{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 07 - b - Saturn  - Feasibility Charts - Drag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from AMAT.planet import Planet\n",
    "from AMAT.vehicle import Vehicle\n",
    "\n",
    "import numpy as np\n",
    "from scipy import interpolate\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rcParams\n",
    "from matplotlib.patches import Polygon\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up the planet and atmosphere model.\n",
    "planet=Planet(\"SATURN\")\n",
    "planet.h_skip = 1000e3\n",
    "planet.h_low = 50e3\n",
    "planet.loadAtmosphereModel('../atmdata/Saturn/saturn-nominal.dat', 0 , 1 , 2, 3, heightInKmFlag=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta1 = 20.0\n",
    "\n",
    "runID = 'saturn-drag-'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "vinf_kms_array  = np.linspace( 0.0,   30.0,   11)\n",
    "betaRatio_array = np.linspace( 1.0,   41.0 ,  11)\n",
    "\n",
    "v0_kms_array    = np.zeros(len(vinf_kms_array))\n",
    "v0_kms_array[:] = np.sqrt(1.0*(vinf_kms_array[:]*1E3)**2.0 + 2*np.ones(len(vinf_kms_array))*\\\n",
    "                          planet.GM/(planet.RP+1000.0*1.0E3))/1.0E3\n",
    "\n",
    "overShootLimit_array  = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "underShootLimit_array = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "exitflag_os_array     = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "exitflag_us_array     = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "TCW_array             = np.zeros((len(v0_kms_array),len(betaRatio_array)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VINF: 0.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 5.0 TCW: 0.8760489264823264 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 9.0 TCW: 1.1740835885866545 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 13.0 TCW: 1.353705618152162 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 17.0 TCW: 1.4829480180342216 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 21.0 TCW: 1.5833320954698138 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 25.0 TCW: 1.6647800668724813 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 29.0 TCW: 1.7335814872858464 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 33.0 TCW: 1.7925984178727958 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 37.0 TCW: 1.8447420470474754 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 41.0 TCW: 1.8914975341031095 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 5.0 TCW: 0.875843480709591 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 9.0 TCW: 1.1734758539678296 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 13.0 TCW: 1.3534271934986464 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 17.0 TCW: 1.4826413269911427 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 21.0 TCW: 1.58268093989318 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 25.0 TCW: 1.6644287743474706 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 29.0 TCW: 1.7329078165930696 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 33.0 TCW: 1.7922349564250908 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 37.0 TCW: 1.8443807203875622 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 41.0 TCW: 1.8908379746353603 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 5.0 TCW: 0.8753171940115863 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 9.0 TCW: 1.1727542429507594 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 13.0 TCW: 1.352648687461624 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 17.0 TCW: 1.4818653312686365 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 21.0 TCW: 1.5818366079111001 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 25.0 TCW: 1.6635100426137797 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 29.0 TCW: 1.7319718119106255 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 33.0 TCW: 1.7913037956532207 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 37.0 TCW: 1.8434694505267544 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 41.0 TCW: 1.8899542276340071 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 5.0 TCW: 0.8741854125692043 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 9.0 TCW: 1.1715912469298928 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 13.0 TCW: 1.3511196427643881 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 17.0 TCW: 1.4802798842501943 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 21.0 TCW: 1.5801531692268327 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 25.0 TCW: 1.661720684824104 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 29.0 TCW: 1.7301434452019748 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 33.0 TCW: 1.789212344061525 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 37.0 TCW: 1.8414037955881213 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 41.0 TCW: 1.8881957925332244 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 5.0 TCW: 0.8728047379045165 