mb = ModelBehavior() accur = mb.accuracy deltamplus = mb.delta_m_plus dopseudosphere = mb.do_pseudo_sphere header = mb.header ibcnd = mb.incidence_beam_conditions onlyfl = mb.only_fluxes prnt = mb.print_variables radius = mb.radius usrang = mb.user_angles usrtau = mb.user_optical_depths # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Make the output arrays # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ oa = OutputArrays(cp) albmed = oa.albedo_medium flup = oa.diffuse_up_flux rfldn = oa.diffuse_down_flux rfldir = oa.direct_beam_flux dfdt = oa.flux_divergence uu = oa.intensity uavg = oa.mean_intensity trnmed = oa.transmissivity_medium # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Make the arrays I'm unsure about (for now) # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ uns = Unsure(cp) h_lyr = uns.h_lyr
def test_int_input_raises_type_error(self) -> None:
with self.assertRaises(TypeError):
OutputArrays(1)
def fit_ssa(guess, wav_index: int):
# Trap the guess
if not 0 <= guess <= 1:
return 9999999
# Take care of surface variables
albedo = hapke[wav_index].albedo
lamber = hapke[wav_index].lambertian
rhou = hapke[wav_index].rhou
rhoq = hapke[wav_index].rhoq
bemst = hapke[wav_index].bemst
emust = hapke[wav_index].emust
rho_accurate = hapke[wav_index].rho_accurate
cext = dust_file.array['primary'].data[:, :, 0]
csca = dust_file.array['primary'].data[:, :, 1]
csca[:, 0:2] = guess * cext[:, 0:2]
c_ext = ForwardScatteringProperty(
cext,
particle_size_grid=sizes,
wavelength_grid=wavs)
c_sca = ForwardScatteringProperty(
csca,
particle_size_grid=sizes,
wavelength_grid=wavs)
dust_properties = ForwardScatteringPropertyCollection()
dust_properties.add_property(c_ext, 'c_extinction')
dust_properties.add_property(c_sca, 'c_scattering')
# Use the Curiosity OD
dust_col = Column(dust_properties, model_eos,
conrath_profile.profile, p_sizes,
short_wav[pixel_index, :], 0.88, pixel_od[pixel_index],
dust_phsfn)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Make the model
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
model = ModelAtmosphere()
# Make tuples of (dtauc, ssalb, pmom) for each constituent
dust_info = (
dust_col.total_optical_depth, dust_col.scattering_optical_depth,
dust_col.scattering_optical_depth * dust_col.phase_function)
rayleigh_info = (
rco2.scattering_optical_depths, rco2.scattering_optical_depths,
rco2.phase_function) # This works since scat OD = total OD
# Add dust and Rayleigh scattering to the model
model.add_constituent(dust_info)
model.add_constituent(rayleigh_info)
model.compute_model()
optical_depths = model.hyperspectral_total_optical_depths[:, wav_index]
ssa = model.hyperspectral_total_single_scattering_albedos[:, wav_index]
polynomial_moments = model.hyperspectral_legendre_moments[:, :, wav_index]
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Make the output arrays
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
oa = OutputArrays(cp)
albmed = oa.albedo_medium
flup = oa.diffuse_up_flux
rfldn = oa.diffuse_down_flux
rfldir = oa.direct_beam_flux
dfdt = oa.flux_divergence
uu = oa.intensity
uavg = oa.mean_intensity
trnmed = oa.transmissivity_medium
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Optical depth output structure
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
utau = UserLevel(cp, mb).optical_depth_output
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Run the model
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
rfldir, rfldn, flup, dfdt, uavg, uu, albmed, trnmed = \
disort.disort(usrang, usrtau, ibcnd, onlyfl, prnt, plank, lamber,
deltamplus, dopseudosphere, optical_depths, ssa,
polynomial_moments, temperatures, low_wavenumber,
high_wavenumber, utau,
mu0[pixel_index],
phi0[pixel_index],
mu[pixel_index],
phi[pixel_index], fbeam, fisot,
albedo, btemp, ttemp, temis, radius, h_lyr, rhoq, rhou,
rho_accurate, bemst, emust, accur, header, rfldir,
rfldn, flup, dfdt, uavg, uu, albmed, trnmed)
return (uu[0, 0, 0] - reflectance[pixel_index, wav_index])**2
def setUp(self) -> None:
self.oa = OutputArrays(ComputationalParameters(10, 30, 20, 40, 50, 60))