{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "61fdf99d",
   "metadata": {},
   "source": [
    "# Section 6.2 - Venus SmallSat Constellation - Approach Trajectories"
   ]
  },
  {
   "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": [
      "Small satellite #1\n",
      "Entry altitude, km: 150.0\n",
      "Entry longitude BI, deg: -14.49\n",
      "Entry latitude BI, deg: 22.56\n",
      "Atm. relative entry speed, km/s: 10.8187\n",
      "Atm. relative heading angle, deg: 100.7733\n",
      "Atm. relative EFPA, deg: -5.201\n",
      "Inclination, deg: 80.00990376157564\n",
      "----------------------------------------------------\n",
      "Small satellite #2\n",
      "Entry altitude, km: 150.0\n",
      "Entry longitude BI, deg: -10.39\n",
      "Entry latitude BI, deg: 23.1\n",
      "Atm. relative entry speed, km/s: 10.8189\n",
      "Atm. relative heading angle, deg: 95.4145\n",
      "Atm. relative EFPA, deg: -5.2009\n",
      "Inclination, deg: 84.99180827393316\n",
      "----------------------------------------------------\n",
      "Small satellite #3\n",
      "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",
      "----------------------------------------------------\n",
      "Small satellite #4\n",
      "Entry altitude, km: 150.0\n",
      "Entry longitude BI, deg: -2.06\n",
      "Entry latitude BI, deg: 23.1\n",
      "Atm. relative entry speed, km/s: 10.8192\n",
      "Atm. relative heading angle, deg: 84.5675\n",
      "Atm. relative EFPA, deg: -5.2007\n",
      "Inclination, deg: 95.00819172606687\n",
      "----------------------------------------------------\n",
      "Small satellite #5\n",
      "Entry altitude, km: 150.0\n",
      "Entry longitude BI, deg: 2.06\n",
      "Entry latitude BI, deg: 22.56\n",
      "Atm. relative entry speed, km/s: 10.8194\n",
      "Atm. relative heading angle, deg: 79.1875\n",
      "Atm. relative EFPA, deg: -5.2007\n",
      "Inclination, deg: 100.01008259718387\n",
      "----------------------------------------------------\n",
      "----------------------------------------------------\n",
      "Main Orbiter\n",
      "Inclination, deg: 90.00000000000001\n",
      "----------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/athul/Documents/Codes/AMAT-py3.9/venv/lib/python3.9/site-packages/AMAT-2.2.22-py3.9.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": [
    "approach1 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+103.85)*1e3, psi=1.05988*np.pi,\n",
    "                            is_entrySystem=True, h_EI=150e3)\n",
    "\n",
    "approach2 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+103.85)*1e3, psi=1.03*np.pi,\n",
    "                            is_entrySystem=True, h_EI=150e3)\n",
    "\n",
    "approach3 = 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",
    "approach4 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+103.85)*1e3, psi=0.97*np.pi,\n",
    "                            is_entrySystem=True, h_EI=150e3)\n",
    "\n",
    "approach5 = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec,\n",
    "                            rp=(6051.8+103.85)*1e3, psi=0.94*np.pi,\n",
    "                            is_entrySystem=True, h_EI=150e3)\n",
    "\n",
    "space = Approach(\"VENUS\", v_inf_vec_icrf_kms=arrival.v_inf_vec, rp=(6051.8 + 400) * 1e3, psi=1.0*np.pi)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "print('Small satellite #1')\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",
    "print(\"Inclination, deg: \"+str(approach1.i*180/np.pi))\n",
    "print('----------------------------------------------------')\n",
    "print('Small satellite #2')\n",
    "print(\"Entry altitude, km: \"+ str(approach2.h_EI/1e3))\n",
    "print(\"Entry longitude BI, deg: \"+ str(round(approach2.longitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Entry latitude BI, deg: \"+ str(round(approach2.latitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Atm. relative entry speed, km/s: \"+str(round(approach2.v_entry_atm_mag/1e3, 4)))\n",