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 9.0 TCW: 1.1694043632087414 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 13.0 TCW: 1.3488931197643979 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 17.0 TCW: 1.4779661885477253 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 21.0 TCW: 1.5776651823834982 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 25.0 TCW: 1.6588475429816754 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 29.0 TCW: 1.7272314222573186 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 33.0 TCW: 1.7865994933017646 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 37.0 TCW: 1.8388555627971073 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 41.0 TCW: 1.88537541043479 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 5.0 TCW: 0.8716925507615088 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 9.0 TCW: 1.1673687271177187 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 13.0 TCW: 1.3468245211988688 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 17.0 TCW: 1.4757112114748452 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 21.0 TCW: 1.5752090907408274 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 25.0 TCW: 1.656267363607185 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 29.0 TCW: 1.7246512985875597 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 33.0 TCW: 1.784057717777614 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 37.0 TCW: 1.8360824723349651 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 41.0 TCW: 1.882849715570046 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 5.0 TCW: 0.869737593769969 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 9.0 TCW: 1.1647198861392098 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 13.0 TCW: 1.3441250302130356 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 17.0 TCW: 1.4724891390360426 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 21.0 TCW: 1.5717833395538037 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 25.0 TCW: 1.6527615745653748 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 29.0 TCW: 1.7211325206590118 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 33.0 TCW: 1.7803512567625148 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 37.0 TCW: 1.8326092594361398 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 41.0 TCW: 1.8793215838086326 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 5.0 TCW: 0.8679448547991342 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 9.0 TCW: 1.1622052049642662 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 13.0 TCW: 1.341471725012525 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 17.0 TCW: 1.4694987058392144 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 21.0 TCW: 1.5685711305341101 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 25.0 TCW: 1.6494754467275925 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 29.0 TCW: 1.7178828916657949 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 33.0 TCW: 1.7771069156369776 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 37.0 TCW: 1.8293090342194773 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 41.0 TCW: 1.875712882996595 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 5.0 TCW: 0.8658819610864157 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 9.0 TCW: 1.1591839040629566 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 13.0 TCW: 1.3382073393877363 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 17.0 TCW: 1.465857065122691 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 21.0 TCW: 1.5645115631486988 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 25.0 TCW: 1.645346015204268 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 29.0 TCW: 1.713797433905711 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 33.0 TCW: 1.772952474449994 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 37.0 TCW: 1.8250562745015486 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 41.0 TCW: 1.87135832128115 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 5.0 TCW: 0.8635587606040644 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 9.0 TCW: 1.1561992924107471 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 13.0 TCW: 1.3346148843484116 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 17.0 TCW: 1.4618656777674914 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 21.0 TCW: 1.5605519130840548 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 25.0 TCW: 1.6413600214436883 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 29.0 TCW: 1.7095688591653015 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 33.0 TCW: 1.768830813736713 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 37.0 TCW: 1.8205984519809135 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 41.0 TCW: 1.8667758169249282 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 1.0 TCW: 0.0 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 5.0 TCW: 0.8609772741692723 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 9.0 TCW: 1.1529721405167948 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 13.0 TCW: 1.3308813936528168 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 17.0 TCW: 1.4575389728197479 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 21.0 TCW: 1.5560672250358039 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 25.0 TCW: 1.6368380951826111 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 29.0 TCW: 1.705149168454227 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 33.0 TCW: 1.7640654517163057 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 37.0 TCW: 1.8157036643387983 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 41.0 TCW: 1.861744529880525 deg.\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(betaRatio_array)):\n",
