def test_broadening_DLM_noneq(verbose=True, plot=False, *args, **kwargs):
'''
Test Noneq version of DLM and makes sure it gives the same results as the eq
one when used with Tvib=Trot
'''
if plot: # Make sure matplotlib is interactive so that test are not stuck in pytest
plt.ion()
setup_test_line_databases() # add HITRAN-CO2-TEST in ~/.radis if not there
# Conditions
p = 1
wstep = 0.002
wmin = 2380 # cm-1
wmax = 2400 # cm-1
broadening_max_width = 10 # cm-1
# %% 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',
verbose=3,
warnings={'MissingSelfBroadeningWarning':'ignore',
'NegativeEnergiesWarning':'ignore',
'HighTemperatureWarning':'ignore',
'GaussianBroadeningWarning':'ignore'}
) # 0.2)
sf.load_databank('HITRAN-CO2-TEST')
# DLM:
sf.misc['chunksize'] = 'DLM'
s_dlm_eq = sf.eq_spectrum(Tgas=3000)
s_dlm_eq.name = 'DLM eq ({0:.2f}s)'.format(s_dlm_eq.conditions['calculation_time'])
s_dlm_noneq = sf.non_eq_spectrum(Tvib=3000, Trot=3000)
s_dlm_noneq.name = 'DLM noneq ({0:.2f}s)'.format(s_dlm_noneq.conditions['calculation_time'])
# Compare
res = get_residual(s_dlm_eq, s_dlm_noneq, 'radiance_noslit')
if verbose:
print('Residual:', res)
# plot
if plot:
plot_diff(s_dlm_eq, s_dlm_noneq)
assert res <= 4e-5
def test_broadening_methods_different_wstep(verbose=True, plot=False, *args, **kwargs):
'''
Test direct Voigt broadening vs convolution of Gaussian x Lorentzian
for different spectral grid resolution
'''
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 = 1
wmin = 2150 # cm-1
wmax = 2152 # cm-1
broadening_max_width = 10 # cm-1
for i, wstep in enumerate([0.01, 0.1, 0.5]):
# %% 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',
verbose=False,
warnings={'MissingSelfBroadeningWarning':'ignore',
'NegativeEnergiesWarning':'ignore',
'HighTemperatureWarning':'ignore',
'GaussianBroadeningWarning':'ignore'}
) # 0.2)
sf.load_databank('HITRAN-CO-TEST')
# s = pl.non_eq_spectrum(Tvib=T, Trot=T, Ttrans=T)
sf._broadening_method = 'voigt'
s_voigt = sf.eq_spectrum(Tgas=T, name='direct')
sf._broadening_method = 'convolve'
s_convolve = sf.eq_spectrum(Tgas=T, name='convolve')
res = get_residual(s_voigt, s_convolve, 'abscoeff')
if verbose:
print('Residual:', res)
# plot the last one
if plot:
plot_diff(s_voigt, s_convolve, 'abscoeff', nfig='test_voigt_broadening_methods'+str(i),
title='P {0} bar, T {1} K, wstep {2} cm-1'.format(p, T, wstep))
assert res < 2e-4
def test_visualTestBaseline(plot=True, *args, **kwargs):
s = load_spec(getTestFile("CO_Tgas1500K_mole_fraction0.01.spec"),
binary=True)
s.update('radiance_noslit', verbose=False)
s.apply_slit(0.1)
s = Radiance_noslit(s)
assert s.units['radiance'] == 'mW/cm2/sr/nm'
s2 = sub_baseline(s, 2e-4, -2e-4, name='sub_arb_baseline')
if plot:
plot_diff(s, s2)
def test_offset(plot=True):
s = load_spec(getTestFile("CO_Tgas1500K_mole_fraction0.01.spec"),
binary=True)
s.update('radiance_noslit', verbose=False)
s.apply_slit(0.1)
s2 = offset(s, 10, 'nm', name='offset_10nm')
if plot:
plot_diff(s, s2)
assert np.allclose(s2.get_wavelength(which='convoluted'),
s.get_wavelength(which='convoluted') + 10)
assert np.allclose(s2.get_wavelength(which='non_convoluted'),
s.get_wavelength(which='non_convoluted') + 10)
# Test inplace version
s.offset(10, 'nm')
assert np.allclose(s2.get_wavelength(which='convoluted'),
s.get_wavelength(which='convoluted'))
def test_broadening_methods_different_wstep(verbose=True,
plot=False,
*args,
**kwargs):
"""
Test direct Voigt broadening vs convolution of Gaussian x Lorentzian
for different spectral grid resolution
"""
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 = 1