    "print(\"Atm. relative heading angle, deg: \"+str(round(approach2.heading_entry_atm*180/np.pi, 4)))\n",
    "print(\"Atm. relative EFPA, deg: \"+str(round(approach2.gamma_entry_atm*180/np.pi, 4)))\n",
    "print(\"Inclination, deg: \"+str(approach2.i*180/np.pi))\n",
    "print('----------------------------------------------------')\n",
    "print('Small satellite #3')\n",
    "print(\"Entry altitude, km: \"+ str(approach3.h_EI/1e3))\n",
    "print(\"Entry longitude BI, deg: \"+ str(round(approach3.longitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Entry latitude BI, deg: \"+ str(round(approach3.latitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Atm. relative entry speed, km/s: \"+str(round(approach3.v_entry_atm_mag/1e3, 4)))\n",
    "print(\"Atm. relative heading angle, deg: \"+str(round(approach3.heading_entry_atm*180/np.pi, 4)))\n",
    "print(\"Atm. relative EFPA, deg: \"+str(round(approach3.gamma_entry_atm*180/np.pi, 4)))\n",
    "print(\"Inclination, deg: \"+str(approach3.i*180/np.pi))\n",
    "print('----------------------------------------------------')\n",
    "print('Small satellite #4')\n",
    "print(\"Entry altitude, km: \"+ str(approach4.h_EI/1e3))\n",
    "print(\"Entry longitude BI, deg: \"+ str(round(approach4.longitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Entry latitude BI, deg: \"+ str(round(approach4.latitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Atm. relative entry speed, km/s: \"+str(round(approach4.v_entry_atm_mag/1e3, 4)))\n",
    "print(\"Atm. relative heading angle, deg: \"+str(round(approach4.heading_entry_atm*180/np.pi, 4)))\n",
    "print(\"Atm. relative EFPA, deg: \"+str(round(approach4.gamma_entry_atm*180/np.pi, 4)))\n",
    "print(\"Inclination, deg: \"+str(approach4.i*180/np.pi))\n",
    "print('----------------------------------------------------')\n",
    "print('Small satellite #5')\n",
    "print(\"Entry altitude, km: \"+ str(approach5.h_EI/1e3))\n",
    "print(\"Entry longitude BI, deg: \"+ str(round(approach5.longitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Entry latitude BI, deg: \"+ str(round(approach5.latitude_entry_bi*180/np.pi, 2)))\n",
    "print(\"Atm. relative entry speed, km/s: \"+str(round(approach5.v_entry_atm_mag/1e3, 4)))\n",
    "print(\"Atm. relative heading angle, deg: \"+str(round(approach5.heading_entry_atm*180/np.pi, 4)))\n",
    "print(\"Atm. relative EFPA, deg: \"+str(round(approach5.gamma_entry_atm*180/np.pi, 4)))\n",
    "print(\"Inclination, deg: \"+str(approach5.i*180/np.pi))\n",
    "print('----------------------------------------------------')\n",
    "print('----------------------------------------------------')\n",
    "print('Main Orbiter')\n",
    "print(\"Inclination, deg: \"+str(space.i*180/np.pi))\n",
    "print('----------------------------------------------------')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1ac68319",
   "metadata": {},
   "outputs": [
    {
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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-constellation-approach.png', width=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ded4eb1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rcParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9bc111c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes\n",
    "from mpl_toolkits.axes_grid1.inset_locator import mark_inset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "07757735",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 425x425 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "fig.set_size_inches([4.25, 4.25])\n",
    "\n",
    "plt.rc('font',family='Times New Roman')\n",
    "params = {'mathtext.default': 'regular' }\n",
    "plt.rcParams.update(params)\n",
    "\n",
    "theta_arr = np.linspace(0, 2*np.pi, 101)\n",
    "X_MARS = approach1.planetObj.RP*np.cos(theta_arr)/1e6\n",
    "Y_MARS = approach1.planetObj.RP*np.sin(theta_arr)/1e6\n",
    "\n",
