{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.interpolate import interp1d\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from solcore.structure import Structure\n",
    "from solcore.absorption_calculator import calculate_rat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "E_eV = np.linspace(0.65, 4, 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def nk_convert(fname, energy):\n",
    "    \"\"\" Designed to handle nk data files\"\"\"\n",
    "\n",
    "    # Import data...\n",
    "    E_n, n, E_k, k = np.loadtxt(fname, delimiter=\",\", unpack=True)\n",
    "    print(\"File :: \" + fname + \" :: Imported Successfully!\")\n",
    "\n",
    "    # Interpolate data...\n",
    "    n_interp = interp1d(E_n, n, bounds_error=False, fill_value=(n[0], n[-1]))(energy)\n",
    "    k_interp = interp1d(E_k, k, bounds_error=False, fill_value=(k[0], k[-1]))(energy)\n",
    "    return (energy, n_interp, k_interp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load nk data using nk_convert function..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alinp_nk = nk_convert(\"../data/AlInP_nk.csv\", energy=E_eV)\n",
    "gainp_nk = nk_convert(\"../data/GaInP_nk.csv\", energy=E_eV)\n",
    "mgf_nk = nk_convert(\"../data/MgF_nk.csv\", energy=E_eV)\n",
    "sic_nk = nk_convert(\"../data/SiCx_nk.csv\", energy=E_eV)\n",
    "zns_nk = nk_convert(\"../data/ZnS_nk.csv\", energy=E_eV)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Build the optical stack..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stack = Structure([\n",
    "    [117, 1240 / E_eV, mgf_nk[1], mgf_nk[2]],\n",
    "    [80, 1240 / E_eV, sic_nk[1], sic_nk[2]],\n",
    "    [61, 1240 / E_eV, zns_nk[1], zns_nk[2]],\n",
    "    [25, 1240 / E_eV, alinp_nk[1], alinp_nk[2]],\n",
    "    [350000, 1240 / E_eV, gainp_nk[1], gainp_nk[2]]\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "angles = np.linspace(0, 80, 10)\n",
    "RAT_angles = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Calculate RAT ::\")\n",
    "for theta in angles:\n",
    "    print(\"Calculating at angle :: %4.1f deg\" % theta)\n",
    "    # Calculate RAT data...\n",
    "    rat_data = calculate_rat(stack, angle=theta, wavelength=1240 / E_eV)\n",
    "    RAT_angles.append((theta, rat_data[\"R\"], rat_data[\"A\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = plt.cm.jet(np.linspace(1, 0, len(RAT_angles)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax2 = plt.subplots(1, 1)\n",
    "\n",
    "for i, RAT in enumerate(RAT_angles):\n",
    "    ax2.plot(1240 / E_eV, RAT[1] * 100, ls=\"-\", color=colors[i], label=\"%4.1f$^\\circ$\" % RAT[0])\n",
    "    ax2.plot(1240 / E_eV, RAT[2] * 100, ls=\"--\", color=colors[i])\n",
    "\n",
    "ax2.set_ylim([0, 100])\n",
    "ax2.set_xlim([300, 1800])\n",
    "ax2.set_xlabel(\"Wavelength (nm)\")\n",
    "ax2.set_ylabel(\"Reflection and Transmission (%)\")\n",
    "ax2.legend(loc=5)\n",
    "ax2.text(0.05, 0.45, '(a)', transform=ax2.transAxes, fontsize=12)\n",
    "\n",
    "plt.tight_layout(w_pad=4)\n",
    "plt.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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