wmin = 2150 # cm-1
wmax = 2152 # cm-1
broadening_max_width = 10 # cm-1
for i, wstep in enumerate([0.01, 0.1, 0.5]):
# %% 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",
optimization=None,
verbose=False,
warnings={
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"HighTemperatureWarning": "ignore",
"GaussianBroadeningWarning": "ignore",
"AccuracyError": "ignore",
"AccuracyWarning": "ignore",
},
) # 0.2)
sf.load_databank("HITRAN-CO-TEST")
# s = pl.non_eq_spectrum(Tvib=T, Trot=T, Ttrans=T)
sf.params.broadening_method = "voigt"
s_voigt = sf.eq_spectrum(Tgas=T, name="direct")
sf.params.broadening_method = "convolve"
s_convolve = sf.eq_spectrum(Tgas=T, name="convolve")
res = get_residual(s_voigt, s_convolve, "abscoeff")
if verbose:
print("Residual:", res)
# plot the last one
if plot:
plot_diff(
s_voigt,
s_convolve,
"abscoeff",
nfig="test_voigt_broadening_methods" + str(i),
title="P {0} bar, T {1} K, wstep {2} cm-1".format(p, T, wstep),
)
assert res < 2e-4
def test_broadening_methods_different_conditions(verbose=True,
plot=False,
*args,
**kwargs):
"""
Test direct Voigt broadening vs convolution of Gaussian x Lorentzian
for different spectral grid resolution
Notes
-----
Reference broadening calculated manually with the HWHM formula of
`HITRAN.org <https://hitran.org/docs/definitions-and-units/>`_
"""
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
wstep = 0.005
wmin = 2150.4 # cm-1
wmax = 2151.4 # cm-1
broadening_max_width = 2 # cm-1
for (T, p, fwhm_lorentz, fwhm_gauss) in [
# K, bar, expected FWHM for Lotentz, gauss (cm-1)
(3000, 1, 0.02849411, 0.01594728),
(300, 1, 0.16023415, 0.00504297),
(3000, 0.01, 0.00028494, 0.01594728),
]:
# %% 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",
verbose=False,
warnings={
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"HighTemperatureWarning": "ignore",
"OutOfRangeLinesWarning": "ignore",
"GaussianBroadeningWarning": "ignore",
"CollisionalBroadeningWarning": "ignore",
},
)
sf.load_databank("HITRAN-CO-TEST")
# Manually filter line database, keep one line only:
sf.df0.drop(sf.df0[sf.df0.vu != 1].index, inplace=True)
assert isclose(sf.df0.wav, 2150.856008)
# Calculate spectra (different broadening methods)
sf.params.broadening_method = "voigt"
s_voigt = sf.eq_spectrum(Tgas=T, name="direct")
# assert broadening FWHM are correct
assert isclose(2 * float(sf.df1.hwhm_gauss), fwhm_gauss)
assert isclose(2 * float(sf.df1.hwhm_lorentz), fwhm_lorentz)
sf.params.broadening_method = "convolve"
s_convolve = sf.eq_spectrum(Tgas=T, name="convolve")
# assert broadening FWHM are correct
assert isclose(2 * float(sf.df1.hwhm_gauss), fwhm_gauss)
assert isclose(2 * float(sf.df1.hwhm_lorentz), fwhm_lorentz)
res = get_residual(s_voigt, s_convolve, "abscoeff")
if verbose:
print(
"{0} K, {1} bar: FWHM lorentz = {2:.3f} cm-1, FWHM gauss = {3:.3f} cm-1"
.format(T, p, 2 * float(sf.df1.hwhm_lorentz),
2 * float(sf.df1.hwhm_gauss)))
if plot:
plot_diff(
s_voigt,
s_convolve,
"abscoeff",
title=
r"T {0} K, p {1} bar: w$_\mathrm{{L}}$ {2:.3f}, w$_\mathrm{{G}}$ {3:.3f} cm$^{{-1}}$"
.format(T, p, 2 * float(sf.df1.hwhm_lorentz),
float(sf.df1.hwhm_gauss)),
)
# assert all broadening methods match
assert res < 2e-4
def test_noneq_continuum(plot=False,
verbose=2,
warnings=True,
*args,
**kwargs):
'''
Test calculation with pseudo-continuum under nonequilibrium
Assert results on emisscoeff dont change
Notes
-----
Uses HITRAN so it can deployed and tested on [Travis]_, but we should switch
to HITEMP if some HITEMP files can be downloaded automatically at the
execution time.
