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 test_klarenaar_validation_case(verbose=True,
plot=False,
warnings=True,
*args,
**kwargs):
""" Reproduce the Klarenaar 2018 validation case, as given in the
[RADIS-2018]_ article.
References
----------
Klarenaar et al, "Time evolution of vibrational temperatures in a CO 2 glow
discharge measured with infrared absorption spectroscopy", doi 10.1088/1361-6595/aa902e,
and the references there in.
"""
setup_test_line_databases()
try:
# %% Data from Dang, adapted by Klarenaar
s_exp = Spectrum.from_txt(
getValidationCase(
join(
"test_CO2_3Tvib_vs_klarenaar_data",
"klarenaar_2017_digitized_data.csv",
)),
"transmittance_noslit",
waveunit="cm-1",
unit="I/I0",
delimiter=",",
name="Klarenaar 2017",
)
# %% Calculate Klarenaar test case conditions
sf = SpectrumFactory(
2284.2,
2284.6,
wstep=0.001, # cm-1
pressure=20 * 1e-3, # bar
db_use_cached=True,
cutoff=1e-25,
molecule="CO2",
isotope="1,2",
path_length=10, # cm-1
# warning! 10% in mass fraction -> less in mole fraction
mole_fraction=0.1 * 28.97 / 44.07,
broadening_max_width=1, # cm-1
medium="vacuum",
export_populations="vib",
)
sf.warnings["MissingSelfBroadeningWarning"] = "ignore"
# sf.load_databank('HITEMP-CO2-DUNHAM')
sf.load_databank("HITEMP-CO2-TEST")
# Calculate with Klarenaar fitted values
T12 = 517
T3 = 2641
Trot = 491
s = sf.non_eq_spectrum((T12, T12, T3),
Trot,
Ttrans=Trot,
vib_distribution="treanor",
name="RADIS")
if plot:
plot_diff(s, s_exp, "transmittance_noslit")
# plt.savefig('test_CO2_3Tvib_vs_klarenaar.png')
assert get_residual(s, s_exp, "transmittance_noslit",
ignore_nan=True) < 0.003
return True
except DatabankNotFound as err:
assert IgnoreMissingDatabase(err, __file__, warnings)
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import minimize
from os.path import join
# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------
# 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(
join('test_CO2_3Tvib_vs_klarenaar_data',
'klarenaar_2017_digitized_data.csv')),
'transmittance_noslit',
waveunit='cm-1',
unit='',
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
def test_compare_torch_CO2(verbose=True,
plot=False,
save=False,
warnings=True,
use_cache=True,
*args,
**kwargs):
''' Reproduce the plasma torch experiment of Packan 2003 in in atmospheric air
Notes
-----
Thresholds parameters are reduced for a faster calculation time. For instance:
- broadening_max_width should be 50 rather than 20
- cutoff should be 1e-27 rather than 1e-25
- wstep should be 0.01 or even 0.008 rather than 0.1
Performance:
- neq==0.9.20: Finished test_compare_torch_CO2 in 758.640324s
- neq==0.9.21: Finished test_compare_torch_CO2 in 672s
- neq==0.9.21*: (with ParallelFactory) Finished test_compare_torch_CO2 in 298s
- neq==0.9.22: (Parallel + continuum) Finished in 65s
RADIS 1.0.0 == neq 0.9.24
Reference
--------
Packan et al 2003 "Measurement and Modeling of OH, NO, and CO Infrared Radiation
at 3400 K", JTHT
'''
if plot: # Make sure matplotlib is interactive so that test are not stuck in pytest
plt.ion()
t0 = time()
try:
# %% Conditions
wlmin = 4100
wlmax = 4900
wmin = nm2cm(wlmax)
wmax = nm2cm(wlmin)
wstep = 0.1
# Load concentration profile
conds = pd.read_csv(getValidationCase(
'test_compare_torch_CO2_data/test_compare_torch_CO2_conditions_JTHT2003.dat'
),
comment='#',
delim_whitespace=True)
slab_width = 0.05 # cm, WARNING. Hardcoded (look up the table)
# %% Calculate slabs
# CO2
sf = ParallelFactory(
wmin,
wmax,
mole_fraction=None,
path_length=None,
molecule='CO2',
isotope='1,2',
parallel=False,
wstep=wstep,
db_use_cached=use_cache,
export_lines=False, # saves some memory
export_populations=False, # saves some memory
cutoff=1e-25,
pseudo_continuum_threshold=0.01,
Nprocs=cpu_count() - 1, # warning with memory if too many procs
broadening_max_width=20,
verbose=False)
sf.warnings['MissingSelfBroadeningWarning'] = 'ignore'
sf.warnings['NegativeEnergiesWarning'] = 'ignore'
# # Init database: only if we want to save all spectra being calculated
# (discarded for the moment)
# if use_cache:
# sf.init_database('test_compare_torch_CO2_SpectrumDatabase_HITEMP_1e25',
# add_info=['Tgas'])
sf.init_databank('HITEMP-CO2-DUNHAM',
load_energies=False) # saves some memory
# sf.init_databank('CDSD-4000')
# CO
sfco = ParallelFactory(
wmin,
wmax,
mole_fraction=None,
path_length=None,
molecule='CO',
isotope='1,2',
parallel=False,
wstep=wstep,
db_use_cached=use_cache,
export_lines=False, # saves some memory
export_populations=False, # saves some memory
cutoff=1e-25,
