{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Phase Scan Effect on Antenna Voltage Unbalance\n",
    "In this notebook we explore the effect of a phase scan over the voltage unbalance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import skrf as rf\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "# WEST ICRH Antenna package\n",
    "import sys; sys.path.append('..')\n",
    "from west_ic_antenna import WestIcrhAntenna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# nicer plot\n",
    "rf.stylely()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's use a TOPICA simulation of the WEST front face in a \"L-mode plasma\" at 55 MHz: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "freq = rf.Frequency(start=50, stop=60, npoints=1001, unit='MHz')\n",
    "plasma_TOPICA = '../west_ic_antenna/data/Sparameters/front_faces/TOPICA/S_TSproto12_55MHz_Hmode_LAD6-2.5cm.s4p'\n",
    "\n",
    "antenna = WestIcrhAntenna(frequency=freq, front_face=plasma_TOPICA)\n",
    "print(f'Optimal coupling resistance expected:', antenna.front_face_Rc().max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we match the antenna, both sides at the same time to operate the antenna at 55 MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# antenna excitation to match for\n",
    "power = [1, 1]  # W\n",
    "phase = [0, np.pi]  # dipole\n",
    "\n",
    "Cs = antenna.match_both_sides(f_match=55e6, power=power, phase=phase, \n",
    "                              solution_number=1, verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize how good the antenna is matched for the target frequency, by looking to the active S parameters (ie. taking into account the antenna excitation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s_act = antenna.s_act(power=power, phase=phase, Cs=Cs)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(antenna.f_scaled, 20*np.log10(np.abs(s_act)), lw=2)\n",
    "ax.set_xlabel('Frequency [MHz]')\n",
    "ax.set_ylabel('Sact [dB]')\n",
    "ax.legend(('Left side', 'Right side'))\n",
    "ax.axvline(55, ls='--', color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that the antenna is perfeclty matched, let's see how the voltages evolve with frequency. At the match frequency, the voltages (and currents) get very close: the antenna is balanced."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(antenna.f_scaled, np.abs(antenna.voltages(power, phase, Cs)), lw=2)\n",
    "ax.axvline(55, ls='--', color='gray')\n",
    "ax.set_xlabel('Frequency [MHz]')\n",
    "ax.set_ylabel('Voltage [V]')\n",
    "ax.legend(('V1', 'V2', 'V3', 'V4'), ncol=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the antenna voltages are not perfectly balanced at the match point, which is expected due to the intercouplings: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, (ax1,ax2) = plt.subplots(2, 1, sharex=True)\n",
    "ax1.plot(antenna.f_scaled, np.abs(antenna.voltages(power, phase, Cs)), lw=2)\n",
    "[a.axvline(55, ls='--', color='gray') for a in (ax1,ax2)]\n",
    "ax2.set_xlabel('Frequency [MHz]')\n",
    "ax1.set_ylabel('Voltage [V]')\n",
    "ax1.legend(('V1', 'V2', 'V3', 'V4'), ncol=4)\n",
    "ax1.set_xlim(54.7, 55.3)\n",
    "ax1.set_ylim(25, 37)\n",
    "ax2.plot(antenna.f_scaled, 20*np.log10(np.abs(s_act)), lw=2)\n",
    "fig.subplots_adjust(hspace=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " So let's see how the voltages evolve at the match frequency when we sweep the phase shift between sides:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "power = [1e6, 1e6]  # 1 MW each side\n",
    "toroidal_phases = np.deg2rad(np.linspace(start=0, stop=360, num=36))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "antenna_single_freq = WestIcrhAntenna(frequency=rf.Frequency(55, 55, 1, unit='MHz'),\n",
    "                                     front_face=plasma_TOPICA, Cs=Cs) \n",
    "\n",
    "voltages, currents, Rcs = [], [], []\n",
    "for toroidal_phase in tqdm(toroidal_phases):\n",
    "    voltages.append(antenna_single_freq.voltages(power, phase=[0, toroidal_phase]))\n",
    "    currents.append(antenna_single_freq.voltages(power, phase=[0, toroidal_phase]))\n",
    "    Rcs.append(antenna_single_freq.Rc_WEST(power, phase=[0, toroidal_phase]))\n",
    "voltages = np.array(voltages).squeeze()\n",
    "currents = np.array(currents).squeeze()\n",
    "Rcs = np.array(Rcs).squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export data\n",
    "np.savetxt('voltages_vs_phase.csv', \n",
    "           np.c_[np.rad2deg(toroidal_phases), np.abs(voltages)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(np.rad2deg(toroidal_phases), np.abs(voltages)/1e3, lw=2)\n",
    "ax.axvline(180, ls='--', color='gray')\n",
    "ax.set_xlabel('Toroidal Phase [deg]')\n",
    "ax.set_ylabel('Voltage [kV]')\n",
    "ax.legend(('V1', 'V2', 'V3', 'V4'), ncol=4)\n",
    "ax.set_ylim(0,50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The phase sweep generates voltage (or currents) unbalance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The voltage probe toroidal phase difference is also slightly affected in this case:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(np.rad2deg(toroidal_phases), np.rad2deg(np.angle(voltages[:,2]) - np.angle(voltages[:,0]))%360, lw=2)\n",
    "ax.plot(np.rad2deg(toroidal_phases), np.rad2deg(np.angle(voltages[:,3]) - np.angle(voltages[:,1]))%360, lw=2)\n",
    "ax.plot(np.rad2deg(toroidal_phases), np.rad2deg(toroidal_phases), color='k', ls='--')\n",
    "ax.axvline(180, ls='--', color='gray')\n",
    "ax.set_xlabel('Toroidal Phase [deg]')\n",
    "ax.set_ylabel('Phase [deg]')\n",
    "ax.legend(('$\\Delta  \\phi$ $V_3-V_1$', '$\\Delta  \\phi$ $V_4-V_2$'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Coupling resistance, which is deduced from the currents, is of course also affected:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(np.rad2deg(toroidal_phases), Rcs, lw=2)\n",
    "ax.axvline(180, ls='--', color='gray')\n",
    "ax.set_xlabel('Toroidal Phase [deg]')\n",
    "ax.set_ylabel('Coupling Resistances [Ohm]')\n",
    "ax.legend(('Left', 'Right'), ncol=4)\n",
    "ax.set_ylim(0,1.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.core.display import HTML\n",
    "def _set_css_style(css_file_path):\n",
    "    \"\"\"\n",
    "    Read the custom CSS file and load it into Jupyter\n",
    "    Pass the file path to the CSS file\n",
    "    \"\"\"\n",
    "    styles = open(css_file_path, \"r\").read()\n",
    "    s = '<style>%s</style>' % styles\n",
    "    return HTML(s)\n",
    "\n",
    "_set_css_style('custom.css')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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