'''
if plot: # Make sure matplotlib is interactive so that test are not stuck in pytest
plt.ion()
try:
if verbose:
printm('>>> test_noneq_continuum')
sf = SpectrumFactory(wavelength_min=4200,
wavelength_max=4500,
parallel=False,
bplot=False,
cutoff=1e-23,
molecule='CO2',
isotope='1,2',
db_use_cached=True,
broadening_max_width=10,
path_length=0.1,
mole_fraction=1e-3,
medium='vacuum',
verbose=verbose)
sf.warnings.update({
'MissingSelfBroadeningWarning': 'ignore',
'NegativeEnergiesWarning': 'ignore',
'LinestrengthCutoffWarning': 'ignore',
'HighTemperatureWarning': 'ignore'
})
sf.fetch_databank(
) # uses HITRAN: not really valid at this temperature, but runs on all machines without install
# sf.load_databank('HITEMP-CO2-DUNHAM') # to take a real advantage of abscoeff continuum, should calculate with HITEMP
sf._export_continuum = True # activate it
# Calculate one without pseudo-continuum
sf.params.pseudo_continuum_threshold = 0
s1 = sf.non_eq_spectrum(Tvib=2000, Trot=1000)
s1.name = 'All lines resolved ({0}) ({1:.1f}s)'.format(
s1.conditions['lines_calculated'],
s1.conditions['calculation_time'])
assert s1.conditions['pseudo_continuum_threshold'] == 0
# Calculate one with pseudo-continuum
sf.params.pseudo_continuum_threshold = 0.05
s2 = sf.non_eq_spectrum(Tvib=2000, Trot=1000)
s2.name = 'Semi-continuum + {0} lines ({1:.1f}s)'.format(
s2.conditions['lines_calculated'],
s2.conditions['calculation_time'])
assert s2.conditions['pseudo_continuum_threshold'] == 0.05
assert 'abscoeff_continuum' in s2.get_vars()
assert 'emisscoeff_continuum' in s2.get_vars()
# Plot
if plot:
plot_diff(s1,
s2,
'radiance_noslit',
Iunit='µW/cm2/sr/nm',
nfig='test_noneq_continuum: diff')
s2.plot('emisscoeff',
label=s2.name,
nfig='test_noneq_continuum: show continuum')
s2.plot('emisscoeff_continuum',
nfig='same',
label='Pseudo-continuum (aggreg. {0:g} lines)'.format(
s2.conditions['lines_in_continuum']),
force=True)
# Compare
res = get_residual(s1, s2, 'abscoeff') + get_residual(
s1, s2, 'emisscoeff')
if verbose:
printm('residual:', res)
assert res < 5e-6
except DatabankNotFound as err:
assert IgnoreMissingDatabase(err, __file__, warnings)
def test_broadening(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 radis.io.hapi import db_begin, fetch, tableList, absorptionCoefficient_Voigt
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
db_begin(join(dirname(__file__), __file__.replace('.py', '_HAPIdata')))
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, # K
'p': p / 1.01325, # 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('HITRAN-CO-TEST')
# 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
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 test_broadening_DLM_FT(verbose=True, plot=False, *args, **kwargs):
"""
Test use of DLM with and without Fourier Transform
Ensures that results are the same, and compare calculation times.
