def spectrums(molecule, ids, path):
print(f"\n***** Plotting Spectrums *****\n")
environment = {"p": 1, "T": 296, "l": 1000}
nu1, coef = absorptionCoefficient_Voigt(
(ids, ),
molecule,
OmegaStep=0.01,
HITRAN_units=False,
GammaL="gamma_self",
Environment=environment,
)
nu2, absorp = absorptionSpectrum(nu1, coef, Environment=environment)
nu3, transm = transmittanceSpectrum(nu1, coef, Environment=environment)
nu4, radian = radianceSpectrum(nu1, coef, Environment=environment)
plt.figure()
plt.subplot(2, 2, 1)
plt.plot(nu1, coef, "r")
plt.title(f"{molecule} Absorption Coefficient")
plt.subplot(2, 2, 2)
plt.plot(nu2, absorp, "g")
plt.title(f"{molecule} Absorption Spectrum")
plt.subplot(2, 2, 3)
plt.plot(nu3, transm, "b")
plt.title(f"{molecule} Transmittance Spectrum")
plt.subplot(2, 2, 4)
plt.plot(nu4, radian, "y")
plt.title(f"{molecule} Radiance Spectrum")
plt.tight_layout()
plt.savefig(f"{path}/spectrums.png")
plt.clf()
def hires(molecule, ids, path):
print(f"\n***** Plotting HiRes *****\n")
environment = {"p": 1, "T": 296, "l": 1000}
nu1, coef = absorptionCoefficient_Voigt(
(ids, ),
molecule,
OmegaStep=0.01,
HITRAN_units=False,
GammaL="gamma_self",
Environment=environment,
)
nu2, transm = transmittanceSpectrum(nu1, coef, Environment=environment)
nu3, conv, _, _, _ = convolveSpectrum(
nu2,
transm,
SlitFunction=SLIT_MICHELSON,
Resolution=1.0,
AF_wing=20.0,
)
plt.figure()
plt.plot(nu2, transm, "red", nu3, conv, "blue")
plt.legend(["HI-RES", "Michelson"])
plt.tight_layout()
plt.savefig(f"{path}/hires.png")
plt.clf()
def absorptions(molecule, ids, path):
print(f"\n***** Plotting Absorption Coefficients *****\n")
plt.figure()
colors = ["r", "g", "b", "y"]
for i, temperature in enumerate([296]):
nu, coef = absorptionCoefficient_Voigt(
(ids, ),
molecule,
OmegaStep=0.01,
HITRAN_units=False,
GammaL="gamma_self",
Environment={
"p": 1,
"T": temperature
},
)
plt.subplot(2, 2, i + 1)
plt.plot(nu, coef, colors[i])
plt.title(f"{molecule} Absorption (p=1atm, T={temperature}K)")
plt.xlabel("Wavenumber")
plt.ylabel("Absorption Coefficient")
plt.tight_layout()
plt.savefig(f"{path}/absorption_coefficients.png")
plt.clf()
def transform_data(molecules, nu_min, nu_max):
for molecule, spec in molecules.items():
print(f"\n***** Converting Molecule {molecule} Data to CSV *****\n")
dataset = pandas.DataFrame(columns=COLUMNS)
environment = {"T": 296, "p": 1, "l": 1}
wave_number, absorption_coefficient = absorptionCoefficient_Voigt(
Components=(spec, ),
SourceTables=molecule,
OmegaRange=(nu_min, nu_max),
OmegaStep=0.1,
HITRAN_units=False,
Environment=environment,
)
_, absorption_spectrum = absorptionSpectrum(wave_number,
absorption_coefficient,
Environment=environment)
_, transmittance_spectrum = transmittanceSpectrum(
wave_number, absorption_coefficient, Environment=environment)
dataset["wave_number"] = wave_number
dataset["mass"] = molecularMass(spec[0], spec[1])
dataset["name"] = molecule
dataset["absorption_coefficient"] = absorption_coefficient
dataset["absorption_spectrum"] = absorption_spectrum
dataset["transmittance_spectrum"] = transmittance_spectrum
dataset.to_csv(f"{CSV}/{molecule}.csv")
def calc_hapi():
nu, coef = absorptionCoefficient_Voigt(
SourceTables=molecule,
Environment={
"T": T,
"p": pressure_bar / 1.01315,
}, # K # atm
GammaL="gamma_self",
WavenumberStep=dnu,
HITRAN_units=False,
)
return nu, coef
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
#StartTime = time.time()
hapi.db_begin('TestData')
nu_hapi_Doppler, abs_hapi_Doppler = hapi.absorptionCoefficient_Doppler(
SourceTables=Molecule,
OmegaGrid=WaveNumber,
HITRAN_units=True,
Environment=Env,
GammaL='gamma_self',
OmegaWing=OmegaWingValue,
OmegaWingHW=0.0,
LineShift=False) #, OmegaStep=0.01)
nu_hapi_Voigt, abs_hapi_Voigt = hapi.absorptionCoefficient_Voigt(
SourceTables=Molecule,
OmegaGrid=WaveNumber,
HITRAN_units=True,
Environment=Env,
GammaL='gamma_air',
OmegaWing=OmegaWingValue,
OmegaWingHW=0.0,
LineShift=False) #, OmegaStep=0.01)
#TimeTakenHapi = time.time() - StartTime
#print("The time taken for HAPI is::",TimeTakenHapi)
StartTime = time.time()
Database = ReadData(Molecule, Location="data/")
CrossSectionDoppler = CalcCrossSection(Database,
Temp=TempValue,
P=P_Value,
Broadening="Self",
WN_Grid=WaveNumber,
def calDas(gasList, nu, profile, mode, iCut=1e-30, etalonCoeff=None,
unitDict={'c': 'V ratio', 'p': 'hPa', 't': 'K', 'l': 'cm'}, info_out=False):
"""
Calculate direction absorption spectrum.
