example_plotfluxrope.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e03ee688",
   "metadata": {},
   "source": [
    "# Example Notebook for plotting a fluxrope"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "318d72a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n",
      "0.12.2\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "\n",
    "%autoreload 2\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import datetime as datetime\n",
    "from datetime import timedelta\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "import copy as cp\n",
    "\n",
    "import py3dcore_h4c as py3dcore_h4c\n",
    "\n",
    "import py3dcore_h4c.fluxplot as fp\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "print(sns.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6445d79d",
   "metadata": {},
   "source": [
    "## simple speed calculation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "536dc050",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CME speed STEREO-A 1673.148148148148\n"
     ]
    }
   ],
   "source": [
    "#cor2 fov\n",
    "\n",
    "r1=13*695000\n",
    "\n",
    "\n",
    "#time in minutes from COR2 inner to outer\n",
    "t1=90*60\n",
    "\n",
    "\n",
    "speed=r1/t1\n",
    "\n",
    "print('CME speed STEREO-A',speed)\n",
    "\n",
    "\n",
    "#LASCO"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c97542a5",
   "metadata": {},
   "source": [
    "## ICMECAT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bdd1c8fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ICMECAT events near 1 AU 856\n"
     ]
    }
   ],
   "source": [
    "url='https://helioforecast.space/static/sync/icmecat/HELIO4CAST_ICMECAT_v21.csv'\n",
    "ic=pd.read_csv(url)\n",
    "ic=ic.drop(columns='Unnamed: 0') #drop an extra index column\n",
    "\n",
    "iwin=np.where(ic.sc_insitu=='Wind')[0]\n",
    "ista=np.where(ic.sc_insitu=='STEREO-A')[0]\n",
    "istb=np.where(ic.sc_insitu=='STEREO-B')[0]\n",
    "\n",
    "i1au=np.sort(np.hstack([iwin,ista,istb]))\n",
    "print('ICMECAT events near 1 AU',len(i1au))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4748eae",
   "metadata": {},
   "source": [
    "## py3DCORE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6bdb36fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "t_launch = datetime.datetime(2022, 9, 5, 18, 45, 0)\n",
    "\n",
    "#2022 Sep 5: 15 solar radii at 18:45 UT (PSP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7960c6e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "iparams_arr = np.array([[\n",
    "    0,      # time offset\n",
    "    -175,    # l_1 (longitude) HEEQ\n",
    "    -9.5,    # l_2 (latitude)\n",
    "    6,      # o (inclination, orientation)\n",
    "    0.35,   # d_1au (frontal width at 1AU)\n",
    "    1.2,   # delta (cross-section aspect ratio)\n",
    "    15,      # r_0 (initialization distance in solar radii)\n",
    "    1690,    # v_0 (initial velocty in)\n",
    "    146,      # t factor (magnetic field twist)\n",
    "    1.14,      # expansion factor (fixed)\n",
    "    1.64,     # magnetic field decay rate (fixed)\n",
    "    25,     # b_1au (magnetic field strength at 1au)\n",
    "    0.56,    # Gamma (solar wind drag coefficient)\n",
    "    579    # v_sw (solar wind speed)\n",
    "]], dtype=np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4eeb90b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "overwrite = {\n",
    "    \"cme_longitude\": {\n",
    "            \"maximum\": 180,\n",
    "            \"minimum\": 170\n",
    "        },\n",
    "    \"cme_latitude\": {\n",
    "            \"maximum\": -9,\n",
    "            \"minimum\": -10\n",
    "        },\n",
    "    \"cme_inclination\" :{\n",
    "            \"maximum\": 6.5,\n",
    "            \"minimum\": 5.5\n",
    "        },\n",
    "    \"cme_diameter_1au\" :{\n",
    "            \"maximum\": 0.4,\n",
    "            \"minimum\": 0.3\n",
    "        },\n",
    "    \"cme_aspect_ratio\": {\n",
    "            \"maximum\": 1.5,\n",
    "            \"minimum\": 1\n",
    "        },\n",
    "    \"cme_launch_radius\": {\n",
    "            \"maximum\": 15.5,\n",
    "            \"minimum\": 14.5\n",
    "        },\n",
    "    \"cme_launch_velocity\": {\n",
    "            \"maximum\": 1750,\n",
    "            \"minimum\": 1650\n",
    "        },\n",
    "    \"t_factor\": {\n",
    "            \"maximum\": 150,\n",
    "            \"minimum\": 140\n",
    "        },\n",
    "    \"magnetic_field_strength_1au\": {\n",
    "            \"maximum\": 26,\n",
    "            \"minimum\": 24\n",
    "        },\n",
    "    \"background_drag\": {\n",
    "            \"maximum\": 0.6,\n",
    "            \"minimum\": 0.5\n",
    "        },\n",
    "    \"background_velocity\": {\n",
    "            \"maximum\": 625,\n",
    "            \"minimum\": 550\n",
    "        },\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7c5983d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 1#number of runs\n",
    "\n",
    "#we initialize model for 1 run with default params\n",
    "\n",