"""
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 = 1
wstep = 0.002
wmin = 2000 # cm-1
wmax = 2300 # cm-1
broadening_max_width = 10 # cm-1
# %% 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",
verbose=verbose,
chunksize="DLM",
warnings={
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"HighTemperatureWarning": "ignore",
"GaussianBroadeningWarning": "ignore",
},
) # 0.2)
sf.load_databank("HITRAN-CO-TEST")
# DLM, real space
if verbose:
print("\nConvolve version \n")
sf._broadening_method = "convolve"
s_dlm = sf.eq_spectrum(Tgas=T)
s_dlm.name = "DLM ({0:.2f}s)".format(s_dlm.conditions["calculation_time"])
# DLM , with Fourier
if verbose:
print("\nFFT version \n")
sf.params.broadening_method = "fft"
s_dlm_fft = sf.eq_spectrum(Tgas=T)
s_dlm_fft.name = "DLM FFT ({0:.2f}s)".format(
s_dlm_fft.conditions["calculation_time"])
# Compare
res = get_residual(s_dlm, s_dlm_fft, "abscoeff")
if verbose:
print("Residual:", res)
# plot
if plot:
plot_diff(s_dlm, s_dlm_fft, "abscoeff")
plt.legend()
assert res < 5e-6
def test_validation_vs_specair(rtol=1e-2,
verbose=True,
plot=False,
*args,
**kwargs):
''' Test RADIS output on CO IR bands against SPECAIR
Test is only performed on integrals of absorption coefficient
RADIS doesnt actually match Specair exactly, but this is due to line intensity
differences (Specair has no rovibrational specific intensities) rather than
differences in populations calculations, as evidenced by the partition functions
comparison in the RADIS presentation article.
'''
setup_test_line_databases() # add HITRAN-CO-TEST in ~/.radis if not there
# %% Specair calculation
# -----------
specair_300_300 = load_spec(getValidationCase(
join('test_validation_vs_specair_noneqCO_data',
'specair_CO_IR_Tvib300_Trot300.spec')),
binary=True)
specair_300_2000 = load_spec(getValidationCase(
join('test_validation_vs_specair_noneqCO_data',
'specair_CO_IR_Tvib300_Trot2000.spec')),
binary=True)
specair_2000_300 = load_spec(getValidationCase(
join('test_validation_vs_specair_noneqCO_data',
'specair_CO_IR_Tvib2000_Trot300.spec')),
binary=True)
article_version = False # just for the article
# %% Compare with RADIS
# ----------
wstep = 0.002
pl = SpectrumFactory(
wavelength_min=4400,
wavelength_max=4900,
mole_fraction=1,
pressure=0.01, # bar
path_length=1, # we dont care for abscoeff anyway
parallel=False,
cutoff=1e-30,
wstep=wstep,
isotope=1, # '1,2,3',
medium='vacuum') # 0.2)
pl.warnings['MissingSelfBroadeningWarning'] = 'ignore'
if article_version:
pl.load_databank('HITEMP-CO-DUNHAM')
else:
pl.load_databank('HITRAN-CO-TEST')
# Available on all systems, convenient for fast testing, but you
# will be missing some small lines for T ~ 2000 K .
print(
'Using HITRAN: small lines will be missing at T ~ 2000K. Use HITEMP if you want them'
)
s_300_300 = pl.eq_spectrum(300, name='RADIS')
s_2000_300 = pl.non_eq_spectrum(Tvib=2000,
Trot=300,
Ttrans=300,
name='RADIS')
s_300_2000 = pl.non_eq_spectrum(Tvib=300,
Trot=2000,
Ttrans=2000,
name='RADIS')
# %% Test
# Compare integrals
b1 = np.isclose(specair_300_300.get_integral('abscoeff'),
s_300_300.get_integral('abscoeff'),
rtol=rtol)
b1 *= np.isclose(specair_2000_300.get_integral('abscoeff'),
s_2000_300.get_integral('abscoeff'),
rtol=rtol)
b1 *= np.isclose(specair_300_2000.get_integral('abscoeff'),
s_300_2000.get_integral('abscoeff'),
rtol=rtol)
# Compare partition functions to hardcoded values
b2 = np.isclose(s_2000_300.lines.Q, 139, atol=1) # Specair: 139
b2 *= np.isclose(s_300_2000.lines.Q, 727, atol=1) # Specair: 727
if verbose:
printm(
'>>> comparing RADIS vs SPECAIR on CO: integrals of abscoeff is are close'
+ ' to within {0:.1f}%: {1} ({2:.1f}%, {3:.1f}%, {4:.1f}%)'.format(
rtol * 100,
bool(b1),
abs(
specair_300_300.get_integral('abscoeff') /
s_300_300.get_integral('abscoeff') - 1) * 100,
abs(
specair_2000_300.get_integral('abscoeff') /
s_2000_300.get_integral('abscoeff') - 1) * 100,
abs(
specair_300_2000.get_integral('abscoeff') /
s_300_2000.get_integral('abscoeff') - 1) * 100,
))
printm('>>> comparing RADIS vs SPECAIR on CO: partition functions ' +
'are equal to round error: {0}'.format(bool(b2)))
if plot:
plot_diff(
specair_300_300,
s_300_300,
title=r'T$_\mathregular{vib}$ 300 K, T$_\mathregular{rot}$ 300 K',
diff_window=int(
0.02 // wstep
), # compensate for small shifts in both codes. we're comparing intensities here.
