Spring release 🌱

Pull request details : #472

🔬 (Physics) Features

#462 adding GEISA database support by @TranHuuNhatHuy

s = calc_spectrum(1000 / u.cm, 10000 / u.cm,
                   molecule="CH4",
                   mole_fraction=1900e-9,
                   isotope='1,2,3',
                   wstep='auto',
                   pressure=1.01325 * u.bar,
                   Tgas=296 * u.K,
                   path_length=100 * u.cm,
                    databank='geisa',    # GEISA-2020 
                   verbose=False,
                   export_lines=True,
                   )
import matplotlib.pyplot as plt
plt.figure(figsize=(12,6))
s.plot("xsection", yscale='log', nfig='same')
s.line_survey()

GEISA database can be accessed as a Pandas DataFrame using fetch_geisa() :

from radis.io.geisa import fetch_geisa
df = fetch_geisa("H2O")
print(df)

                 wav           int  airbrd  ...  ierrT Tdpnself ierrU
0           0.052583  2.154000e-33  0.0923  ...    0.0    -0.99 -0.99
1           0.181997  2.486000e-35  0.0399  ...    0.0    -0.99 -0.99
2           0.184013  8.470000e-36  0.0399  ...    0.0    -0.99 -0.99
3           0.187637  5.255000e-29  0.0900  ...    0.0    -0.99 -0.99
4           0.363402  2.041100e-33  0.0800  ...    0.0    -0.99 -0.99
             ...           ...     ...  ...    ...      ...   ...
362217  25332.871900  8.100000e-28  0.1056  ...    0.0    -0.99 -0.99
362218  25333.215510  1.560000e-28  0.1078  ...    0.0    -0.99 -0.99
362219  25334.143900  4.750000e-28  0.0905  ...    0.0    -0.99 -0.99
362220  25335.071700  8.260000e-28  0.1102  ...    0.0    -0.99 -0.99
362221  25336.948790  7.170000e-29  0.1125  ...    0.0    -0.99 -0.99

[362222 rows x 31 columns]

⚙️User-interface

#467 radiance & emisscoeff units are now consistent with waverange unit ; i.e. plotting in cm-1 will yield a default radiance in ~mW/cm2/sr/cm-1 while plotting in nm will yield a default radiance in ~mW/cm2/sr/nm @AllanHOlesenBW (major refactor under the hood)
#448 normalize options
#471 line-survey works for multiple molecules

from radis import calc_spectrum
import astropy.units as u

s4 = calc_spectrum(1950 / u.cm, 1980 / u.cm,
                   mole_fraction={'CH4':1900e-9, 'CO2':400e-6},
                    isotope='1,2,3',
                    pressure=1.01325 * u.bar,
                    Tgas=296 * u.K,
                    path_length=100 * u.cm,
                    databank='geisa',
                    verbose=False,
                    export_lines=True)

s4.line_survey(overlay='abscoeff', barwidth=0.001)