{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hard Targeting for scanning Lidar North allignment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "ForWind Oldenburg\n",
    "Version 1.0\n",
    "\n",
    "Contributing author: Andreas Rott\n",
    "\n",
    "\n",
    "To understand the calculations and methods presented in this notebook it is highly recommended to read the corresponding publication: \n",
    "Rott, A., Schneemann, J., Theuer, F., Trujillo Quintero, J. J., and Kühn, M.: Alignment of scanning lidars in offshore wind farms, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2021-62, in review, 2021.\n",
    "\n",
    "Executed with Python 3.8.12\n",
    "\n",
    "## Brief description\n",
    "Code to calculate the North offset of a scanning wind lidar e.g. in an offshore location.\n",
    "The lidar needs to measure in an area with hard targets like wind turbines or light houses with known locations.\n",
    "The hard targets appear in the carrier to noise ratio (CNR) in the lidar data with a high backscatter.\n",
    "\n",
    "To adapt this script to your specific location you need to give the file locations of\n",
    "- a file containing the coordinates of the measured hard targets in a cartesian coordinate system (e.g. UTM)\n",
    "- a data file with the hard target lidar scans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import minimize \n",
    "from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes,mark_inset\n",
    "from scipy import signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "HardTargets_file_path = 'https://zenodo.org/record/5654866/files/HardTargets_coordinates_GTI.csv'\n",
    "HardTarget_Scan_path = 'https://zenodo.org/record/5654866/files/HT_scans_GTI.zip'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load hard target coordinates and Lidar location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22d4ba135e0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load Turbine Coordinates\n",
    "## Choose your file containing hard target cartesian coordinates here, unit: [m]\n",
    "## please make sure that the columns of the coordinates are named 'x' and 'y'\n",
    "\n",
    "HardTargets = pd.read_csv(HardTargets_file_path,index_col=0)\n",
    "\n",
    "## Set the location of your Lidar here using the cartesian coordinate system. In this example case the turbine was located at the Turbine 58 i.e. x=HardTargets.x[57], y = HardTargets.y[57].\n",
    "\n",
    "LidarLocation = pd.DataFrame({'x':HardTargets.x[57], 'y':HardTargets.y[57]}, index=[0])\n",
    "\n",
    "## Set the initial guess for your lidar orientation (deviation from North direction clockwise)\n",
    "\n",
    "initial_guess_Lidar_orientation = 170\n",
    "\n",
    "## Set the location of your lidar data here. The columns 'cnr', 'range' and 'azi' are used. Please make sure that all scans were performed with a scanning elevation of 0 deg.\n",
    "\n",
    "Lidar = pd.read_pickle(HardTarget_Scan_path)\n",
    "\n",
    "# Plot Hard targets and lidar locations\n",
    "fontsize = 20 # set fontsize for plot\n",
    "fig,ax = plt.subplots(figsize=(12,12))\n",
    "ax.scatter(HardTargets.x-LidarLocation.x[0],HardTargets.y-LidarLocation.y[0], s=500, marker='1', label='Hard Targets')\n",
    "ax.scatter(0,0, c='r', s=300, marker='x', label='Lidar location')\n",
    "ax.set_aspect('equal')\n",
    "ax.set_xlabel('Easting, $x\\ [\\mathrm{m}]$', fontsize=fontsize)\n",
    "ax.set_ylabel('Northing, $y\\ [\\mathrm{m}]$', fontsize=fontsize)\n",
    "ax.tick_params(axis='both', which='major', labelsize=fontsize)\n",
    "ax.grid(True)\n",
    "ax.legend(fontsize=fontsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Identify Hard Targets in lidar data via a cnr threshold\n",
    "# Transform azi and range to x and y with initial guess of the misalignment\n",
    "\n",
    "Lidar['x'] = np.sin((Lidar.azi+initial_guess_Lidar_orientation)*np.pi/180)*Lidar.range\n",
    "Lidar['y'] = np.cos((Lidar.azi+initial_guess_Lidar_orientation)*np.pi/180)*Lidar.range\n",
    "\n",