    "        vehicle=Vehicle('DMVehicle', 300.0, beta1, 0.0, 3.1416, 0.0, 0.10, planet)\n",
    "        vehicle.setInitialState(1000.0,0.0,0.0,v0_kms_array[i],0.0,-4.5,0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-6)\n",
    "        vehicle.setDragModulationVehicleParams(beta1,betaRatio_array[j])\n",
    "\n",
    "        underShootLimit_array[i,j], exitflag_us_array[i,j] = vehicle.findUnderShootLimitD(2400.0, 1.0, -15.0,-4.0,1E-10,4000)\n",
    "        overShootLimit_array[i,j] , exitflag_os_array[i,j] = vehicle.findOverShootLimitD (2400.0, 1.0, -15.0,-4.0,1E-10,4000)\n",
    "\n",
    "        TCW_array[i,j]    = overShootLimit_array[i,j] - underShootLimit_array[i,j]\n",
    "\n",
    "        print('VINF: '+str(vinf_kms_array[i])+' km/s, BETA RATIO: '+str(betaRatio_array[j])+' TCW: '+str(TCW_array[i,j])+' deg.')\n",
    "\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'vinf_kms_array.txt',vinf_kms_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'v0_kms_array.txt',v0_kms_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'betaRatio_array.txt',betaRatio_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'overShootLimit_array.txt',overShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'exitflag_os_array.txt',exitflag_os_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'underShootLimit_array.txt',underShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'exitflag_us_array.txt',exitflag_us_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'TCW_array.txt',TCW_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 0.0 km/s, BR: 1.0 G_MAX: 7.610221219246741 QDOT_MAX: 1128.4054357321504 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 5.0 G_MAX: 7.610221219246741 QDOT_MAX: 1487.2012245003764 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 9.0 G_MAX: 7.610221219246741 QDOT_MAX: 1581.794712573322 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 13.0 G_MAX: 7.610221219246741 QDOT_MAX: 1634.1766579662026 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 17.0 G_MAX: 7.610221219246741 QDOT_MAX: 1670.3295189040787 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 21.0 G_MAX: 7.610221219246741 QDOT_MAX: 1697.589125221713 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 25.0 G_MAX: 7.610221219246741 QDOT_MAX: 1719.0935101478544 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 29.0 G_MAX: 7.610221219246741 QDOT_MAX: 1737.0345594909427 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 33.0 G_MAX: 7.610221219246741 QDOT_MAX: 1752.065255101766 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 37.0 G_MAX: 7.610221219246741 QDOT_MAX: 1765.361154983129 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 0.0 km/s, BR: 41.0 G_MAX: 7.610221219246741 QDOT_MAX: 1777.145104544117 J_MAX: 212887.1692913718 STAG. PRES: 0.014746368417578084\n",
      "V_infty: 3.0 km/s, BR: 1.0 G_MAX: 7.721049403851685 QDOT_MAX: 1143.18321042315 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 5.0 G_MAX: 7.721049403851685 QDOT_MAX: 1504.8083159563064 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 9.0 G_MAX: 7.721049403851685 QDOT_MAX: 1600.1120049511155 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 13.0 G_MAX: 7.721049403851685 QDOT_MAX: 1653.203669605648 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 17.0 G_MAX: 7.721049403851685 QDOT_MAX: 1689.669670400552 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 21.0 G_MAX: 7.721049403851685 QDOT_MAX: 1717.021103378029 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 25.0 G_MAX: 7.721049403851685 QDOT_MAX: 1738.9309103722942 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 29.0 G_MAX: 7.721049403851685 QDOT_MAX: 1756.9168053086084 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 33.0 G_MAX: 7.721049403851685 QDOT_MAX: 1772.254851174047 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 37.0 G_MAX: 7.721049403851685 QDOT_MAX: 1785.5446216549387 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 3.0 km/s, BR: 41.0 G_MAX: 7.721049403851685 QDOT_MAX: 1797.149873803461 J_MAX: 214749.14102990602 STAG. PRES: 0.014961089237380156\n",