lw_multiplier=1, #0.75,
wunit='nm_vac',
plot_medium=True,
)
plt.xlim((4500, 4900))
if article_version:
plt.savefig(
'out/test_validation_vs_specair_noneqCO_Tvib300_Trot300.png')
plt.savefig(
'out/test_validation_vs_specair_noneqCO_Tvib300_Trot300.pdf')
plot_diff(
specair_2000_300,
s_2000_300,
title=r'T$_\mathregular{vib}$ 2000 K, T$_\mathregular{rot}$ 300 K',
diff_window=int(
0.02 // wstep
), # compensate for small shifts in both codes. we're comparing intensities here.
lw_multiplier=1, #0.75,
wunit='nm_vac',
plot_medium=True,
)
plt.xlim((4500, 4900))
if article_version:
plt.savefig(
'out/test_validation_vs_specair_noneqCO_Tvib2000_Trot300.png')
plt.savefig(
'out/test_validation_vs_specair_noneqCO_Tvib2000_Trot300.pdf')
plot_diff(
specair_300_2000,
s_300_2000,
title=r'T$_\mathregular{vib}$ 300 K, T$_\mathregular{rot}$ 2000 K',
diff_window=int(
0.02 // wstep
), # compensate for small shifts in both codes. we're comparing intensities here.
lw_multiplier=1, #0.75,
wunit='nm_vac',
plot_medium=True,
)
plt.xlim((4500, 4900))
if article_version:
plt.savefig(
'out/test_validation_vs_specair_noneqCO_Tvib300_Trot2000.png')
plt.savefig(
'out/test_validation_vs_specair_noneqCO_Tvib300_Trot2000.pdf')
return bool(b1 * b2)
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')
def test_abscoeff_continuum(plot=False,
verbose=2,
warnings=True,
threshold=0.1,
*args,
**kwargs):
"""
Test calculation with pseudo-continuum
Assert results on abscoeff dont change
Notes
-----
Uses HITRAN so it can deployed and tested on [Travis]_, but we should switch
to HITEMP if some HITEMP files can be downloaded automatically at the
execution time.
"""
if plot: # Make sure matplotlib is interactive so that test are not stuck in pytest
plt.ion()
try:
if verbose:
printm(">>> test_abscoeff_continuum")
sf = SpectrumFactory(
wavelength_min=4200,
wavelength_max=4500,
parallel=False,
bplot=False,
cutoff=1e-23,
molecule="CO2",
isotope="1,2",
db_use_cached=True,
broadening_max_width=10,
path_length=0.1,
mole_fraction=1e-3,
medium="vacuum",
verbose=verbose,
)
sf.warnings.update({
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"LinestrengthCutoffWarning": "ignore",
"HighTemperatureWarning": "ignore",
})
sf.fetch_databank(
) # uses HITRAN: not really valid at this temperature, but runs on all machines without install
# sf.load_databank('HITEMP-CO2-DUNHAM') # to take a real advantage of abscoeff continuum, should calculate with HITEMP
sf._export_continuum = True # activate it
# Calculate one without pseudo-continuum
sf.params.pseudo_continuum_threshold = 0
s1 = sf.eq_spectrum(Tgas=2000)
s1.name = "All lines resolved ({0}) ({1:.1f}s)".format(
s1.conditions["lines_calculated"],
s1.conditions["calculation_time"])
assert s1.conditions["pseudo_continuum_threshold"] == 0
# Calculate one with pseudo-continuum
sf.params.pseudo_continuum_threshold = threshold
s2 = sf.eq_spectrum(Tgas=2000)
s2.name = "Semi-continuum + {0} lines ({1:.1f}s)".format(
s2.conditions["lines_calculated"],
s2.conditions["calculation_time"])
assert s2.conditions["pseudo_continuum_threshold"] == threshold
assert "abscoeff_continuum" in s2.get_vars()
# Plot
if plot:
plot_diff(
s1,
s2,
"radiance_noslit",
Iunit="µW/cm2/sr/nm",
nfig="test_abscoeff_continuum: diff",
)
s2.plot(
"abscoeff",
label="Full spectrum",
nfig="test_abscoeff_continuum: show continuum",
force=True,
)
s2.plot(
"abscoeff_continuum",
nfig="same",
label="Pseudo-continuum".format(
s2.conditions["lines_in_continuum"]),
force=True,
)
plt.legend()
# Compare
res = get_residual(s1, s2, "abscoeff")
if verbose:
printm("residual:", res)
globals().update(locals())
assert res < 1.32e-6
except DatabankNotFound as err:
assert IgnoreMissingDatabase(err, __file__, warnings)
def test_line_broadening(rtol=1e-3, verbose=True, plot=False, *args, **kwargs):
r"""
Plot absorption coefficient (cm-1) of CO at high temperature (2000 K) with
RADIS, and compare with calculations from HAPI using the HITRAN database
Notes
-----
In this example no data is needed. Everything is downloaded from the HITRAN
database directly using either the HAPI ``fetch`` function, or the RADIS
:meth:`~neq.spec.factory.fetch_databank` method.
