##CALLING DISORT
rfldir_array = []
rfldn_array = []
flup_array = []
dfdt_array = []
uavg_array = []
uu_array = []
albmed_array = []
trnmed_array = []
for i in range (n_data):
[rfldir, rfldn, flup, dfdt, uavg, uu, albmed, trnmed] =\
disort.run(dTau=dTau, iphas=iphas, uphas=[p_array[i]], w0=[w0_array[i]], gg=gg,
umu0=umu0, phi0=phi0, albedo=albedo, fbeam=fbeam,
umu=umu, phi=phi, maxmom=maxmom, prnt=prnt)
rfldir_array.append(rfldir)
rfldn_array.append(rfldn)
flup_array.append(flup)
dfdt_array.append(dfdt)
uavg_array.append(uavg)
uu_array.append(uu)
albmed_array.append(albmed)
trnmed_array.append(trnmed)
for i in range(len(uu_array)):
print(uu_array[i])
# [rfldir, rfldn, flup, dfdt, uavg, uu, albmed, trnmed] =\
# disort.run(dTau, w0=w0, iphas=iphas, gg=gg,
# umu0=umu0, phi0=phi0, albedo=albedo, fbeam=fbeam,
# utau=uTau, umu=umu, phi=phi)
# CASE IMPLEMENTED IN run_disort.f
dTau = np.array([0.0, 0.0, 0.0, 1.0, 0.0, 0.0])
iphas = np.array([2, 2, 2, 3, 2, 2])
w0 = np.array([0.5, 0.5, 0.5, 0.899999976, 0.5, 0.5])
N = len(dTau)
gg = np.ones(N)*0.85
prnt = np.array([True, True, True, False, True])
[rfldir, rfldn, flup, dfdt, uavg, uu, albmed, trnmed] =\
disort.run(dTau, w0=w0, iphas=iphas, gg=gg,
umu0=umu0, phi0=phi0, albedo=albedo, fbeam=fbeam,
utau=uTau, umu=umu, phi=phi, prnt=prnt)
print '\n\n'
print '########################################### REFERENCE ###############################################'
print '\n\n'
print ' ****************************************************************************************************'
print ' DISORT: Test Case No. 10a: like 9c, USRANG = True '
print ' ****************************************************************************************************'
print ''
print ' No. streams = 32 No. computational layers = 6'
print ' 2 User optical depths : 0.0000 1.0000'
print ' 4 User polar angle cosines : -1.00000 -0.50000 0.50000 1.00000'
print ' 3 User azimuthal angles : 0.00 60.00 120.00'
print ' No thermal emission'
print ' Boundary condition flag: IBCND = 0'
def get_fluxes(pres_output,pres,temp,wave,Tau,Omega,cosz,Lstar,alpha_surf, \
output_angle = None,
N_streams=4,doThermal=False,Ts=None,sourceFn=None, \
UsrTau=None,UsrAng=None ):
# ---
# setup pyDISORT:
params_disort = {}
params_disort['verbose'] = 0 # 0 = suppress header
# cosine of viewing zenith angle where to output the RT fields (Default: 1.)
if output_angle is None:
params_disort['umu'] = 1.
else:
params_disort[
'umu'] = output_angle # (CAREFUL: might have to be monotonically increasing?)
# Output returned at computational or user-defined tau,angles?
# (default: returns ouput at user-defined angles)
# -> note: I haven't gotten the computational option to work..
if UsrTau is not None:
params_disort['UsrTau'] = UsrTau
if UsrAng is not None:
params_disort['UsrAng'] = UsrAng
# ---
# if output is at user-defined levels:
# define those levels
if pres_output == "toa":
# (if we only want TOA output)
p = np.array([0.])
def get_utau(tau=None, p=None, pres=None):
return np.array([0.])
elif pres_output == "input":
# (output on input grid)
p = pres
def get_utau(tau, p=None, pres=None):
utau = tau
return utau
else:
# (output at user-defined pressures)
# interpolate on log tau
# at toa: tau=0-> -inf -> NaN with this method. manually fix
# also can get utau>max(tau) because of round-off?? manually fix -> still crashes!
p = pres_output
def get_utau(tau, p, pres):
utau = 10**(np.interp(p, pres, np.log10(tau)))
utau[np.isnan(utau)] = 0.
return utau
# ---
params_disort['iphas'] = 2 # phase function: 1=isotropic, 2=rayleigh
params_disort['gg'] = 0. # asymmetry parameter. =0 for Rayleigh
params_disort['umu0'] = cosz
params_disort['albedo'] = alpha_surf
params_disort['Nstr'] = N_streams # number of streams -> ??
params_disort['ibcnd'] = 0
# using spectrally resolved stellar source function?
# need same dims as 'wave'!
if sourceFn is not None:
source = sourceFn(wave)
else:
source = wave * 0. + Lstar
# show more/less output?
params_disort['prnt'] = np.array([False, False, False, False, False])
# include thermal emission?
params_disort['plank'] = doThermal
if doThermal:
# careful about mid-level vs interfaces..
params_disort['temp'] = temp
params_disort['btemp'] = Ts
params_disort['temis'] = 0. # emissivity of top boundary
params_disort['ttemp'] = 0. #Tstrat # doesn't matter if temis=0?
# HERE: assume fixed dnu in wave grid!!
dwave = np.diff(wave)[0]
# ---
# iterate over spectral grid:
# cast p into array form, to deal with float input..
Idirect_grid = np.zeros((len(np.array(p)), len(wave)))
Iplus_grid = np.zeros((len(np.array(p)), len(wave)))
Iminus_grid = np.zeros((len(np.array(p)), len(wave)))
# --
for nu in wave:
# ...
if doThermal:
params_disort['wvnmlo'] = nu - dwave / 2.
params_disort['wvnmhi'] = nu + dwave / 2.
# direct beam source:
params_disort['fbeam'] = source[nu ==
wave] # (don't include cosz here!)
# optical thickness:
tau = np.squeeze(Tau[:, nu == wave]) # 1d
# single scattering albedo:
# careful: tau is computed from kappa via trapz rule -> apply same to omega!
# i.e., int[f(x)dx] = sum [f(i+1)+f(i)]*0.5 * dx(i)
omega = np.squeeze(Omega[:, nu == wave]) # 1d
params_disort['w0'] = 0.5 * (omega[0:-1] + omega[1:])
#
params_disort['utau'] = get_utau(tau, p, pres)
#
dtau = np.diff(tau)
#
Idirect, Iminus, Iplus, dfdt, uavg, uu, albmed, trnmed = disort.run(
dtau, **params_disort)
Idirect_grid[:, nu ==
wave] = Idirect[:, np.newaxis] # cast into right shape..
Iplus_grid[:, nu == wave] = Iplus[:, np.newaxis]
Iminus_grid[:, nu == wave] = Iminus[:, np.newaxis]
if doThermal:
# THERMAL EMISSION has units=W/m2. transform to W/m2/cm-1:
Idirect_grid = Idirect_grid / dwave
Iplus_grid = Iplus_grid / dwave
Iminus_grid = Iminus_grid / dwave
return Idirect_grid, Iplus_grid, Iminus_grid