      "V_infty: 6.0 km/s, BR: 1.0 G_MAX: 8.047163343549014 QDOT_MAX: 1187.4005845461302 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 5.0 G_MAX: 8.047163343549014 QDOT_MAX: 1558.0150017960755 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 9.0 G_MAX: 8.047163343549014 QDOT_MAX: 1655.7174248029621 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 13.0 G_MAX: 8.047163343549014 QDOT_MAX: 1710.11345429344 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 17.0 G_MAX: 8.047163343549014 QDOT_MAX: 1747.6014884203448 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 21.0 G_MAX: 8.047163343549014 QDOT_MAX: 1775.8253477779044 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 25.0 G_MAX: 8.047163343549014 QDOT_MAX: 1798.164740244332 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 29.0 G_MAX: 8.047163343549014 QDOT_MAX: 1816.5446430392694 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 33.0 G_MAX: 8.047163343549014 QDOT_MAX: 1832.4165438084772 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 37.0 G_MAX: 8.047163343549014 QDOT_MAX: 1846.239507254953 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 6.0 km/s, BR: 41.0 G_MAX: 8.047163343549014 QDOT_MAX: 1858.3198311385295 J_MAX: 220198.3084263887 STAG. PRES: 0.015592742413938822\n",
      "V_infty: 9.0 km/s, BR: 1.0 G_MAX: 8.597357323498036 QDOT_MAX: 1262.3675899148716 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 5.0 G_MAX: 8.597357323498036 QDOT_MAX: 1647.9579562122383 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 9.0 G_MAX: 8.597357323498036 QDOT_MAX: 1749.7943516176886 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 13.0 G_MAX: 8.597357323498036 QDOT_MAX: 1806.6414812002397 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 17.0 G_MAX: 8.597357323498036 QDOT_MAX: 1845.8644081091666 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 21.0 G_MAX: 8.597357323498036 QDOT_MAX: 1875.1330436705584 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 25.0 G_MAX: 8.597357323498036 QDOT_MAX: 1898.6946636138034 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 29.0 G_MAX: 8.597357323498036 QDOT_MAX: 1917.9773980360633 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 33.0 G_MAX: 8.597357323498036 QDOT_MAX: 1934.347299769134 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 37.0 G_MAX: 8.597357323498036 QDOT_MAX: 1948.8232803908265 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 9.0 km/s, BR: 41.0 G_MAX: 8.597357323498036 QDOT_MAX: 1961.6541538983615 J_MAX: 229241.2604670802 STAG. PRES: 0.016658413717528773\n",
      "V_infty: 12.0 km/s, BR: 1.0 G_MAX: 9.376141330177742 QDOT_MAX: 1369.7190459408575 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 5.0 G_MAX: 9.376141330177742 QDOT_MAX: 1776.5296068542648 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 9.0 G_MAX: 9.376141330177742 QDOT_MAX: 1884.2416561130076 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 13.0 G_MAX: 9.376141330177742 QDOT_MAX: 1944.5853906808288 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 17.0 G_MAX: 9.376141330177742 QDOT_MAX: 1986.2455071812929 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 21.0 G_MAX: 9.376141330177742 QDOT_MAX: 2017.3794264666403 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 25.0 G_MAX: 9.376141330177742 QDOT_MAX: 2042.1882668741137 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 29.0 G_MAX: 9.376141330177742 QDOT_MAX: 2062.677757094442 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 33.0 G_MAX: 9.376141330177742 QDOT_MAX: 2080.3941264011855 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 37.0 G_MAX: 9.376141330177742 QDOT_MAX: 2095.8577388393674 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 12.0 km/s, BR: 41.0 G_MAX: 9.376141330177742 QDOT_MAX: 2109.270560472862 J_MAX: 241753.4029509346 STAG. PRES: 0.018166788105753482\n",
      "V_infty: 15.0 km/s, BR: 1.0 G_MAX: 10.37713771325517 QDOT_MAX: 1511.2129107674766 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 5.0 G_MAX: 10.37713771325517 QDOT_MAX: 1946.378095313016 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 9.0 G_MAX: 10.37713771325517 QDOT_MAX: 2061.715622658611 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 13.0 G_MAX: 10.37713771325517 QDOT_MAX: 2126.799485007586 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 17.0 G_MAX: 10.37713771325517 QDOT_MAX: 2171.6959286280717 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 15.0 km/s, BR: 21.0 G_MAX: 10.37713771325517 QDOT_MAX: 2205.410992699744 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 25.0 G_MAX: 10.37713771325517 QDOT_MAX: 2232.3046715033456 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 29.0 G_MAX: 10.37713771325517 QDOT_MAX: 2254.474195522844 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 33.0 G_MAX: 10.37713771325517 QDOT_MAX: 2273.4094173664857 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 37.0 G_MAX: 10.37713771325517 QDOT_MAX: 2289.927960380115 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 15.0 km/s, BR: 41.0 G_MAX: 10.37713771325517 QDOT_MAX: 2304.7198017493565 J_MAX: 257503.75790269295 STAG. PRES: 0.0201055465642421\n",