    "plt.plot(X_MARS, Y_MARS, color='red', linestyle='dashed', linewidth=2.0, label='Venus surface')\n",
    "\n",
    "BR1 = np.dot(approach1.b_mag*approach1.B_vec_bi_unit, approach1.R_vec_bi_unit)\n",
    "BT1 = np.dot(approach1.b_mag*approach1.B_vec_bi_unit, approach1.T_vec_bi_unit)\n",
    "\n",
    "BR2 = np.dot(approach2.b_mag*approach2.B_vec_bi_unit, approach2.R_vec_bi_unit)\n",
    "BT2 = np.dot(approach2.b_mag*approach2.B_vec_bi_unit, approach2.T_vec_bi_unit)\n",
    "\n",
    "BR3 = np.dot(approach3.b_mag*approach3.B_vec_bi_unit, approach3.R_vec_bi_unit)\n",
    "BT3 = np.dot(approach3.b_mag*approach3.B_vec_bi_unit, approach3.T_vec_bi_unit)\n",
    "\n",
    "BR4 = np.dot(approach4.b_mag*approach4.B_vec_bi_unit, approach4.R_vec_bi_unit)\n",
    "BT4 = np.dot(approach4.b_mag*approach4.B_vec_bi_unit, approach4.T_vec_bi_unit)\n",
    "\n",
    "BR5 = np.dot(approach5.b_mag*approach5.B_vec_bi_unit, approach5.R_vec_bi_unit)\n",
    "BT5 = np.dot(approach5.b_mag*approach5.B_vec_bi_unit, approach5.T_vec_bi_unit)\n",
    "\n",
    "BR6 = np.dot(space.b_mag*space.B_vec_bi_unit, space.R_vec_bi_unit)\n",
    "BT6 = np.dot(space.b_mag*space.B_vec_bi_unit, space.T_vec_bi_unit)\n",
    "\n",
    "\n",
    "X_SS = (BR3/1e6)*np.cos(theta_arr)\n",
    "Y_SS = (BR3/1e6)*np.sin(theta_arr)\n",
    "plt.plot(X_SS, Y_SS, color='g', linestyle='dashed', linewidth=2.0, label='SmallSat |B| circle')\n",
    "\n",
    "X_HS = (BR6/1e6)*np.cos(theta_arr)\n",
    "Y_HS = (BR6/1e6)*np.sin(theta_arr)\n",
    "plt.plot(X_HS, Y_HS, color='m', linestyle='dashed', linewidth=2.0, label='Host |B| circle')\n",
    "\n",
    "\n",
    "plt.scatter(BT1/1e6, BR1/1e6, marker=\"o\", s=40, color='g', zorder=100,  label='SmallSat aim points')\n",
    "plt.scatter(BT2/1e6, BR2/1e6, marker=\"o\", s=40, color='g', zorder=100)\n",
    "plt.scatter(BT3/1e6, BR3/1e6, marker=\"o\", s=40, color='g', zorder=100)\n",
    "plt.scatter(BT4/1e6, BR4/1e6, marker=\"o\", s=40, color='g', zorder=100)\n",
    "plt.scatter(BT5/1e6, BR5/1e6, marker=\"o\", s=40, color='g', zorder=100)\n",
    "plt.scatter(BT6/1e6, BR6/1e6, marker=\"*\", s=100, color='m', zorder=100, label='Host orbiter aim point')\n",
    "\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "plt.gca().set_aspect('equal')\n",
    "\n",
    "plt.xlabel('B.T '+r'$\\times 10^3$'+ ' km' ,fontsize=12)\n",
    "plt.ylabel('B.R '+r'$\\times 10^3$'+ ' km' ,fontsize=12)\n",
    "\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xticks(fontsize=12)\n",
    "ax = plt.gca()\n",
    "ax.tick_params(direction='in')\n",
    "ax.yaxis.set_ticks_position('both')\n",
    "ax.xaxis.set_ticks_position('both')\n",
    "\n",
    "ax.set_zorder(1)\n",
    "ax=plt.gca()\n",
    "ax.xaxis.set_tick_params(direction='in', which='both')\n",
    "ax.yaxis.set_tick_params(direction='in', which='both')\n",
    "ax.xaxis.set_tick_params(width=1, length=4)\n",
    "ax.yaxis.set_tick_params(width=1, length=4)\n",
    "ax.xaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.yaxis.set_tick_params(width=1, length=4, which='minor')\n",
    "ax.xaxis.grid(which='major', color='k', linestyle='dotted', linewidth=0.5)\n",
    "ax.xaxis.grid(which='minor', color='k', linestyle='dotted', linewidth=0.0)\n",
    "ax.yaxis.grid(which='major', color='k', linestyle='dotted', linewidth=0.5)\n",
    "ax.yaxis.grid(which='minor', color='k', linestyle='dotted', linewidth=0.0)\n",
    "\n",
    "plt.annotate('', xy=(BT2/1e6, BR2/1e6), xytext=(BT1/1e6, BR1/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate('', xy=(BT3/1e6, BR3/1e6), xytext=(BT2/1e6, BR2/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate('', xy=(BT4/1e6, BR4/1e6), xytext=(BT3/1e6, BR3/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate('', xy=(BT5/1e6, BR5/1e6), xytext=(BT4/1e6, BR4/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "plt.annotate('', xy=(BT6/1e6, BR6/1e6), xytext=(BT5/1e6, BR5/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "\n",
    "#plt.text(5800, -1000, r'$\\Delta V_1$', fontsize=14)\n",