Parameters
----------
gasList: list of dict
List of parameters for calculation. The dict should have keys for 'gas' (
gas name str), 'p' (pressure in hPa), 't' (temperature in K), 'l' (path
length in cm), 'c' (volume mixing ratio).
nu: array
Wavelength array in cm-1.
profile: str
Choose one from 'Voigt', 'HT', 'Doppler', and 'Lorentz'.
mode: str
Choose one from 'Absorbance', 'Transmission', 'Absorb coeff'.
iCut: float
Intensity cut threshold.
etalonCoeff: list of dict
Results from generateEtalons, containing coefficients for etalon calculation.
info_out: bool
True to output line infomation.
Returns
-------
results: list of dict
Each dict in the list has keys of 'gasParams' (dict given in input),
'nu' (wavelength array cm^-1), 'coeff' (spectrum coeff).
"""
results = []
for idx, gasParams in enumerate(gasList):
if gasParams['gas'] not in hapi.tableList():
return str('Cannot find specified gas.')
nuInTable = hapi.getColumn(gasParams['gas'], 'nu')
if (np.min(nu) < np.min(nuInTable) - 1) | (
np.min(nu) > np.max(nuInTable) + 1) | (
np.max(nu) > np.max(nuInTable) + 1) | (
np.max(nu) < np.min(nuInTable) - 1):
return str(
'Cannot find lines within specified wavenumber range, please download data.')
Cond = ('AND', ('BETWEEN', 'nu', np.min(nu), np.max(nu)), ('>=', 'sw', iCut))
hapi.select(gasParams['gas'], Conditions=Cond, DestinationTableName='tmp')
p, t, l, n = unitHandler(gasParams, unitDict)
if profile == 'Voigt':
nu, coeff = hapi.absorptionCoefficient_Voigt(SourceTables='tmp',
OmegaGrid=nu,
Environment={'T': t,
'p': p})
elif profile == 'HT':
nu, coeff = hapi.absorptionCoefficient_HT(SourceTables='tmp',
OmegaGrid=nu,
Environment={'T': t, 'p': p},
IntensityThreshold=iCut)
elif profile == 'Doppler':
nu, coeff = hapi.absorptionCoefficient_Doppler(SourceTables='tmp',
OmegaGrid=nu,
Environment={'T': t,
'p': p},
IntensityThreshold=iCut)
elif profile == 'Lorentz':
nu, coeff = hapi.absorptionCoefficient_Lorentz(SourceTables='tmp',
OmegaGrid=nu,
Environment={'T': t,
'p': p},
IntensityThreshold=iCut)
else:
raise Exception('No suitable profile.')
if mode == 'Absorbance':
coeff = coeff * n * l
elif mode == 'Transmission':
coeff = coeff * n * l
coeff = np.exp(-coeff)
if info_out:
hapi.select('tmp', File='tmp.txt')
hapi.dropTable('tmp')
result = dict()
result['gasParams'] = gasParams
result['nu'] = nu
result['spectrum'] = coeff
results.append(result)
return results
import hapi as hp
import matplotlib.pyplot as plt
hp.db_begin("data")
#hp.fetch("H2O",1,1,3400,4100)
hp.select('H2O',
ParameterNames=('nu', 'sw'),
Conditions=('between', 'nu', 4000, 4100))
nu, coef = hp.absorptionCoefficient_Voigt(((1, 1), ),
'H2O',
OmegaStep=1,
HITRAN_units=False,
GammaL='gamma_self',
Environment={
'p': 1,
'T': 296.
})
plt.plot(nu, coef)
plt.show()