"""
from hapi import (
absorptionCoefficient_Voigt,
db_begin,
fetch,
tableList,
transmittanceSpectrum,
)
setup_test_line_databases() # add HITRAN-CO-TEST in ~/.radis if not there
# Conditions
molecule = "CO2"
mol_id = get_molecule_identifier(molecule)
iso = 1
T = 1500
p = 0.1
L = 0.1
# M = 0.001 # mole fraction (dont know where to put that )
dnu = 0.0001
wmin = nm2cm(4372.69 + 0.2) # cm-1
wmax = nm2cm(4372.69 - 0.2) # cm-1
# broadening_max_width = 6 # cm-1
broadening_max_width = 0.5 # cm-1
# %% HITRAN calculation
# -----------
# Generate HAPI database locally
HAPIdb = join(dirname(__file__), __file__.replace(".py", "_HAPIdata"))
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
s_hapi = calc_hapi()
def calc_radis():
# %% Calculate with RADIS
# ----------
pl = SpectrumFactory(
wavenum_min=wmin,
wavenum_max=wmax,
mole_fraction=1,
path_length=L,
wstep=dnu,
molecule=molecule,
pressure=p,
broadening_max_width=broadening_max_width,
cutoff=1e-23,
isotope=iso,
)
pl.warnings["MissingSelfBroadeningWarning"] = "ignore"
pl.warnings["HighTemperatureWarning"] = "ignore"
pl.fetch_databank(
source="hitran",
load_energies=False,
db_use_cached=True,
)
s = pl.eq_spectrum(Tgas=T) # , Ttrans=300)
s.name = "RADIS"
if plot:
pl.plot_broadening()
return s
s = calc_radis()
# %% Compare
# also shrinks HAPI range to the valid one
s_hapi.resample(s.get_wavenumber(), unit="cm-1", energy_threshold=0.1)
save = False # just used in the article
if plot or save:
from radis import plot_diff
# title = '{0} bar, {1} K, {2} cm'.format(p, T, L) if save else None
fig, [ax0, ax1] = plot_diff(s,
s_hapi,
var="transmittance_noslit",
method="ratio",
show=plot)
ax0.annotate(
r"[P64](00$^\mathregular{0}$0)$\rightarrow $(00$^\mathregular{0}$1)",
(2286.945, 0.76),
(2286.94, 0.8),
arrowprops=dict(arrowstyle="->", facecolor="black"),
)
ax0.annotate(
r"[P53](01$^\mathregular{1}$0)$\rightarrow $(01$^\mathregular{1}$1)",
(2286.9, 0.78),
(2286.9, 0.82),
arrowprops=dict(arrowstyle="->", facecolor="black"),
horizontalalignment="right",
)
ax1.set_ylim(0.95, 1.05)
if save:
fig.savefig("out/test_RADIS_vs_HAPI_line_broadening.pdf")
# Compare integrals
diff = abs(
s.get_integral("transmittance_noslit") /
s_hapi.get_integral("transmittance_noslit") - 1)
b = diff < rtol
if verbose:
printm("Integral difference ({0:.2f}%) < {1:.2f}%: {2}".format(
diff * 100, rtol * 100, b))
return b
s_opt.update()
# compare times
t_ref = s_ref.conditions['calculation_time']
t_opt = s_opt.conditions['calculation_time']
t_dlm = s_dlm.conditions['calculation_time']
#%%
plt.ion()
#%%
_, [ax0, ax1] = plot_diff(
s_ref,
s_dlm,
'transmittance_noslit',
method='ratio',
label1='Reference {1} lines ({0:.0f}s)'.format(
t_ref, str_fmt(s_ref.conditions['lines_calculated'])),
label2='New method {1} lines ({0:.0f}s)'.format(
t_dlm, str_fmt(s_dlm.conditions['lines_calculated'])),
) #legendargs={'loc':'lower left', 'handlelength':1, 'fontsize':16.5})
ax0.set_ylim((0.87, 1))
ax1.set_ylim((0.999, 1.001))
handles, labels = ax0.get_legend_handles_labels()
leg = ax0.legend(frameon=False, fontsize=16, loc=3)
axins = ax0.inset_axes([0.60, 0.125, 0.35, 0.45])
axins.ticklabel_format(useOffset=False, axis='x')
axins.tick_params(which='major', labelsize=14)
axins.get_yaxis().set_visible(False)
axins.plot(*s_ref.get('transmittance_noslit', wunit='cm-1'), color='k', lw=2)
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 test_broadening_DLM(verbose=True, plot=False, *args, **kwargs):
"""
Test use of lineshape template for broadening calculation.
