CIA coefficient
===============

.. code:: ipython3

    from exojax.utils.grids import wavenumber_grid
    
    nus, wav, res = wavenumber_grid(5000, 50000, 1000, unit="AA")
    from exojax.spec import contdb
    
    cdbH2H2 = contdb.CdbCIA('.database/H2-H2_2011.cia', nus)



.. parsed-literal::

    xsmode assumes ESLOG in wavenumber space: mode=lpf
    H2-H2


.. parsed-literal::

    /home/kawahara/exojax/src/exojax/utils/grids.py:123: UserWarning: Resolution may be too small. R=433.86018742134854
      warnings.warn('Resolution may be too small. R=' + str(resolution),


logacia can provide an absorption coeffcient as a function of
temperature

.. code:: ipython3

    from exojax.spec.hitrancia import logacia
    import jax.numpy as jnp
    
    Tfix = jnp.array([1000.0, 1300.0, 1600.0])
    lc = logacia(Tfix, nus, cdbH2H2.nucia, cdbH2H2.tcia, cdbH2H2.logac)


plotting…

.. code:: ipython3

    import matplotlib.pyplot as plt
    
    plt.style.use('bmh')
    for i in range(0, len(Tfix)):
        plt.plot(wav[::-1], lc[i, :], lw=1, label=str(int(Tfix[i])) + " K")
    plt.axvspan(22876.0, 23010.0, alpha=0.3, color="green")
    plt.xlabel("wavelength ($\\AA$)")
    plt.ylabel("absorption coefficient ($cm^5$)")
    plt.legend()
    plt.savefig("cia.png")



.. image:: CIA_opacity_files/CIA_opacity_5_0.png


.. code:: ipython3

    #max value
    import numpy as np
    1.e8 / nus[np.argmax(lc[1, :])]





.. parsed-literal::

    23858.80474469375