def __init__(self, name="gmi", band_indices=None, stokes_dimension=1):
if not band_indices is None:
channel_indices = []
i = 0
for bi in band_indices:
for o in GMI.sidebands[bi]:
channel_indices += [i]
i += 1
center_frequencies = [
GMI.center_frequencies[i] for i in band_indices
]
offsets = [GMI.sidebands[i] for i in band_indices]
self.nedt = GMI.nedt[channel_indices]
else:
center_frequencies = GMI.center_frequencies
offsets = GMI.sidebands
self.nedt = GMI.nedt
channels, sensor_response = sensor_properties(center_frequencies,
offsets,
order="negative")
super().__init__(name, channels, stokes_dimension=stokes_dimension)
self.sensor_line_of_sight = np.array([[132.0]])
self.sensor_position = np.array([[600e3]])
m = sensor_response.shape[0]
self.sensor_response_f = self.f_grid[:m]
self.sensor_response_pol = self.f_grid[:m]
self.sensor_response_dlos = self.f_grid[:m, np.newaxis]
self.sensor_response = sensor_response
self.sensor_f_grid = self.f_grid[:m]
def __init__(self, name="ici", band_indices=None, stokes_dimension=1):
"""
This creates an instance of the ICI sensor to be used within a
:code:`parts` simulation.
Arguments:
name(:code:`str`): The name of the sensor used within the parts
simulation.
band_indicees(:code:`list`): Indices of the frequency bands to be used.
stokes_dimension(:code:`int`): The stokes dimension to use for
the retrievals.
"""
if not band_indices is None:
channel_indices = []
i = 0
for bi in band_indices:
for o in ICI.sidebands[bi]:
channel_indices += [i]
i += 1
center_frequencies = [
ICI.center_frequencies[i] for i in band_indices
]
offsets = [ICI.sidebands[i] for i in band_indices]
self.nedt = ICI.nedt[channel_indices]
else:
center_frequencies = ICI.center_frequencies
offsets = ICI.sidebands
self.nedt = ICI.nedt
channels, sensor_response = sensor_properties(center_frequencies,
offsets,
order="negative")
super().__init__(name, channels, stokes_dimension=stokes_dimension)
self.sensor_line_of_sight = np.array([[132.0]])
self.sensor_position = np.array([[600e3]])
m = sensor_response.shape[0]
self.sensor_response_f = self.f_grid[:m]
self.sensor_response_pol = self.f_grid[:m]
self.sensor_response_dlos = self.f_grid[:m, np.newaxis]
self.sensor_response = sensor_response
self.sensor_f_grid = self.f_grid[:m]
def __init__(self, stokes_dimension=1):
channels, sensor_response = sensor_properties(Ismar.center_frequencies,
Ismar.offsets,
order="positive")
super().__init__(name="ismar",
f_grid=channels,
stokes_dimension=stokes_dimension)
self.sensor_line_of_sight = np.array([180.0])
self.sensor_position = np.array([9300.0])
self.iy_unit = "RJBT"
m = sensor_response.shape[0]
self.sensor_response_f = self.f_grid[:m]
self.sensor_response_pol = self.f_grid[:m]
self.sensor_response_dlos = self.f_grid[:m, np.newaxis]
self.sensor_response = sensor_response
self.sensor_f_grid = self.f_grid[:m]
def __init__(self, stokes_dimension=1):
channels, sensor_response = sensor_properties(
HampPassive.center_frequencies,
HampPassive.sidebands,
order="positive")
super().__init__(name="hamp_passive",
f_grid=channels,
stokes_dimension=stokes_dimension)
self.sensor_line_of_sight = np.array([180.0])
self.sensor_position = np.array([12500.0])
m = sensor_response.shape[0]
self.sensor_response_f = self.f_grid[:m]
self.sensor_response_pol = self.f_grid[:m]
self.sensor_response_dlos = self.f_grid[:m, np.newaxis]
self.sensor_response = sensor_response
self.sensor_f_grid = self.f_grid[:m]