{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "61fdf99d",
   "metadata": {},
   "source": [
    "# Section 4.3 - Venus SmallSat Aerocapture - Interplanetary Approach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "29dc6009",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from astropy.time import Time\n",
    "from AMAT.arrival import Arrival"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4fb3cea5",
   "metadata": {},
   "outputs": [],
   "source": [
    "arrival = Arrival()\n",
    "arrival.set_vinf_vec_from_lambert_arc(lastFlybyPlanet='EARTH',\n",
    "                                      arrivalPlanet='VENUS',\n",
    "                                      lastFlybyDate=Time(\"2010-05-10 00:00:00\", scale='tdb'),\n",
    "                                      arrivalDate=Time(\"2010-12-06 00:00:00\", scale='tdb'),\n",
    "                                      ephem_file='../../../spice-data/de432s.bsp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "53f2f563",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arrival v_inf vector, ICRF: [-3.26907095  0.67649492 -1.06977471] km/s\n",
      "Arrival VINF MAG: 3.51 km/s.\n",
      "Arrival Declination: -21.93 deg.\n"
     ]
    }
   ],
   "source": [
    "print(\"Arrival v_inf vector, ICRF: \"+str(arrival.v_inf_vec)+\" km/s\")\n",
    "print(\"Arrival VINF MAG: \"+str(round(arrival.v_inf_mag, 2))+\" km/s.\")\n",
    "print(\"Arrival Declination: \"+str(round(arrival.declination, 2))+\" deg.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5ee00b2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from AMAT.approach import Approach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "57f8b29f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entry altitude, km: 150.0\n",
      "Entry longitude BI, deg: -6.22\n",
      "Entry latitude BI, deg: 23.28\n",
      "Atm. relative entry speed, km/s: 10.8191\n",
      "Atm. relative heading angle, deg: 89.991\n",
      "Atm. relative EFPA, deg: -5.2008\n",
      "Inclination, deg: 90.00000000000001\n"
     ]
    }
   ],
   "source": [
    "approach1 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+103.85)*1e3, psi=np.pi,\n",
    "                            is_entrySystem=True, h_EI=150e3)\n",
    "\n",
    "print(\"Entry altitude, km: \"+ str(approach1.h_EI/1e3))\n",
    "print(\"Entry longitude BI, deg: \"+ str(round(approach1.longitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Entry latitude BI, deg: \"+ str(round(approach1.latitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Atm. relative entry speed, km/s: \"+str(round(approach1.v_entry_atm_mag/1e3, 4)))\n",
    "print(\"Atm. relative heading angle, deg: \"+str(round(approach1.heading_entry_atm*180/np.pi, 4)))\n",
    "print(\"Atm. relative EFPA, deg: \"+str(round(approach1.gamma_entry_atm*180/np.pi, 4)))\n",
    "\n",
    "print(\"Inclination, deg: \"+str(approach1.i*180/np.pi))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a7365d8",
   "metadata": {},
   "source": [
    "Run the following code to generate the approach trajectory plot. The code is also available in the file ```section-4-3-venus-smallsat-approach-viz.py```."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74e2d43a",
   "metadata": {},
   "source": [
    "```\n",
    "from mayavi import mlab\n",
    "import numpy as np\n",
    "from tvtk.tools import visual\n",
    "from AMAT.approach import Approach\n",
    "from astropy.time import Time\n",
    "from AMAT.arrival import Arrival\n",
    "\n",
    "def Arrow_From_A_to_B(x1, y1, z1, x2, y2, z2):\n",
    "    ar1 = visual.arrow(x=x1, y=y1, z=z1)\n",
    "    ar1.length_cone = 0.4\n",
    "\n",
    "    arrow_length = np.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2 + (z2 - z1) ** 2)\n",
    "    ar1.actor.scale = [arrow_length, arrow_length, arrow_length]\n",
    "    ar1.pos = ar1.pos / arrow_length\n",
    "    ar1.axis = [x2 - x1, y2 - y1, z2 - z1]\n",
    "    return ar1\n",
    "\n",
    "arrival = Arrival()\n",
    "arrival.set_vinf_vec_from_lambert_arc(lastFlybyPlanet='EARTH',\n",
    "                                      arrivalPlanet='VENUS',\n",
    "                                      lastFlybyDate=Time(\"2010-05-10 00:00:00\", scale='tdb'),\n",
    "                                      arrivalDate=Time(\"2010-12-06 00:00:00\", scale='tdb'),\n",
    "                                      ephem_file='../../../spice-data/de432s.bsp')\n",
    "\n",
    "\n",
    "\n",
