Using the TMM solver to calculate the reflection of a multilayered ARC
======================================================================

.. image:: RAT_of_ARC.png
   :width: 50%

- Required extra files, available in `Solcore's Github repository (Examples folder) <https://github.com/dalonsoa/solcore5>`_:

    - AlInP_nk.csv
    - GaInP_nk.csv
    - MgF_nk.csv
    - SiCx_nk.csv
    - ZnS_nk.csv

.. code-block:: Python

    from scipy.interpolate import interp1d
    import matplotlib.pyplot as plt
    import numpy as np

    from solcore.structure import Structure
    from solcore.absorption_calculator import calculate_rat

    E_eV = np.linspace(0.65, 4, 1000)


    def nk_convert(fname, energy):
        """ Designed to handle nk data files"""

        # Import data...
        E_n, n, E_k, k = np.loadtxt(fname, delimiter=",", unpack=True)
        print("File :: " + fname + " :: Imported Successfully!")

        # Interpolate data...
        n_interp = interp1d(E_n, n, bounds_error=False, fill_value=(n[0], n[-1]))(energy)
        k_interp = interp1d(E_k, k, bounds_error=False, fill_value=(k[0], k[-1]))(energy)

        return (energy, n_interp, k_interp)


    # Load nk data using nk_convert function...
    alinp_nk = nk_convert("AlInP_nk.csv", energy=E_eV)
    gainp_nk = nk_convert("GaInP_nk.csv", energy=E_eV)
    mgf_nk = nk_convert("MgF_nk.csv", energy=E_eV)
    sic_nk = nk_convert("SiCx_nk.csv", energy=E_eV)
    zns_nk = nk_convert("ZnS_nk.csv", energy=E_eV)

    # Build the optical stack...
    stack = Structure([
        [117, 1240 / E_eV, mgf_nk[1], mgf_nk[2]],
        [80, 1240 / E_eV, sic_nk[1], sic_nk[2]],
        [61, 1240 / E_eV, zns_nk[1], zns_nk[2]],
        [25, 1240 / E_eV, alinp_nk[1], alinp_nk[2]],
        [350000, 1240 / E_eV, gainp_nk[1], gainp_nk[2]]
    ])

    angles = np.linspace(0, 80, 10)
    RAT_angles = []

    print("Calculate RAT ::")
    for theta in angles:
        print("Calculating at angle :: %4.1f deg" % theta)
        # Calculate RAT data...
        rat_data = calculate_rat(stack, angle=theta, wavelength=1240 / E_eV)

        RAT_angles.append((theta, rat_data["R"], rat_data["A"]))

    colors = plt.cm.jet(np.linspace(1, 0, len(RAT_angles)))

    fig, ax2 = plt.subplots(1, 1)

    for i, RAT in enumerate(RAT_angles):
        ax2.plot(1240 / E_eV, RAT[1] * 100, ls="-", color=colors[i], label="%4.1f$^\circ$" % RAT[0])
        ax2.plot(1240 / E_eV, RAT[2] * 100, ls="--", color=colors[i])

    ax2.set_ylim([0, 100])
    ax2.set_xlim([300, 1800])
    ax2.set_xlabel("Wavelength (nm)")
    ax2.set_ylabel("Reflection and Transmission (%)")
    ax2.legend(loc=5)
    ax2.text(0.05, 0.45, '(a)', transform=ax2.transAxes, fontsize=12)

    plt.tight_layout(w_pad=4)
    plt.show()