      "V_infty: 18.0 km/s, BR: 1.0 G_MAX: 11.617825088322828 QDOT_MAX: 1690.2212180521246 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 5.0 G_MAX: 11.617825088322828 QDOT_MAX: 2160.9108185867826 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 9.0 G_MAX: 11.617825088322828 QDOT_MAX: 2286.201820611023 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 13.0 G_MAX: 11.617825088322828 QDOT_MAX: 2357.349348468525 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 17.0 G_MAX: 11.617825088322828 QDOT_MAX: 2406.276712701027 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 21.0 G_MAX: 11.617825088322828 QDOT_MAX: 2442.7608946220657 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 25.0 G_MAX: 11.617825088322828 QDOT_MAX: 2472.1414961069236 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 29.0 G_MAX: 11.617825088322828 QDOT_MAX: 2496.400922017117 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 33.0 G_MAX: 11.617825088322828 QDOT_MAX: 2517.434609895952 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 37.0 G_MAX: 11.617825088322828 QDOT_MAX: 2535.6180807276346 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 18.0 km/s, BR: 41.0 G_MAX: 11.617825088322828 QDOT_MAX: 2551.374943195289 J_MAX: 276500.7312118121 STAG. PRES: 0.02250838676368722\n",
      "V_infty: 21.0 km/s, BR: 1.0 G_MAX: 13.088787847480452 QDOT_MAX: 1909.7037759831549 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 5.0 G_MAX: 13.088787847480452 QDOT_MAX: 2424.259861527002 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 9.0 G_MAX: 13.088787847480452 QDOT_MAX: 2562.055630629622 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 13.0 G_MAX: 13.088787847480452 QDOT_MAX: 2640.4608118521974 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 17.0 G_MAX: 13.088787847480452 QDOT_MAX: 2694.5009381106534 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 21.0 G_MAX: 13.088787847480452 QDOT_MAX: 2734.9255336756996 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 25.0 G_MAX: 13.088787847480452 QDOT_MAX: 2767.250301082568 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 29.0 G_MAX: 13.088787847480452 QDOT_MAX: 2794.418361713338 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 33.0 G_MAX: 13.088787847480452 QDOT_MAX: 2817.578277169159 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 37.0 G_MAX: 13.088787847480452 QDOT_MAX: 2837.3270365647104 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 21.0 km/s, BR: 41.0 G_MAX: 13.088787847480452 QDOT_MAX: 2855.340009501725 J_MAX: 298500.07474570826 STAG. PRES: 0.025356951223690315\n",
      "V_infty: 24.0 km/s, BR: 1.0 G_MAX: 14.81108775249388 QDOT_MAX: 2174.489827976788 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 5.0 G_MAX: 14.81108775249388 QDOT_MAX: 2741.549620139579 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 9.0 G_MAX: 14.81108775249388 QDOT_MAX: 2894.610561773593 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 13.0 G_MAX: 14.81108775249388 QDOT_MAX: 2981.84690296957 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 17.0 G_MAX: 14.81108775249388 QDOT_MAX: 3042.175752443202 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 21.0 G_MAX: 14.81108775249388 QDOT_MAX: 3087.2908549630015 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 25.0 G_MAX: 14.81108775249388 QDOT_MAX: 3123.472817161632 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 29.0 G_MAX: 14.81108775249388 QDOT_MAX: 3153.8537284147824 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 33.0 G_MAX: 14.81108775249388 QDOT_MAX: 3179.4761386014343 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 37.0 G_MAX: 14.81108775249388 QDOT_MAX: 3201.924963588508 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 24.0 km/s, BR: 41.0 G_MAX: 14.81108775249388 QDOT_MAX: 3221.8519851017827 J_MAX: 323541.69065370015 STAG. PRES: 0.02869228744811461\n",
      "V_infty: 27.0 km/s, BR: 1.0 G_MAX: 16.773831390447732 QDOT_MAX: 2488.5051230940244 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 5.0 G_MAX: 16.773831390447732 QDOT_MAX: 3119.131808158232 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 9.0 G_MAX: 16.773831390447732 QDOT_MAX: 3290.3741606702224 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 13.0 G_MAX: 16.773831390447732 QDOT_MAX: 3388.310909544533 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 17.0 G_MAX: 16.773831390447732 QDOT_MAX: 3456.198988514642 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 21.0 G_MAX: 16.773831390447732 QDOT_MAX: 3507.27876664612 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 25.0 G_MAX: 16.773831390447732 QDOT_MAX: 3548.128883955063 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 29.0 G_MAX: 16.773831390447732 QDOT_MAX: 3582.0954998244956 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 33.0 G_MAX: 16.773831390447732 QDOT_MAX: 3610.9284754002233 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 37.0 G_MAX: 16.773831390447732 QDOT_MAX: 3636.7508827979814 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 27.0 km/s, BR: 41.0 G_MAX: 16.773831390447732 QDOT_MAX: 3658.3402089106908 J_MAX: 351517.65600066446 STAG. PRES: 0.03249288630202138\n",