    "#plt.text(4700, -3500, r'$\\Delta V_2$', fontsize=14)\n",
    "#plt.text(3000, -5500, r'$\\Delta V_3$', fontsize=14)\n",
    "#plt.text(1000, -6200, r'$\\Delta V_4$', fontsize=14)\n",
    "#plt.text(-1500, -7200, r'$\\Delta V_5$', fontsize=14)\n",
    "\n",
    "\n",
    "for axis in ['top', 'bottom', 'left', 'right']:\n",
    "    ax.spines[axis].set_linewidth(2)\n",
    "    \n",
    "plt.xlim([-20, 20])\n",
    "#plt.ylim([-22, 0])\n",
    "\n",
    "axins = zoomed_inset_axes(ax, 3.7 ,loc=10, axes_kwargs={'zorder':2})\n",
    "axins.set_xlim(-4,4)\n",
    "axins.set_ylim(-20, -17.5)\n",
    "axins.plot(X_SS, Y_SS, color='g', linestyle='dashed', linewidth=2.0)\n",
    "axins.plot(X_HS, Y_HS, color='m', linestyle='dashed', linewidth=2.0)\n",
    "axins.scatter(BT1/1e6, BR1/1e6, marker=\"o\", s=40, color='g', zorder=1)\n",
    "axins.scatter(BT2/1e6, BR2/1e6, marker=\"o\", s=40, color='g', zorder=1)\n",
    "axins.scatter(BT3/1e6, BR3/1e6, marker=\"o\", s=40, color='g', zorder=1)\n",
    "axins.scatter(BT4/1e6, BR4/1e6, marker=\"o\", s=40, color='g', zorder=1)\n",
    "axins.scatter(BT5/1e6, BR5/1e6, marker=\"o\", s=40, color='g', zorder=1)\n",
    "axins.scatter(BT6/1e6, BR6/1e6, marker=\"*\", s=100, color='m', zorder=1)\n",
    "axins.annotate('', xy=(BT2/1e6, BR2/1e6), xytext=(BT1/1e6, BR1/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "axins.annotate('', xy=(BT3/1e6, BR3/1e6), xytext=(BT2/1e6, BR2/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "axins.annotate('', xy=(BT4/1e6, BR4/1e6), xytext=(BT3/1e6, BR3/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "axins.annotate('', xy=(BT5/1e6, BR5/1e6), xytext=(BT4/1e6, BR4/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "axins.annotate('', xy=(BT6/1e6, BR6/1e6), xytext=(BT5/1e6, BR5/1e6),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.2', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "\n",
    "#axins.scatter(BT5/1e3, BR5/1e3, marker=\"o\", s=100, color='g')\n",
    "#axins.scatter(BT6/1e3, BR6/1e3, marker=\"*\", s=200, color='m')\n",
    "axins.annotate('', xy=(BT6/1e3, 0.999*BR6/1e3), xytext=(BT5/1e3, BR5/1e3),\n",
    "               va=\"center\", ha=\"center\",\n",
    "               arrowprops=dict(arrowstyle='->, head_width=0.3', facecolor='blue'), fontsize=10, color='k',\n",
    "               bbox=dict(boxstyle='round,pad=0.2', fc='w', ec='k', alpha=1))\n",
    "#axins.text(50, -7450, r'$\\Delta V_5$', rotation=0, fontsize=12)\n",
    "\n",
    "axins.invert_yaxis()\n",
    "patch, pp1, pp2 = mark_inset(ax, axins,loc1=1,loc2=1, fc=\"none\", ec=\"k\", linestyle='solid', linewidth = 1.0, zorder=-10)\n",
    "pp1.loc1 = 1\n",
    "pp1.loc2 = 4\n",
    "pp2.loc1 = 2\n",
    "pp2.loc2 = 3\n",
    "plt.draw()\n",
    "\n",
    "axins.yaxis.get_major_locator().set_params(nbins=1)\n",
    "axins.xaxis.get_major_locator().set_params(nbins=1)\n",
    "\n",
    "plt.setp(axins.get_xticklabels(), visible=False)\n",
    "plt.setp(axins.get_yticklabels(), visible=True)\n",
    "\n",
    "axins.xaxis.set_tick_params(direction='in', which='both')\n",
    "axins.yaxis.set_tick_params(direction='in', which='both')\n",
    "\n",
    "axins.text(2.5, -18.3, r'$\\Delta V_1$', rotation=0, fontsize=12)\n",
    "axins.text(0.6, -18.5, r'$\\Delta V_2$', rotation=0, fontsize=12)\n",
    "axins.text(-1.2, -18.5, r'$\\Delta V_3$', rotation=0, fontsize=12)\n",
    "axins.text(-3.2, -18.3, r'$\\Delta V_4$', rotation=0, fontsize=12)\n",
    "axins.text(-2.4, -19.3, r'$\\Delta V_5$', rotation=0, fontsize=12)\n",
    "\n",
    "ax.legend(loc='lower right', fontsize=10, framealpha=1)\n",
    "\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/venus/venus-smallsat-const-b-plane.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/venus/venus-smallsat-const-b-plane.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../../../data/mdpi-aerospace/smallsat-mission-concepts/venus/venus-smallsat-const-b-plane.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  }
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