def import_hitran_and_populate_particles_table():
start_time = time.time()
'''
#change file to loadable version
with open('/home/toma/Desktop/molecule_properties.txt', 'r') as f:
outfile = open('/home/toma/Desktop/molecule_properties (copy).txt', 'w')
for line in f:
data = line.split()
data.pop(1)
for i in data:
outfile.write("%s " % i)
outfile.write('\n')
outfile.close()
f.close()
'''
version_name = 'HITRAN_2016'
reference_link = r'https://www.sciencedirect.com/science/article/pii/S0022407317301073?via%3Dihub'
#everything is in string though to be noticed
#length of lists are 124
mol_ids, iso_ids, iso_names, iso_abundances, iso_masses, mol_names = \
np.loadtxt('/home/toma/Desktop/molecule_properties (copy).txt', dtype='str', skiprows=1, usecols=(1, 2, 3, 4, 5, 6), unpack=True)
for i in range(len(mol_ids)):
particle_property_query = "INSERT INTO particles VALUES('%s', '%s', '%s', '%s', '%s', null);" % (mol_names[i], iso_names[i], \
iso_abundances[i], iso_masses[i], 1) #this one is temporary
#insert each molecule's properties into particles table
sql_order(particle_property_query)
#then, fetch all the data from HITRAN using HAPI
hapi.db_begin('data')
#becasue cannot choose inifinity as upper limit, use a giant number instead
#gpp is upper state degeneracy
hapi.fetch(mol_names[i], int(mol_ids[i]), int(iso_ids[i]), 0, 1e9, Parameters=['nu', 'a', 'gamma_air', 'n_air', 'delta_air', \
'elower', 'gpp', 'gamma_H2', 'n_H2', 'delta_H2', 'gamma_He', 'n_He', 'delta_He'])
#open the file and use insert_hitran.py to insert all parameters into transitions table
filename = '/home/toma/Desktop/linelists-database/data/{}.data'.format(
mol_names[i])
insert_hitran.insert_hitran(filename, version_name, i + 1,
reference_link)
#delete the files since the files are named by HAPI using mol_name instead of iso_name
#s.t. python wont get confused in the for loop
header_filename = '/home/toma/Desktop/linelists-database/data/{}.header'.format(
mol_names[i])
os.remove(filename)
os.remove(header_filename)
print("Finished in %s seconds" % (time.time() - start_time))
def calc_hapi():
""" Calc spectrum under HAPI """
clean_after_run = not exists(HAPIdb) and False
try:
db_begin(HAPIdb)
if not molecule in tableList(
): # only if data not downloaded already
fetch(
molecule,
mol_id,
iso,
wmin - broadening_max_width / 2,
wmax + broadening_max_width / 2,
)
# HAPI doesnt correct for side effects
# Calculate with HAPI
nu, coef = absorptionCoefficient_Voigt(
SourceTables="CO2",
Environment={
"T": T,
"p": p / 1.01325,
}, # K # atm
WavenumberStep=dnu,
HITRAN_units=False,
GammaL="gamma_self",
)
nu, trans = transmittanceSpectrum(
nu,
coef,
Environment={
"l": L,
},
) # cm
s_hapi = Spectrum.from_array(
nu,
trans,
"transmittance_noslit",
"cm-1",
"1",
conditions={"Tgas": T},
name="HAPI",
)
except:
raise
finally:
if clean_after_run:
shutil.rmtree(HAPIdb)
return s_hapi
def test_broadening_vs_hapi(rtol=1e-2,
verbose=True,
plot=False,
*args,
**kwargs):
"""
Test broadening against HAPI and tabulated data
We're looking at CO(0->1) line 'R1' at 2150.86 cm-1
"""
from hapi import absorptionCoefficient_Voigt, db_begin, fetch, tableList
if plot: # Make sure matplotlib is interactive so that test are not stuck in pytest
plt.ion()
setup_test_line_databases() # add HITRAN-CO-TEST in ~/.radis if not there
# Conditions
T = 3000
p = 0.0001
wstep = 0.001
wmin = 2150 # cm-1
wmax = 2152 # cm-1
broadening_max_width = 10 # cm-1
# %% HITRAN calculation
# -----------
# Generate HAPI database locally
hapi_data_path = join(dirname(__file__),
__file__.replace(".py", "_HAPIdata"))
db_begin(hapi_data_path)
if not "CO" in tableList(): # only if data not downloaded already
fetch("CO", 5, 1, wmin - broadening_max_width / 2,
wmax + broadening_max_width / 2)