      "V_infty: 30.0 km/s, BR: 1.0 G_MAX: 18.989912248714383 QDOT_MAX: 2857.781715935505 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 5.0 G_MAX: 18.989912248714383 QDOT_MAX: 3563.686787294337 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 9.0 G_MAX: 18.989912248714383 QDOT_MAX: 3757.5062998657922 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 13.0 G_MAX: 18.989912248714383 QDOT_MAX: 3868.6837887449115 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 17.0 G_MAX: 18.989912248714383 QDOT_MAX: 3945.212090732244 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 21.0 G_MAX: 18.989912248714383 QDOT_MAX: 4003.454827793433 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 25.0 G_MAX: 18.989912248714383 QDOT_MAX: 4049.762487294059 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 29.0 G_MAX: 18.989912248714383 QDOT_MAX: 4088.3883693028347 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 33.0 G_MAX: 18.989912248714383 QDOT_MAX: 4122.236480706251 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 30.0 km/s, BR: 37.0 G_MAX: 18.989912248714383 QDOT_MAX: 4150.257155871858 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n",
      "V_infty: 30.0 km/s, BR: 41.0 G_MAX: 18.989912248714383 QDOT_MAX: 4176.453191050427 J_MAX: 382458.53158451436 STAG. PRES: 0.03678407108936335\n"
     ]
    }
   ],
   "source": [
    "acc_net_g_max_array       = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "stag_pres_atm_max_array   = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "q_stag_total_max_array    = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "heatload_max_array        = np.zeros((len(v0_kms_array),len(betaRatio_array)))\n",
    "\n",
    "\n",
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(betaRatio_array)):\n",
    "        vehicle=Vehicle('DMVehicle', 300, beta1, 0.0, 3.1416, 0.0, 0.10, planet)\n",
    "        vehicle.setInitialState(1000.0,0.0,0.0,v0_kms_array[i],0.0,overShootLimit_array[i,j],0.0,0.0)\n",
    "        vehicle.setSolverParams(1E-5)\n",
    "\n",
    "        vehicle.propogateEntry (2400.0, 1.0, 0.0)\n",
    "\n",
    "        # Extract and save variables to plot\n",
    "        t_min_os         = vehicle.t_minc\n",
    "        h_km_os          = vehicle.h_kmc\n",
    "        acc_net_g_os     = vehicle.acc_net_g\n",
    "        q_stag_con_os    = vehicle.q_stag_con\n",
    "        q_stag_rad_os    = vehicle.q_stag_rad\n",
    "        rc_os            = vehicle.rc\n",
    "        vc_os            = vehicle.vc\n",
    "        stag_pres_atm_os = vehicle.computeStagPres(rc_os,vc_os)/(1.01325E5)\n",
    "        heatload_os      = vehicle.heatload\n",
    "\n",
    "\n",
    "        vehicle=Vehicle('DMVehicle', 300.0, beta1, 0.0, 3.1416, 0.0, 0.10, planet)\n",
    "        vehicle.setInitialState(1000.0,0.0,0.0,v0_kms_array[i],0.0,underShootLimit_array[i,j],0.0,0.0)\n",
    "        vehicle.setSolverParams( 1E-5)\n",
    "\n",
    "        vehicle.propogateEntry (2400.0, 1.0, 0.0)\n",
    "\n",
    "        # Extract and save variable to plot\n",
    "        t_min_us         = vehicle.t_minc\n",
    "        h_km_us          = vehicle.h_kmc\n",
    "        acc_net_g_us     = vehicle.acc_net_g\n",
    "        q_stag_con_us    = vehicle.q_stag_con\n",
    "        q_stag_rad_us    = vehicle.q_stag_rad\n",
    "        rc_us            = vehicle.rc\n",
    "        vc_us            = vehicle.vc\n",
    "        stag_pres_atm_us = vehicle.computeStagPres(rc_us,vc_us)/(1.01325E5)\n",
    "        heatload_us      = vehicle.heatload\n",
    "\n",
    "        q_stag_total_os  = q_stag_con_os + q_stag_rad_os\n",
    "        q_stag_total_us  = q_stag_con_us + q_stag_rad_us\n",
    "\n",
    "        acc_net_g_max_array[i,j]      = max(max(acc_net_g_os),max(acc_net_g_os))\n",
    "        stag_pres_atm_max_array[i,j]  = max(max(stag_pres_atm_os),max(stag_pres_atm_os))\n",
    "        q_stag_total_max_array[i,j]   = max(max(q_stag_total_os),max(q_stag_total_us))\n",
    "        heatload_max_array[i,j]       = max(max(heatload_os),max(heatload_os))\n",
    "\n",
    "        print(\"V_infty: \"+str(vinf_kms_array[i])+\" km/s\"+\", BR: \"+str(betaRatio_array[j])+\" G_MAX: \"+str(acc_net_g_max_array[i,j])+\" QDOT_MAX: \"+str(q_stag_total_max_array[i,j])+\" J_MAX: \"+str(heatload_max_array[i,j])+\" STAG. PRES: \"+str(stag_pres_atm_max_array[i,j]))\n",
    "\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'acc_net_g_max_array.txt',acc_net_g_max_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'stag_pres_atm_max_array.txt',stag_pres_atm_max_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'q_stag_total_max_array.txt',q_stag_total_max_array)\n",
    "np.savetxt('../data/jsr-paper/saturn/'+runID+'heatload_max_array.txt',heatload_max_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\AthulGirija\\anaconda3\\envs\\env1\\lib\\site-packages\\scipy\\interpolate\\interpolate.py:630: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  slope = (y_hi - y_lo) / (x_hi - x_lo)[:, None]\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 234x234 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../data/jsr-paper/saturn/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/saturn/'+runID+'betaRatio_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'stag_pres_atm_max_array.txt')\n",