    "model_obj = py3dcore_h4c.ToroidalModel(t_launch, n, iparams=overwrite)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d690fcca",
   "metadata": {},
   "source": [
    "    Model Parameters\n",
    "    ================\n",
    "        For this specific model there are a total of 14 initial parameters which are as follows:\n",
    "        0: t_i          time offset\n",
    "        1: lon          longitude\n",
    "        2: lat          latitude\n",
    "        3: inc          inclination\n",
    "\n",
    "        4: dia          cross section diameter at 1 AU\n",
    "        5: delta        cross section aspect ratio\n",
    "\n",
    "        6: r0           initial cme radius\n",
    "        7: v0           initial cme velocity\n",
    "        8: T            T factor (related to the twist)\n",
    "\n",
    "        9: n_a          expansion rate\n",
    "        10: n_b         magnetic field decay rate\n",
    "\n",
    "        11: b           magnetic field strength at center at 1AU\n",
    "        12: bg_d        solar wind background drag coefficient\n",
    "        13: bg_v        solar wind background speed\n",
    "\n",
    "        There are 4 state parameters which are as follows:\n",
    "        0: v_t          current velocity\n",
    "        1: rho_0        torus major radius\n",
    "        2: rho_1        torus minor radius\n",
    "        3: b_t          magnetic field strength at center"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9d07e56d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# after the model has been initialized, we generate a set of random initial parameters according to the table above\n",
    "\n",
    "model_obj.generator()\n",
    "#model_obj.update_iparams(iparams_arr, seed=42)\n",
    "\n",
    "\n",
    "#measurement times \n",
    "tm0 =  datetime.datetime(2022, 9, 7, 8)\n",
    "# tm0 =  t_launch + datetime.timedelta(days=1)\n",
    "tm1 =  t_launch + datetime.timedelta(days=1.5)\n",
    "tm2 =  t_launch + datetime.timedelta(days=3.5)\n",
    "\n",
    "\n",
    "#colors for 3dplots\n",
    "\n",
    "c0 = 'mediumseagreen'\n",
    "c1 = \"xkcd:red\"\n",
    "c2 = \"xkcd:blue\"\n",
    "\n",
    "\n",
    "#colors for components in plots\n",
    "cbt = \"xkcd:black\"\n",
    "cbx = \"xkcd:magenta\"\n",
    "cby = \"xkcd:orange\"\n",
    "cbz = \"xkcd:azure\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c7b9496d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.689, 150., 0.)\n",
      "(0.064, -175., 0.)\n",
      "(1., 0., 0.)\n"
     ]
    }
   ],
   "source": [
    "############# define synthetic satellite positions - semi-circle at 0.689 AU (SolO), from -90 to +90 longitude\n",
    "\n",
    "lonstart = -180\n",
    "lonstep = 5\n",
    "lonend = 180\n",
    "\n",
    "lonend = lonend + lonstep\n",
    "satpos = np.zeros(len(np.arange(lonstart,lonend,lonstep)),dtype=[('r',float),('lon', float),('lat', float)])\n",
    "#convert to recarray\n",
    "satpos = satpos.view(np.recarray)  \n",
    "\n",
    "##### set position\n",
    "satpos.r = 0.689\n",
    "satpos.lon = np.arange(lonstart,lonend,lonstep)\n",
    "satpos.lat = 0.0\n",
    "\n",
    "print(satpos[66])\n",
    "\n",
    "#print(satpos.r, satpos.lon)    \n",
    "\n",
    "# another satpos definition \n",
    "satpos2=cp.deepcopy(satpos)\n",
    "satpos2.r = 0.064\n",
    "\n",
    "print(satpos2[1])\n",
    "\n",
    "# another satpos definition \n",
    "satpos3=cp.deepcopy(satpos)\n",
    "satpos3.r = 1\n",
    "\n",
    "print(satpos3[36])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad312361",
   "metadata": {},
   "source": [
    "## plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c1dc0455",
   "metadata": {},
   "outputs": [],
   "source": [
    "#model_obj.iparams_arr[0][:]\n",
    "model_obj.iparams_arr[0][8] = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9ce39701",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERROR\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 840x630 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"talk\")     \n",
    "\n",
    "sns.set_style(\"ticks\",{'grid.linestyle': '--'})\n",
    "fsize=15\n",
    "\n",
    "fig=plt.figure(1,figsize=(12,9),dpi=70)\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "fp.plot_configure(ax, view_azim=0, view_elev=90, view_radius=0.8)\n",
    "\n",
    "fp.plot_3dcore(ax, model_obj, tm1, color=c2)\n",
    "fp.plot_3dcore_field(ax, model_obj, color=c2, step_size=0.005, lw=1.1, ls=\"-\")\n",
    "fp.plot_satellite(ax,satpos[66],color='blue',alpha=0.9)\n",
    "fp.plot_satellite(ax,satpos2[1],color='red',alpha=0.9)\n",
    "fp.plot_satellite(ax,satpos3[36],color='green',alpha=0.9)\n",
    "\n",
    "\n",
    "# ax.plot([0,0.689],[0,0],[0,0],ls='-',color='black',lw=0.3)\n",
    "\n",
    "fp.plot_circle(ax,0.689)\n",
    "fp.plot_circle(ax,1.0)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "\n",
    "#plt.savefig('results/initial_test.pdf')\n",
    "#plt.savefig('initial_test.png', dpi=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0d90c67",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "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": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}