# HAPI doesnt correct for side effects
# Calculate with HAPI
nu, coef = absorptionCoefficient_Voigt(
SourceTables="CO",
Environment={
"T": T,
"p": p / 1.01325,
}, # K # atm
WavenumberStep=wstep,
HITRAN_units=False,
)
s_hapi = Spectrum.from_array(nu,
coef,
"abscoeff",
"cm-1",
"cm-1",
conditions={"Tgas": T},
name="HAPI")
# %% Calculate with RADIS
# ----------
sf = SpectrumFactory(
wavenum_min=wmin,
wavenum_max=wmax,
mole_fraction=1,
path_length=1, # doesnt change anything
wstep=wstep,
pressure=p,
broadening_max_width=broadening_max_width,
isotope=[1],
warnings={
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"HighTemperatureWarning": "ignore",
"GaussianBroadeningWarning": "ignore",
},
) # 0.2)
sf.load_databank(path=join(hapi_data_path, "CO.data"),
format="hitran",
parfuncfmt="hapi")
# s = pl.non_eq_spectrum(Tvib=T, Trot=T, Ttrans=T)
s = sf.eq_spectrum(Tgas=T, name="RADIS")
if plot: # plot broadening of line of largest linestrength
sf.plot_broadening(i=sf.df1.S.idxmax())
# Plot and compare
res = abs(get_residual_integral(s, s_hapi, "abscoeff"))
if plot:
plot_diff(
s,
s_hapi,
var="abscoeff",
title="{0} bar, {1} K (residual {2:.2g}%)".format(p, T, res * 100),
show_points=False,
)
plt.xlim((wmin, wmax))
if verbose:
printm("residual:", res)
assert res < rtol
def create(molecules, nu_min, nu_max):
for molecule, spec in molecules.items():
print(f"\n***** Loading Molecule: {molecule} *****\n")
print(f"*** Minimum Wave Number (nu): {nu_min} ***")
print(f"*** Maximum Wave Number (nu): {nu_max} ***")
fetch(molecule, spec[0], spec[1], nu_min, nu_max)
# Import external libraries
from hapi import absorptionCoefficient_Lorentz, transmittanceSpectrum, fetch
from numpy import savetxt, shape, array
# Spectral range of interest - um
lmin = 2.0 # min wavelength
lmax = 3.0 # max wavelength
kmin = 10**4 / lmax # min wavenumber
kmax = 10**4 / lmin # max wavenumber
# Molecular species of interest
nmol = 'H2O'
# Fetch the HITRAN data for the molecule of interest
fetch(nmol, 1, 1, kmin, kmax)
# Compute the absorption/extinction coefficient - cm^-1
kmat, abscoeff = absorptionCoefficient_Lorentz(SourceTables = nmol, \
WavenumberStep = 0.5, \
HITRAN_units = False)
# Process the data to be exported
data = array([10**4 / kmat * 1000, abscoeff]).T
data = data[::-1]
# Export the processed data
filename = './Data/abscoeff' + nmol + '.txt'
savetxt(filename, data, fmt=['%.4E', '%.4E'])
# End of file
D_n_nO2 = control['delta number of loosen O2 layers']
if control['if A band']:
S_startWavelength = control['sigma start wavelength']
S_endWavelength = control['sigma end wavelength']
S_minTH = control['sigma min tangent height']
S_maxTH = control['sigma max tangent height']
S_w1_step = control['sigma w1 step']
S_n_nO2 = control['sigma number of loosen O2 layers']
# load hitran database
db_begin(control['hitran database path'])
if not os.path.exists(
os.path.join(
control['hitran database path'], 'O2_{:.1f}-{:.1f}.data'.format(
D_startWavelength, D_endWavelength))):
fetch('O2_{:.1f}-{:.1f}'.format(D_startWavelength, D_endWavelength), 7, 1,
1e7 / D_endWavelength, 1e7 / D_startWavelength)
if control['if A band']:
if not os.path.exists(
os.path.join(
control['hitran database path'],
'O2_{:.1f}-{:.1f}.data'.format(S_startWavelength,
S_endWavelength))):
fetch('O2_{:.1f}-{:.1f}'.format(S_startWavelength, S_endWavelength), 7,
1, 1e7 / S_endWavelength, 1e7 / S_startWavelength)
# load singlet delta band data
s.loadData(if_close_file=False, startWavelength=1200, endWavelength=1340)
# parse data to regular along-track/across track grids, usually 30 along-track, 8 across-track
D_granules = s.divideProfiles(
radiancePerElectron=control['delta radiance per electron'])
D_ngranule = len(D_granules)