    "probe = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+105)*1e3, psi=np.pi,\n",
    "                            is_entrySystem=True, h_EI=150e3)\n",
    "\n",
    "\n",
    "space = Approach(\"VENUS\",\n",
    "                    v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                 rp=(6051.8 + 400) * 1e3, psi=3*np.pi/2)\n",
    "\n",
    "north_pole_bi_vec = probe.ICRF_to_BI(arrival.north_pole)\n",
    "\n",
    "theta_star_arr_probe = np.linspace(-2.25, probe.theta_star_entry, 101)\n",
    "pos_vec_bi_arr_probe = probe.pos_vec_bi(theta_star_arr_probe)/6051.8e3\n",
    "\n",
    "\n",
    "theta_star_arr_space = np.linspace(-2.25, 0.0, 101)\n",
    "pos_vec_bi_arr_space = space.pos_vec_bi(theta_star_arr_space)/6051.8e3\n",
    "\n",
    "x_arr_probe = pos_vec_bi_arr_probe[0][:]\n",
    "y_arr_probe = pos_vec_bi_arr_probe[1][:]\n",
    "z_arr_probe = pos_vec_bi_arr_probe[2][:]\n",
    "\n",
    "x_arr_space = pos_vec_bi_arr_space[0][:]\n",
    "y_arr_space = pos_vec_bi_arr_space[1][:]\n",
    "z_arr_space = pos_vec_bi_arr_space[2][:]\n",
    "\n",
    "\n",
    "u = np.linspace(0, 2 * np.pi, 100)\n",
    "v = np.linspace(0, np.pi, 100)\n",
    "x = 1*np.outer(np.cos(u), np.sin(v))\n",
    "y = 1*np.outer(np.sin(u), np.sin(v))\n",
    "z = 1*np.outer(np.ones(np.size(u)), np.cos(v))\n",
    "\n",
    "x1 = 1.040381198513972*np.outer(np.cos(u), np.sin(v))\n",
    "y1 = 1.040381198513972*np.outer(np.sin(u), np.sin(v))\n",
    "z1 = 1.040381198513972*np.outer(np.ones(np.size(u)), np.cos(v))\n",
    "\n",
    "\n",
    "x_ring_1 = 1.1*np.cos(u)\n",
    "y_ring_1 = 1.1*np.sin(u)\n",
    "z_ring_1 = 0.0*np.cos(u)\n",
    "\n",
    "x_ring_2 = 1.2*np.cos(u)\n",
    "y_ring_2 = 1.2*np.sin(u)\n",
    "z_ring_2 = 0.0*np.cos(u)\n",
    "\n",
    "mlab.figure(bgcolor=(0,0,0))\n",
    "s1 = mlab.mesh(x, y, z, color=(0.34,0.33,0.33))\n",
    "s2 = mlab.mesh(x1, y1, z1, color=(0.34, 0.33,0.33), opacity=0.3)\n",
    "r1 = mlab.plot3d(x_ring_1, y_ring_1, z_ring_1, color=(1,1,1), line_width=1, tube_radius=None)\n",
    "#r2 = mlab.plot3d(x_ring_2, y_ring_2, z_ring_2, color=(1,1,1), line_width=1, tube_radius=None)\n",
    "\n",
    "p1 = mlab.plot3d(x_arr_probe, y_arr_probe, z_arr_probe, color=(0,1,0), line_width=3, tube_radius=None)\n",
    "#p2 = mlab.plot3d(x_arr_space, y_arr_space, z_arr_space, color=(0,0,1), line_width=3, tube_radius=None)\n",
    "\n",
    "\n",
    "mlab.plot3d([0, 1.2 * north_pole_bi_vec[0]],\n",
    "                   [0, 1.2 * north_pole_bi_vec[1]],\n",
    "                   [0, 1.2 * north_pole_bi_vec[2]])\n",
    "\n",
    "mlab.show()\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1ac68319",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "image/png": {
       "width": 1200
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='../../../plots/venus-smallsat-approach.png', width=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "df5c2365",
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.orbiter import PropulsiveOrbiter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f124ced8",
   "metadata": {},
   "outputs": [],
   "source": [
    "approach2 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+200)*1e3, psi=np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "329fca98",
   "metadata": {},
   "outputs": [],
   "source": [
    "orbiter = PropulsiveOrbiter(approach=approach2, apoapsis_alt_km=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b36993b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3131.626375180178"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orbiter.DV_OI_mag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "851dfa26",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/athul/Documents/Codes/AMAT/venv/lib/python3.8/site-packages/AMAT-2.2.20-py3.8.egg/AMAT/approach.py:480: RuntimeWarning: invalid value encountered in arccos\n",
      "  gamma = -1*np.arccos(self.h/(r_mag_bi*v_mag_bi))\n"
     ]
    }
   ],
   "source": [
    "approach3 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+400)*1e3, psi=np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "73bb0099",
   "metadata": {},
   "outputs": [],
   "source": [
    "orbiter2 = PropulsiveOrbiter(approach=approach2, apoapsis_alt_km=150000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ccc7c599",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "784.1738873565789"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orbiter2.DV_OI_mag"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}