    "## Select hard targets by cnr threshold. As in the example below you can choose the threshold for different range intervals separately, if needed for close and distant hard targets in one run\n",
    "# id_ht = ((Lidar.cnr>5) & (Lidar.range <=4000)) | ((Lidar.cnr>-5) & (Lidar.range >4000) & (Lidar.range <=9000))\n",
    "id_ht = (Lidar.cnr>5) & (Lidar.range <7000) &(Lidar.y>-7/6*Lidar.x-200)\n",
    "\n",
    "# If needed, you can separate non fixed hard targets like ships manually here. Further you can exclude data in sectors or ranges. Just exclude them from the boolian variable id_ht.\n",
    "# Example:\n",
    "# id_ht = id_ht & (Lidar.y>0)\n",
    "# id_ht = id_ht & (Lidar.y<0)\n",
    "# id_ht = id_ht & (Lidar.range<1000)\n",
    "\n",
    "# Plot hard target range gates with initial guess over the turbines\n",
    "fig,ax = plt.subplots(figsize=(12,12))\n",
    "ax.scatter(HardTargets.x-LidarLocation.x[0],HardTargets.y-LidarLocation.y[0], s=500, marker='1', label='Hard Targets')\n",
    "ax.scatter(0,0, c='r', s=300, marker='x', label='Lidar location')\n",
    "ax.scatter(Lidar[id_ht].x, Lidar[id_ht].y, c='C1', s=25, marker='o', zorder=1, label='Hard target range gates')\n",
    "\n",
    "ax.set_aspect('equal')\n",
    "ax.set_xlabel('Easting, $x\\ [\\mathrm{m}]$', fontsize=fontsize)\n",
    "ax.set_ylabel('Northing, $y\\ [\\mathrm{m}]$', fontsize=fontsize)\n",
    "ax.tick_params(axis='both', which='major', labelsize=fontsize)\n",
    "ax.grid(True)\n",
    "ax.legend(fontsize=fontsize)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Define inputs for cost function from lidar data\n",
    "ht_azi = Lidar.azi[id_ht]\n",
    "ht_range = Lidar.range[id_ht]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define cost function for optimization\n",
    "def cost_function(params, ht_azi=ht_azi, ht_range=ht_range, HardTargets=HardTargets, show_plot=0):\n",
    "    x_offset = params[0]\n",
    "    y_offset = params[1]\n",
    "    azi_offset = params[2]\n",
    "    t_x = np.expand_dims(HardTargets.x.values, axis=1)\n",
    "    t_y = np.expand_dims(HardTargets.y.values, axis=1)\n",
    "    ht_x = np.array(np.sin((ht_azi+azi_offset)*np.pi/180)*ht_range+x_offset)\n",
    "    ht_y = np.array(np.cos((ht_azi+azi_offset)*np.pi/180)*ht_range+y_offset)\n",
    "    cost = np.sqrt((ht_x - t_x)**2 + (ht_y - t_y)**2)\n",
    "    cost = np.min(cost, axis=0)\n",
    "    if show_plot:\n",
    "        fig,ax = plt.subplots(figsize=(16,16))\n",
    "        ax.scatter(t_x.squeeze()-LidarLocation.x.values, t_y.squeeze()-LidarLocation.y.values, s=500, marker='1', label='Hard Targets')\n",
    "        ax.scatter(ht_x-LidarLocation.x[0], ht_y-LidarLocation.y[0], s=25, marker='o', zorder=1, label='Hard target range gates')\n",
    "        ax.scatter(0,0, c='r', s=300, marker='x', label='Lidar location')        \n",
    "        ax.set_aspect('equal')\n",
    "        ax.set_xlabel('Easting, $x\\ [\\mathrm{m}]$', fontsize=fontsize)\n",
    "        ax.set_ylabel('Northing, $y\\ [\\mathrm{m}]$', fontsize=fontsize)\n",
    "        ax.tick_params(axis='both', which='major', labelsize=fontsize)\n",
    "        ax.grid(True)\n",
    "        ax.legend(fontsize=fontsize)\n",
    "    return np.linalg.norm(cost)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_offset = -3.9\n",
      "y_offset = -4.3\n",
      "North_offset = 171.65°\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x1152 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "initial_params = [LidarLocation.x[0],LidarLocation.y[0], initial_guess_Lidar_orientation]\n",
    "result = minimize(cost_function,initial_params,method='Nelder-Mead')\n",
    "# print(result)\n",
    "cost_function(result.x,show_plot=1)\n",
    "print('x_offset = {:2.2}'.format(result.x[0]-LidarLocation.x[0]) )\n",
    "print('y_offset = {:2.2}'.format(result.x[1]-LidarLocation.y[0]) )\n",
    "print('North_offset = {:3.2f}\\N{DEGREE SIGN}'.format(result.x[2]) )"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "8ad08f8f50e91180a9dcfef1ac7f78584c9e111444e7578f1d150ce9815081fd"
  },
  "kernelspec": {
   "display_name": "Python 3.9.5 64-bit ('spyder': conda)",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}