np.array([[600e3]])
simulation = ArtsSimulation(atmosphere = atmosphere,
data_provider = DataProvider(),
sensors = [ici])
simulation.scattering_solver = scattering_solver()
simulation.setup()
simulation.run()
def test_simulation_scattering_jacobian():
ice = ScatteringSpecies("ice", D14(-1.0, 2.0),
scattering_data = scattering_data,
scattering_meta_data = scattering_meta)
ice.psd.t_min = 0.0
ice.psd.t_max = 275.0
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
scatterers = [ice],
surface = Tessem())
ici = ICI(channel_indices = [1, -1])
ici.sensor_line_of_sight = np.array([[135.0]])
ici.sensor_position = np.array([[600e3]])
simulation = ArtsSimulation(atmosphere = atmosphere,
data_provider = DataProvider(),
sensors = [ici])
simulation.jacobian.add(ice.mass_density)
simulation.setup()
simulation.run()
print(simulation.workspace.particle_bulkprop_field.value)
return np.copy(simulation.workspace.jacobian.value)
data_provider = DataProvider(),
sensors = [cs])
simulation.setup()
simulation.run()
y = np.copy(cs.y)
assert(y.shape[0] == 2)
assert(y.shape[-1] == 2)
ice = ScatteringSpecies("ice", D14(-1.0, 2.0),
scattering_data = scattering_data,
scattering_meta_data = scattering_meta)
ice.psd.t_min = 0.0
ice.psd.t_max = 275.0
atmosphere = Atmosphere1D(absorbers = [O2(), N2(), H2O()],
scatterers = [],
surface = Tessem())
ici = ICI(stokes_dimension = 1, channel_indices = [1, -1])
ici.sensor_line_of_sight = np.array([[135.0]])
ici.sensor_position = np.array([[600e3]])
simulation = ArtsSimulation(atmosphere = atmosphere,
data_provider = DataProvider(),
sensors = [ici])
simulation.scattering_solver = RT4()
simulation.setup()
for i in range(100):
simulation.run()
def __init__(self, hydrometeors, sensors, data_provider):
cw_a = [p for p in data_provider.subproviders \
if getattr(p, "name", "") == "cloud_water"]
self.include_cloud_water = len(cw_a) > 0
self.hydrometeors = hydrometeors
absorbers = [
O2(model="TRE05", from_catalog=False),
N2(model="SelfContStandardType", from_catalog=False),
H2O(model=["SelfContCKDMT320", "ForeignContCKDMT320"],
from_catalog=True,
lineshape="VP",
normalization="VVH",
cutoff=750e9)
]
absorbers = [O2(), N2(), H2O()]
if self.include_cloud_water:
absorbers.insert(2, CloudWater(model="ELL07", from_catalog=False))
scatterers = hydrometeors
surface = Tessem()
atmosphere = Atmosphere1D(absorbers, scatterers, surface)
self.simulation = ArtsSimulation(atmosphere,
sensors=sensors,
scattering_solver=Disort(nstreams=16))
self.sensors = sensors
self.data_provider = data_provider
self.simulation.data_provider = self.data_provider
self._setup_retrieval()
self.radar_only = all(
[isinstance(s, ActiveSensor) for s in self.sensors])
def radar_only(rr):
rr.settings["max_iter"] = 30
rr.settings["stop_dx"] = 1e-4
rr.settings["method"] = "lm"
rr.settings["lm_ga_settings"] = np.array(
[1000.0, 3.0, 2.0, 10e3, 1.0, 1.0])
rr.sensors = [s for s in rr.sensors if isinstance(s, ActiveSensor)]
rr.retrieval_quantities = [h.moments[0] for h in self.hydrometeors]
rr.retrieval_quantities += [
h.moments[1] for h in self.hydrometeors
]
#rr.retrieval_quantities = [h.moments[1] for h in self.hydrometeors]
def all_quantities(rr):
rr.settings["max_iter"] = 30
rr.settings["stop_dx"] = 1e-2
rr.settings["method"] = "lm"
rr.settings["lm_ga_settings"] = np.array(
[20.0, 5.0, 2.0, 1e5, 0.1, 1.0])
if all([isinstance(s, PassiveSensor) for s in rr.sensors]):
rr.settings["lm_ga_settings"] = np.array(
[20.0, 3.0, 2.0, 1e5, 0.1, 1.0])
#else:
# rr.settings["lm_ga_settings"] = np.array(
# [10.0, 3.0, 2.0, 1e5, 1.0, 1.0])
rr.retrieval_quantities = [h.moments[0] for h in self.hydrometeors]
rr.retrieval_quantities += [
h.moments[1] for h in self.hydrometeors
]
if not self.h2o is None:
rr.retrieval_quantities += [self.h2o]
if not self.cw is None:
rr.retrieval_quantities += [self.cw]
if not self.temperature is None:
rr.retrieval_quantities += [self.temperature]
if all([isinstance(s, ActiveSensor) for s in self.sensors]):
self.simulation.retrieval.callbacks = [("Radar only", radar_only)]
elif any([isinstance(s, ActiveSensor) for s in self.sensors]):
self.simulation.retrieval.callbacks = [
#("Radar only", radar_only),
("All quantities", all_quantities)
]
else:
self.simulation.retrieval.callbacks = [("All quantities",
all_quantities)]