    "\n",
    "\n",
    "f1 = interpolate.interp2d(x, y, np.transpose(Z1), kind='cubic')\n",
    "g1 = interpolate.interp2d(x, y, np.transpose(G1), kind='cubic')\n",
    "q1 = interpolate.interp2d(x, y, np.transpose(Q1), kind='cubic')\n",
    "h1 = interpolate.interp2d(x, y, np.transpose(H1), kind='cubic')\n",
    "s1 = interpolate.interp2d(x, y, np.transpose(S1), kind='cubic')\n",
    "\n",
    "\n",
    "x_new =  np.linspace( 0.0,   30,  110)\n",
    "y_new =  np.linspace( 0.0,   41 ,110)\n",
    "\n",
    "z1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "g1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "q1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "h1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "s1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "for i in range(0,len(x_new)):\n",
    "    for j in range(0,len(y_new)):\n",
    "\n",
    "        z1_new[i,j] = f1(x_new[i],y_new[j])\n",
    "        g1_new[i,j] = g1(x_new[i],y_new[j])\n",
    "        q1_new[i,j] = q1(x_new[i],y_new[j])\n",
    "        h1_new[i,j] = h1(x_new[i],y_new[j])\n",
    "        s1_new[i,j] = s1(x_new[i],y_new[j])\n",
    "\n",
    "\n",
    "Z1 = z1_new\n",
    "G1 = g1_new\n",
    "Q1 = q1_new\n",
    "S1 = s1_new\n",
    "H1 = h1_new/1000.0\n",
    "\n",
    "X, Y = np.meshgrid(x_new, y_new)\n",
    "\n",
    "Zlevels = np.array([1.0, 1.5])\n",
    "\n",
    "Glevels = np.array([10])\n",
    "Qlevels = np.array([1800, 2100])\n",
    "Hlevels = np.array([300])\n",
    "#Slevels = np.array([0.8])\n",
    "\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([3.25,3.25])\n",
    "rcParams['font.family'] = 'sans-serif'\n",
    "rcParams['font.sans-serif'] = ['DejaVu Sans']\n",
    "\n",
    "plt.xlim([0.0,30.0])\n",
    "plt.ylim([1.0,41.0])\n",
    "\n",
    "\n",
    "ZCS1 = plt.contour(X, Y, np.transpose(Z1), levels=Zlevels, colors='black')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.clabel(ZCS1, inline=1, fontsize=10, colors='black',fmt='%.2f',inline_spacing=1)\n",
    "ZCS1.collections[0].set_linewidths(1.5)\n",
    "ZCS1.collections[1].set_linewidths(1.5)\n",
    "ZCS1.collections[0].set_label(r'$TCW, deg$')\n",
    "\n",
    "\n",
    "GCS1 = plt.contour(X, Y, np.transpose(G1), levels=Glevels, colors='blue',linestyles='dashed')\n",
    "\n",
    "Glabels=plt.clabel(GCS1, inline=1, fontsize=10, colors='blue',fmt='%d',inline_spacing=0)\n",
    "GCS1.collections[0].set_linewidths(1.5)\n",
    "\n",
    "GCS1.collections[0].set_label(r'$g$'+r'-load')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted')\n",
    "\n",
    "plt.clabel(QCS1, inline=1, fontsize=10, colors='red',fmt='%d',inline_spacing=0)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "QCS1.collections[1].set_linewidths(1.5)\n",
    "QCS1.collections[0].set_label(r'$\\dot{q}$'+', '+r'$W/cm^2$')\n",
    "\n",
    "\n",
    "HCS1 = plt.contour(X, Y, np.transpose(H1), levels=Hlevels, colors='xkcd:brown',linestyles='dashdot')\n",
    "\n",
    "Hlabels=plt.clabel(HCS1, inline=1, fontsize=10, colors='xkcd:brown',fmt='%d',inline_spacing=0)\n",
    "HCS1.collections[0].set_linewidths(1.5)\n",
    "\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "\n",
    "#GCS1.collections[0].set_label(r'$Peak$'+r' '+r'$g-load$')\n",
    "plt.ylim(1,40)\n",
    "#plt.grid(True,linestyle='dotted', linewidth=0.3)\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(r'$\\beta_2$'+' / '+r'$ \\beta_1 $' ,fontsize=10)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=10)\n",
    "plt.xticks( fontsize=10)\n",
    "plt.yticks(np.array([ 1, 10, 20, 30, 40,]),fontsize=10)\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",
    "plt.legend(loc='upper right', fontsize=8)\n",
    "\n",
    "for l in Hlabels:\n",
    "    l.set_rotation(-90)\n",
    "for l in Glabels:\n",
    "    l.set_rotation(-90)\n",
    "\n",
    "dat0 = ZCS1.allsegs[1][0]\n",
    "\n",
    "x1,y1=dat0[:,0],dat0[:,1]\n",
    "F1 = interpolate.interp1d(x1, y1, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "\n",
    "dat2 = QCS1.allsegs[0][0]\n",
    "x3,y3= dat2[:,0],dat2[:,1]\n",
    "F3 = interpolate.interp1d(x3, y3, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "dat0a = ZCS1.allsegs[0][0]\n",
    "x1a,y1a=dat0a[:,0],dat0a[:,1]\n",
    "F1a = interpolate.interp1d(x1a, y1a, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "\n",
    "x4 = np.linspace(0,30,301)\n",
    "y4 = F1(x4)\n",
    "y4a =F1a(x4)\n",
    "\n",
    "\n",
    "y6 = F3(x4)\n",
    "\n",
    "y7 = y6\n",
    "y8 = np.minimum(y4,y6)\n",
    "\n",
    "\n",
    "\n",
    "plt.fill_between(x4, y4, y7, where=y4<=y7,color='xkcd:neon green')\n",
    "\n",
