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, # K
'p': p/1.01325, # 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', 'I/I0',
conditions={'Tgas': T},
name='HAPI')
except:
raise
finally:
if clean_after_run:
shutil.rmtree(HAPIdb)
return s_hapi
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 substract(s1, s2, var='radiance', wunit='nm', Iunit='default',
resample=True, name='default'):
'''Substract s2 to s1
Parameters
----------
s1, s2: Spectrum objects
The spectra to substract.
var: str, optional
Spectral quantity (ex: 'radiance', 'transmittance'...).
wunit: str, optional
Wave unit ('nm', 'cm-1', ...) to use for output. If default, s1 wunit is taken.
Iunit: str
If 'default' s1 unit is used for variable var.
name: str, optional
If not given will be s1 and s2 names separated by '+'.
Returns
----------
sub : Spectrum object where intensities of s1 and s2 are substracted
Note
----------
Wavelength of s1 is taken as reference.
'''
if s1.get_conditions()['medium'] != s2.get_conditions()['medium']:
raise ValueError('Not the same medium for s1 and s2')
# Check inputs, get defaults
# ----
if Iunit == 'default':
try:
Iunit = s1.units[var]
except KeyError: # unit not defined in dictionary
raise KeyError('Iunit not defined in spectrum. Cant plot')
w1, I3 = get_diff(s1, s2, var=var, wunit=wunit, Iunit=Iunit,
resample=resample)
if name != 'default':
name = s1.get_name()+'+'+s2.get_name()
sub = Spectrum.from_array(w1, I3, var,
waveunit=wunit,
unit=Iunit,
conditions={'medium' : s1.conditions['medium'], 'waveunit':wunit},
name=name)
return sub
SourceTables=molecule,
Environment={
"T": T,
"p": pressure_bar / 1.01315,
}, # K # atm
GammaL="gamma_self",
WavenumberStep=dnu,
HITRAN_units=False,
)
return nu, coef
t0 = time()
nu, coef = calc_hapi()
t0 = time() - t0
print(("Calculated with HAPI in {0:.2f}s".format(t0)))
s_hapi = Spectrum.from_array(nu,
coef,
"abscoeff",
waveunit="cm-1",
unit="cm-1")
s_hapi.name = "HAPI ({0:.1f}s)".format(t0)
plot_diff(s_hapi, s, "abscoeff")
print(("Calculated with RADIS in {0:.2f}s".format(
s.conditions["calculation_time"])))
print(("Number of lines in RADIS:", len(sf.df0)))
# plt.savefig('radis_vs_hapi_test_large_ch4.pdf')
def calc_hapi():
nu, coef = absorptionCoefficient_Voigt(
SourceTables=molecule,
Environment={
'T': T, # K
'p': pressure_bar / 1.01315, # atm
},
GammaL='gamma_self',
WavenumberStep=dnu,
HITRAN_units=False)
return nu, coef
t0 = time()
nu, coef = calc_hapi()
t0 = time() - t0
print(('Calculated with HAPI in {0:.2f}s'.format(t0)))
s_hapi = Spectrum.from_array(nu,
coef,
'abscoeff',
waveunit='cm-1',
unit='cm-1')
s_hapi.name = 'HAPI ({0:.1f}s)'.format(t0)
plot_diff(s_hapi, s, 'abscoeff')
print(('Calculated with RADIS in {0:.2f}s'.format(
s.conditions['calculation_time'])))
print(('Number of lines in RADIS:', len(sf.df0)))
# plt.savefig('radis_vs_hapi_test_large_ch4.pdf')
import matplotlib.pyplot as plt
from scipy.optimize import minimize
# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------
# USER SECTION (change this as you want)
# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------
# %% Get Fitted Data
# Data from Dang, adapted by Klarenaar, digitized by us
s_exp = Spectrum.from_txt(
getValidationCase('test_CO2_3Tvib_vs_klarenaar_data' +
'\klarenaar_2017_digitized_data.csv'),
'transmittance_noslit',
waveunit='cm-1',
unit='I/I0',
delimiter=',',
name='Klarenaar 2017')
w_exp, T_exp = s_exp.get('transmittance_noslit', wunit='cm-1')
# %% Calculate
sf = SpectrumFactory(
2284.2,
2284.6,
wstep=0.001, # cm-1
pressure=20 * 1e-3, # bar
db_use_cached=True,
lvl_use_cached=True,