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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RF Example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An example of using LayerLumos to simulate the Shielding Effectiveness(SE), demo here is a single Ag layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.constants import c\n",
    "from layerlumos.utils import load_material, interpolate_material, load_material_RF\n",
    "from layerlumos.layerlumos import stackrt, stackrt0\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "frequencies = np.linspace(8e9, 18e9, 100)  # Convert wavelengths to frequencies\n",
    "\n",
    "# Interpolate n and k values for SiO2 over the specified frequency range\n",
    "n_k_Ag = load_material_RF('Ag', frequencies)\n",
    "n_Ag = n_k_Ag[:, 1] + 1j*n_k_Ag[:, 2]  # Combine n and k into a complex refractive index\n",
    "\n",
    "# Define stack configuration\n",
    "n_air = np.ones_like(frequencies)  # Refractive index of air\n",
    "d_air = np.array([0])\n",
    "d_Ag = np.array([2e-8])  # Thickness of SiO2 layer in meters (e.g., 2 microns)\n",
    "\n",
    "# Stack refractive indices and thicknesses for air-SiO2-air\n",
    "n_stack = np.vstack([n_air, n_Ag, n_air]).T  # Transpose to match expected shape (Nlayers x Nfreq)\n",
    "d_stack = np.vstack([d_air, d_Ag, d_air])  # No frequency dependence on thickness\n",
    "\n",
    "# Calculate R and T over the frequency (wavelength) range\n",
    "R_TE, T_TE, R_TM, T_TM = stackrt0(n_stack, d_stack, frequencies)\n",
    "\n",
    "# Calculate average R and T\n",
    "SE_TE = -10 * np.log10(T_TE)\n",
    "SE_TM = -10 * np.log10(T_TM)\n",
    "SE = (SE_TE + SE_TM) / 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "47.49071678079014\n"
     ]
    }
   ],
   "source": [
    "# Get the Sheilding Efficiency\n",
    "print(np.mean(SE))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can try multiple metal layer in the structure, considering Fabry–Pérot effect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Interpolate n and k values for SiO2 over the specified frequency range\n",
    "n_k_Ag = load_material_RF('Ag', frequencies)\n",
    "n_Ag = n_k_Ag[:, 1] + 1j*n_k_Ag[:, 2]  # Combine n and k into a complex refractive index\n",
    "\n",
    "n_k_SiO2 = load_material_RF('SiO2', frequencies)\n",
    "n_SiO2 = n_k_SiO2[:, 1] + 1j*n_k_SiO2[:, 2]  # Combine n and k into a complex refractive index\n",
    "\n",
    "\n",
    "# Define stack configuration\n",
    "n_air = np.ones_like(frequencies)  # Refractive index of air\n",
    "d_air = np.array([0])\n",
    "d_SiO2 = np.array([2e-4])\n",
    "d_Ag = np.array([1e-8])  # Thickness of SiO2 layer in meters (e.g., 2 microns)\n",
    "\n",
    "# Stack refractive indices and thicknesses for air-SiO2-air\n",
    "n_stack = np.vstack([n_air, n_Ag, n_SiO2, n_Ag, n_air]).T  # Transpose to match expected shape (Nlayers x Nfreq)\n",
    "d_stack = np.vstack([d_air, d_Ag, d_SiO2, d_Ag, d_air])  # No frequency dependence on thickness\n",
    "\n",
    "# Calculate R and T over the frequency (wavelength) range\n",
    "R_TE, T_TE, R_TM, T_TM = stackrt0(n_stack, d_stack, frequencies)\n",
    "\n",
    "# Calculate average R and T\n",
    "SE_TE = -10 * np.log10(T_TE)\n",
    "SE_TM = -10 * np.log10(T_TM)\n",
    "SE = (SE_TE + SE_TM) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "63.574706852860174\n"
     ]
    }
   ],
   "source": [
    "# Get the Sheilding Efficiency\n",
    "print(np.mean(SE))"
   ]
  }
 ],
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