radis/spectro101

Tutorials for molecular spectroscopy

spectro101's Issues

TODO : generate Sphinx website gallery with Notebook examples

Idea : let's have a stand-alone website to add some Radis-based Tutorials & Fun-Facts on Spectroscopy

• set-up basic website. For convenience we could start from the radis/Fitroom website (https://github.com/radis/fitroom/tree/main/docs) ; also based on Radis

• Host it on the ReadTheDocs pages or Github pages?

• Use nbsphinx : https://nbsphinx.readthedocs.io/en/0.6.1/subdir/gallery.html

Todo : make it work on RADIS-Lab

https://radis.github.io/radis-lab/

(Note : would have to separate production from examples on radis-lab for fast editing & loading, see radis/radis-lab#13 )

TODO : add Fun Fact #1 : The sun would not be visible if the 4.2 µm CO2 lineshape was truely lorentzian

Add a notebook based on this (working) Python example :

"""

Fun Facts About Spectroscopy
----------------------------

# The sun would not be visible if the 4.2 µm CO2 lineshape was truely lorentzian
"""


from radis import calc_spectrum
import matplotlib.pyplot as plt
import astropy.units as u

s = calc_spectrum(wavelength_min=0.3*u.um, wavelength_max=6*u.um,
                  molecule='CO2',
                  isotope='1,2,3',
                  pressure=1.01325,   # bar
                  truncation=None, 
                  Tgas=300,           # K
                  mole_fraction=400e-6,
                  cutoff=0,
                  databank='hitran',  # or use 'hitemp'
                  broadening_method="fft"
                  )

# note : the calculation is quite long (~190s on my laptop) because the FFT
# method used is not optimized for very large ranges

#%% Plot
s.plot('abscoeff', wunit='nm', yscale='log')
plt.axvspan(300, 700, alpha=0.3) # visible spectrum

# we get an absorption coefficient of about ~0.5 cm-1 in the visible range

# %% 
# which means that the sky would be >99% more opaque for a layer of only ~ 10 cm 
# (exp(-5) = 0.006 )

s.rescale_path_length(10).plot('transmittance_noslit', wunit='nm')
plt.axvspan(300, 700, alpha=0.3) # visible spectrum
plt.ylim((0, 1.1))
# plt.ylim((0, 1.1))