Ensures that results are the same with and without DLM.
"""
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 = 1
wstep = 0.002
wmin = 2150 # cm-1
wmax = 2152 # cm-1
broadening_max_width = 10 # cm-1
# %% 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",
verbose=False,
warnings={
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"HighTemperatureWarning": "ignore",
"GaussianBroadeningWarning": "ignore",
},
) # 0.2)
sf.load_databank("HITRAN-CO-TEST")
# Reference: calculate without DLM
assert sf.misc["chunksize"] is None
s_ref = sf.eq_spectrum(Tgas=T)
s_ref.name = "Reference ({0:.2f}s)".format(
s_ref.conditions["calculation_time"])
# DLM:
sf.misc["chunksize"] = "DLM"
sf.params.broadening_method = "convolve"
s_dlm = sf.eq_spectrum(Tgas=T)
s_dlm.name = "DLM ({0:.2f}s)".format(s_dlm.conditions["calculation_time"])
# DLM Voigt with Whiting approximation:
sf.params.broadening_method = "voigt"
s_dlm_voigt = sf.eq_spectrum(Tgas=T)
s_dlm_voigt.name = "DLM Whiting ({0:.2f}s)".format(
s_dlm_voigt.conditions["calculation_time"])
# Compare
res = get_residual(s_ref, s_dlm, "abscoeff")
res_voigt = get_residual(s_dlm, s_dlm_voigt, "abscoeff")
if verbose:
print("Residual:", res)
# plot the last one
if plot:
plot_diff(s_ref, s_dlm, "abscoeff")
plt.legend()
plot_diff(s_dlm, s_dlm_voigt, "abscoeff")
assert res < 1.2e-5
assert res_voigt < 1e-5
Nlines = 1e4
#%% Calculate normal
for width in broadening_max_widths:
spectra_default[width] = load_spec('../spec_fig78/spectra_default[{0}].spec'.format(width), binary=True)
spectra_convolve[width] = load_spec('../spec_fig78/spectra_convolve[{0}].spec'.format(width), binary=True)
spectra_DLM_opt = load_spec('../spec_fig78/spectra_DLM_opt.spec')
plt.ion()
##fig, [ax0, ax1] = plot_diff(spectra_default[broadening_max_widths[1]], spectra_DLM_opt, 'abscoeff', figsize=(10,6))
fig, [ax0, ax1] = plot_diff(spectra_default[broadening_max_widths[1]], spectra_DLM_opt, 'abscoeff', figsize=(10,6))
ax0.set_ylim((0, 0.9))
ax1.set_ylim((-0.0025, 0.0025))
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
axins = ax0.inset_axes([0.115, 0.25, 0.35, 0.45])
axins.ticklabel_format(useOffset=False, axis='x')
axins.tick_params(which='major', labelsize=14)
axins.get_yaxis().set_visible(False)
axins.plot(*spectra_default[broadening_max_widths[1]].get('abscoeff', wunit='cm-1'), color='k', lw=2)
axins.plot(*spectra_DLM_opt.get('abscoeff', wunit='cm-1'), color='r', lw=1)
axins.set_xlim((2235, 2238.5))
def test_noneq_continuum(plot=False,
verbose=2,
warnings=True,
*args,
**kwargs):
"""
Test calculation with pseudo-continuum under nonequilibrium
Assert results on emisscoeff dont change
Notes
-----
Uses HITRAN so it can deployed and tested on `Travis CI <https://travis-ci.com/radis/radis>`_, but we should switch
to HITEMP if some HITEMP files can be downloaded automatically at the
execution time.