    "plt.fill_between(x4, y4a, y8, where=y4a<=y8,color='xkcd:bright yellow')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.savefig('../data/jsr-paper/saturn/saturn-drag-small.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/saturn/saturn-drag-small.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/saturn/saturn-drag-small.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 468x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../data/jsr-paper/saturn/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/saturn/'+runID+'betaRatio_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/saturn/'+runID+'stag_pres_atm_max_array.txt')\n",
    "\n",
    "\n",
    "f1 = interpolate.interp2d(x, y, np.transpose(Z1), kind='cubic')\n",
    "g1 = interpolate.interp2d(x, y, np.transpose(G1), kind='cubic')\n",
    "q1 = interpolate.interp2d(x, y, np.transpose(Q1), kind='cubic')\n",
    "h1 = interpolate.interp2d(x, y, np.transpose(H1), kind='cubic')\n",
    "\n",
    "x_new =  np.linspace( 0.0,   30,  210)\n",
    "y_new =  np.linspace( 1.0,   41 , 110)\n",
    "\n",
    "z1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "g1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "q1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "h1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "#s1_new =  np.zeros((len(x_new),len(y_new)))\n",
    "\n",
    "for i in range(0,len(x_new)):\n",
    "    for j in range(0,len(y_new)):\n",
    "\n",
    "        z1_new[i,j] = f1(x_new[i],y_new[j])\n",
    "        g1_new[i,j] = g1(x_new[i],y_new[j])\n",
    "        q1_new[i,j] = q1(x_new[i],y_new[j])\n",
    "        h1_new[i,j] = h1(x_new[i],y_new[j])\n",
    "\n",
    "        Z1 = z1_new\n",
    "        G1 = g1_new\n",
    "        Q1 = q1_new\n",
    "        H1 = h1_new/1000.0\n",
    "\n",
    "X, Y = np.meshgrid(x_new, y_new)\n",
    "\n",
    "Zlevels = np.array([0.5, 1.0, 1.2, 1.5, 1.6])\n",
    "\n",
    "Glevels = np.array([8, 10.0, 12.0])\n",
    "Qlevels = np.array([1800.0, 1900, 2100, 2300, 2500, 2700])\n",
    "Hlevels = np.array([225.0, 240, 275, 300, 325])\n",
    "#Slevels = np.array([0.8])\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([6.5,6.5])\n",
    "rcParams['font.family'] = 'sans-serif'\n",
    "rcParams['font.sans-serif'] = ['DejaVu Sans']\n",
    "\n",
    "ZCS1 = plt.contour(X, Y, np.transpose(Z1), levels=Zlevels, colors='black')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.clabel(ZCS1, inline=1, fontsize=10, colors='black',fmt='%.1f',inline_spacing=1)\n",
    "ZCS1.collections[0].set_linewidths(1.5)\n",
    "ZCS1.collections[1].set_linewidths(1.5)\n",
    "ZCS1.collections[2].set_linewidths(1.5)\n",
    "ZCS1.collections[3].set_linewidths(1.5)\n",
    "ZCS1.collections[4].set_linewidths(1.5)\n",
    "\n",
    "\n",
    "\n",
    "ZCS1.collections[0].set_label(r'$TCW, deg$')\n",
    "\n",
    "\n",
    "GCS1 = plt.contour(X, Y, np.transpose(G1), levels=Glevels, colors='blue',linestyles='dashed')\n",
    "\n",
    "Glabels=plt.clabel(GCS1, inline=1, fontsize=10, colors='blue',fmt='%d',inline_spacing=0)\n",
    "GCS1.collections[0].set_linewidths(1.5)\n",
    "GCS1.collections[1].set_linewidths(1.5)\n",
    "GCS1.collections[2].set_linewidths(1.5)\n",
    "GCS1.collections[0].set_label(r'$g$'+r'-load')\n",
    "\n",
    "\n",
    "for l in Glabels:\n",
    "    l.set_rotation(-90)\n",
    "\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted')\n",
    "\n",
    "plt.clabel(QCS1, inline=1, fontsize=10, colors='red',fmt='%d',inline_spacing=0)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "QCS1.collections[1].set_linewidths(1.5)\n",
    "QCS1.collections[2].set_linewidths(1.5)\n",
    "QCS1.collections[3].set_linewidths(1.5)\n",
    "QCS1.collections[4].set_linewidths(1.5)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "QCS1.collections[0].set_label(r'$\\dot{q}$'+', '+r'$W/cm^2$')\n",
    "\n",
    "\n",
    "HCS1 = plt.contour(X, Y, np.transpose(H1), levels=Hlevels, colors='xkcd:brown',linestyles='dashdot')\n",
    "\n",
    "Hlabels=plt.clabel(HCS1, inline=1, fontsize=10, colors='xkcd:brown',fmt='%d',inline_spacing=0)\n",
    "HCS1.collections[0].set_linewidths(1.75)\n",
    "HCS1.collections[1].set_linewidths(1.75)\n",
    "HCS1.collections[2].set_linewidths(1.75)\n",
    "HCS1.collections[3].set_linewidths(1.75)\n",
    "HCS1.collections[4].set_linewidths(1.75)\n",
    "\n",
    "\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "for l in Hlabels:\n",
    "    l.set_rotation(-90)\n",
    "    \n",
    "plt.ylim(1,40)\n",
    "#plt.grid(True,linestyle='dotted', linewidth=0.3)\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(r'$\\beta_2$'+' / '+r'$ \\beta_1 $' ,fontsize=12)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=12)\n",
    "plt.xticks(fontsize=12)\n",
    "plt.yticks(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",
    "plt.legend(loc='upper right', fontsize=12)\n",
    "\n",
    "\n",
    "plt.savefig('../data/jsr-paper/saturn/saturn-drag-large.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/saturn/saturn-drag-large.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/saturn/saturn-drag-large.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}