Nprocs=cpu_count() - 1,
broadening_max_width=20,
verbose=False)
sfco.warnings['MissingSelfBroadeningWarning'] = 'ignore'
# Init database: only if we want to save all spectra being calculated
# (discarded for the moment)
# if use_cache:
# sfco.init_database(
# 'test_compare_torch_CO_SpectrumDatabase_HITEMP_1e25', add_info=['Tgas'])
sfco.init_databank('HITEMP-CO-DUNHAM')
# Calculate all slabs
# .. CO2 at equilibrium
slabsco2 = sf.eq_spectrum(list(conds.T_K),
mole_fraction=list(conds.CO2),
path_length=slab_width)
# .. CO at equilibrium, but with non_eq to calculate PartitionFunctions instead of using
# ... tabulated ones (which are limited to 3000 K in HAPI)
slabsco = sfco.non_eq_spectrum(list(conds.T_K),
list(conds.T_K),
mole_fraction=list(conds.CO),
path_length=slab_width)
# Room absorption
with pytest.warns(
UserWarning
): # we expect a "using ParallelFactory for single case" warning
s0 = sf.eq_spectrum(Tgas=300,
mole_fraction=330e-6,
path_length=600)[0]
# Warning: This slab includes the CO2 emission from the 300 K air
# within the spectrometer. But experimentally it is substracted
# by there the chopper (this is corrected below)
# ... see RADIS Article for more details
# Add radiance for everyone if not calculated (ex: loaded from database)
for s in slabsco2 + slabsco + [s0]:
s.update()
# Merge CO + CO2 for each slab
slabstot = [MergeSlabs(s, sco) for (s, sco) in zip(slabsco2, slabsco)]
# %% Line-of-sight
# Solve ETR along line of sight
# --------
# two semi profile, + room absortion
line_of_sight = slabstot[1:][::-1] + slabstot + [s0]
stot = SerialSlabs(*line_of_sight)
# stot = SerialSlabs(*slabstot[1:][::-1], *slabstot, s0) # Python 3 syntax only
# Also calculate the contribution of pure CO
# ---------
s0tr = s0.copy() # transmittance only
s0tr.conditions['thermal_equilibrium'] = False
s0tr._q['radiance_noslit'] *= 0 # hack to remove CO2 emission
s0tr._q['emisscoeff'] *= 0 # hack to remove CO2 emission
line_of_sight = slabsco[1:][::-1] + slabsco + [s0tr]
sco = SerialSlabs(*line_of_sight)
# sco = SerialSlabs(*slabsco[1:][::-1], *slabsco, s0tr) # Python 3 syntax only
# Generate Slit
# ------
disp = 4 # dispersion conversion function (nm/mm)
s_in = 1 # entrance slit (mm)
s_out = 2.8 # exit slit (mm)
top = (s_out - s_in) * disp
base = (s_out + s_in) * disp
slit_function = (top, base) # (nm)
# Final plot unit
unit = 'µW/cm2/sr'
norm_by = 'max' # should be 'max' if unit ~ 'µW/cm2/sr',
# 'area' if unit ~ 'µW/cm2/sr/nm'
# Convolve with Slit
# -------
sco.apply_slit(slit_function,
unit='nm',
norm_by=norm_by,
shape='trapezoidal')
stot.apply_slit(slit_function,
unit='nm',
norm_by=norm_by,
shape='trapezoidal')
# Remove emission from within the spectrometer (substracted
# by the chopper experimentaly)
# -------
s0spectro = s0.copy()
s0spectro.rescale_path_length(75 * 4) # spectrometer length
s0spectro.apply_slit(slit_function,
unit='nm',
norm_by=norm_by,
shape='trapezoidal')
_, I0spectro = s0spectro.get('radiance', Iunit=unit)
wtot, Itot = stot.get('radiance', Iunit=unit)
stot_corr = experimental_spectrum(
wtot,
Itot - I0spectro, # hack to remove
# emission from within
# spectrometer
Iunit=unit,
conditions={'medium': 'air'})
# %% Compare with experiment data
# Plot experimental data
# ------
exp = pd.read_csv(getValidationCase(
'test_compare_torch_CO2_data/test_compare_torch_CO2_spectrum_JTHT2003.dat'
),
skiprows=5,
delim_whitespace=True)
exp.w /= 10 # Angstrom to nm
exp = exp[(exp.w > wlmin) & (exp.w < wlmax)]
sexp = experimental_spectrum(exp.w,
exp.I,
Iunit='mW/cm2/sr',
conditions={'medium': 'air'})
if plot:
sexp.plot('radiance',
wunit='nm',
Iunit=unit,
lw=2,
label='Packan 2003')
# Plot calculated
# ----------
stot.plot('radiance',
wunit='nm',
Iunit=unit,
nfig='same',
color='r',
ls='--',
label='All: CO$_2$+CO')
# Plot internal spectrometer emission
s0spectro.plot('radiance',
wunit='nm',
Iunit=unit,
nfig='same',
color='b',
label='CO$_2$ in Spectrometer')
stot_corr.plot('radiance',
wunit='nm',
Iunit=unit,
nfig='same',
color='r',
lw=2,
label='All-CO$_2$ in Spectro',
zorder=10)
sco.plot('radiance',
wunit='nm',
Iunit=unit,
nfig='same',
color='g',
ls='-',
label='CO')
plt.ylim((0, 9))
plt.legend(loc='upper right')
if save:
plt.savefig('test_compare_torch_CO2_brd20.png')
plt.savefig('test_compare_torch_CO2_brd20k.pdf')
assert get_residual(stot_corr, sexp, 'radiance') < 0.02
except DatabankNotFound as err:
assert IgnoreMissingDatabase(err, __file__, warnings)
if verbose:
print(('Finished test_compare_torch_CO2 in {0:.0f}s'.format(time() -
t0)))