"""
if plot: # Make sure matplotlib is interactive so that test are not stuck in pytest
plt.ion()
if verbose:
printm(">>> test_noneq_continuum")
sf = SpectrumFactory(
wavelength_min=4200,
wavelength_max=4500,
cutoff=1e-23,
molecule="CO2",
isotope="1,2",
broadening_max_width=10,
path_length=0.1,
mole_fraction=1e-3,
medium="vacuum",
optimization=None,
verbose=verbose,
)
sf.warnings.update({
"MissingSelfBroadeningWarning": "ignore",
"NegativeEnergiesWarning": "ignore",
"LinestrengthCutoffWarning": "ignore",
"HighTemperatureWarning": "ignore",
})
sf.fetch_databank(
"hitran"
) # uses HITRAN: not really valid at this temperature, but runs on all machines without install
# sf.load_databank('HITEMP-CO2-DUNHAM') # to take a real advantage of abscoeff continuum, should calculate with HITEMP
sf._export_continuum = True # activate it
# Calculate one without pseudo-continuum
sf.params.pseudo_continuum_threshold = 0
s1 = sf.non_eq_spectrum(Tvib=2000, Trot=1000)
s1.name = "All lines resolved ({0}) ({1:.1f}s)".format(
s1.conditions["lines_calculated"], s1.conditions["calculation_time"])
assert s1.conditions["pseudo_continuum_threshold"] == 0
# Calculate one with pseudo-continuum
sf.params.pseudo_continuum_threshold = 0.05
s2 = sf.non_eq_spectrum(Tvib=2000, Trot=1000)
s2.name = "Semi-continuum + {0} lines ({1:.1f}s)".format(
s2.conditions["lines_calculated"], s2.conditions["calculation_time"])
assert s2.conditions["pseudo_continuum_threshold"] == 0.05
assert "abscoeff_continuum" in s2.get_vars()
assert "emisscoeff_continuum" in s2.get_vars()
# Plot
if plot:
plot_diff(
s1,
s2,
"radiance_noslit",
Iunit="µW/cm2/sr/nm",
nfig="test_noneq_continuum: diff",
)
plt.figure("test_noneq_continuum: show continuum").clear()
s2.plot("emisscoeff",
label=s2.name,
nfig="test_noneq_continuum: show continuum")
s2.plot(
"emisscoeff_continuum",
nfig="same",
label="Pseudo-continuum (aggreg. {0:g} lines)".format(
s2.conditions["lines_in_continuum"]),
force=True,
)
# Compare
res = get_residual(s1, s2, "abscoeff") + get_residual(s1, s2, "emisscoeff")
if verbose:
printm("residual:", res)
assert res < 5.2e-6
spectra_default = {}
spectra_DLM = {}
spectra_DLM_opt = {}
Nlines = [101, 1001, 10017, 100725, 1813040, 1813040]
plt.ion()
for N in Nlines:
spectra_default[N] = load_spec(
'../spec/spectra_default_[{0}].spec'.format(N), binary=True)
spectra_DLM_opt[N] = load_spec(
'../spec/spectra_DLM_opt[{0}].spec'.format(N), binary=True)
# %% Plot last spectra (opt)
fig, [ax0, ax1] = plot_diff(spectra_default[N], spectra_DLM_opt[N], 'abscoeff')
ax0.set_ylim((0, 0.5))
ax1.set_ylim((-0.005, 0.005))
axins = ax0.inset_axes([0.06, 0.3, 0.3, 0.4])
axins.ticklabel_format(useOffset=False, axis='x')
axins.tick_params(which='major', labelsize=14)
axins.get_yaxis().set_visible(False)
axins.plot(*spectra_default[N].get('abscoeff', wunit='cm-1'), color='k', lw=2)
axins.plot(*spectra_DLM_opt[N].get('abscoeff', wunit='cm-1'), color='r', lw=1)
axins.set_xlim((2200, 2205))
axins.set_ylim((0.0125, 0.32))
ax0.indicate_inset_zoom(axins)
fig.savefig('output/Fig6a.pdf')
