{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 06 - a - Jupiter - 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(\"JUPITER\")\n",
    "planet.h_skip = 1000e3\n",
    "planet.h_low = 50e3\n",
    "planet.loadAtmosphereModel('../atmdata/Jupiter/jupiter-galileo-asi.dat', 0 , 1 , 2, 3, heightInKmFlag=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta1 = 20.0\n",
    "\n",
    "runID = 'jupiter-drag-'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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))*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": 7,
   "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: 0.2136042777055991 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 9.0 TCW: 0.2881665681998129 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 13.0 TCW: 0.3363312108849641 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 17.0 TCW: 0.3727796818857314 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 21.0 TCW: 0.4020524562583887 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 25.0 TCW: 0.42639978193619754 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 29.0 TCW: 0.4470359181796084 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 33.0 TCW: 0.4646622138097882 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 37.0 TCW: 0.4799478743370855 deg.\n",
      "VINF: 0.0 km/s, BETA RATIO: 41.0 TCW: 0.4931755976722343 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: 0.21373630032030633 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 9.0 TCW: 0.2883251091479906 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 13.0 TCW: 0.3364456538547529 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 17.0 TCW: 0.37299971061293036 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 21.0 TCW: 0.40228760842001066 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 25.0 TCW: 0.4266443977394374 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 29.0 TCW: 0.4472813949250849 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 33.0 TCW: 0.46490313117101323 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 37.0 TCW: 0.48010109132155776 deg.\n",
      "VINF: 3.0 km/s, BETA RATIO: 41.0 TCW: 0.49332647401752183 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: 0.21389244812598918 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 9.0 TCW: 0.28854819819389377 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 13.0 TCW: 0.33678039567166707 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 17.0 TCW: 0.3734081579532358 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 21.0 TCW: 0.40273847387288697 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 25.0 TCW: 0.42712622942053713 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 29.0 TCW: 0.4477658009491279 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 33.0 TCW: 0.46537083882139996 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 37.0 TCW: 0.4805435933812987 deg.\n",
      "VINF: 6.0 km/s, BETA RATIO: 41.0 TCW: 0.4937456134648528 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: 0.21406033650418976 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 9.0 TCW: 0.28891514863062184 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 13.0 TCW: 0.3373322349143564 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 17.0 TCW: 0.3739885871691513 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 21.0 TCW: 0.403475334700488 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 25.0 TCW: 0.4278289279609453 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 29.0 TCW: 0.44855342135269893 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 33.0 TCW: 0.46613870085275266 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 37.0 TCW: 0.48124885826109676 deg.\n",
      "VINF: 9.0 km/s, BETA RATIO: 41.0 TCW: 0.49440613311890047 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: 0.2143949824385345 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 9.0 TCW: 0.28934974333969876 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 13.0 TCW: 0.3380891138294828 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 17.0 TCW: 0.3749029158279882 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 21.0 TCW: 0.40439487367257243 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 25.0 TCW: 0.4288948328758124 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 29.0 TCW: 0.4496152475767303 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 33.0 TCW: 0.467146047289134 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 37.0 TCW: 0.4821960561530432 deg.\n",
      "VINF: 12.0 km/s, BETA RATIO: 41.0 TCW: 0.4952961387389223 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: 0.21479340876976494 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 9.0 TCW: 0.2899809478985844 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 13.0 TCW: 0.3389524132726365 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 17.0 TCW: 0.3760254957451252 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 21.0 TCW: 0.4056377437154879 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 25.0 TCW: 0.4301202450878918 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 29.0 TCW: 0.4508201141070458 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 33.0 TCW: 0.468283904629061 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 37.0 TCW: 0.48325862638739636 deg.\n",
      "VINF: 15.0 km/s, BETA RATIO: 41.0 TCW: 0.4962898651283467 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: 0.21524633393710246 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 9.0 TCW: 0.2907290539587848 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 13.0 TCW: 0.34005805647029774 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 17.0 TCW: 0.3773473650217056 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 21.0 TCW: 0.40707180840399815 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 25.0 TCW: 0.43161840495304205 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 29.0 TCW: 0.45226021203416167 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 33.0 TCW: 0.4696499540004879 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 37.0 TCW: 0.4845340279134689 deg.\n",
      "VINF: 18.0 km/s, BETA RATIO: 41.0 TCW: 0.4974885430710856 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: 0.21567887389392126 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 9.0 TCW: 0.2915814334337483 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 13.0 TCW: 0.3413046869827667 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 17.0 TCW: 0.37874766992172226 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 21.0 TCW: 0.4086055943262181 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 25.0 TCW: 0.433280387231207 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 29.0 TCW: 0.453769122272206 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 33.0 TCW: 0.471119389992964 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 37.0 TCW: 0.4859042563402909 deg.\n",
      "VINF: 21.0 km/s, BETA RATIO: 41.0 TCW: 0.4987719744021888 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: 0.21626820602250518 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 9.0 TCW: 0.2925188715526019 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 13.0 TCW: 0.34265856415004237 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 17.0 TCW: 0.3803900198836345 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 21.0 TCW: 0.41040410441928543 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 25.0 TCW: 0.43501672772254096 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 29.0 TCW: 0.4554931251259404 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 33.0 TCW: 0.47263518304680474 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 37.0 TCW: 0.48730866410187446 deg.\n",
      "VINF: 24.0 km/s, BETA RATIO: 41.0 TCW: 0.500090451532742 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: 0.21680262633162783 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 9.0 TCW: 0.2935383872318198 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 13.0 TCW: 0.3441036602962413 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 17.0 TCW: 0.38206826794339577 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 21.0 TCW: 0.4122081699388218 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 25.0 TCW: 0.4367892465161276 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 29.0 TCW: 0.45714972517453134 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 33.0 TCW: 0.47416293861169834 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 37.0 TCW: 0.48871489811426727 deg.\n",
      "VINF: 27.0 km/s, BETA RATIO: 41.0 TCW: 0.5014068888776819 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: 0.21734431386721553 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 9.0 TCW: 0.29460557279526256 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 13.0 TCW: 0.345602418827184 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 17.0 TCW: 0.38378542231657775 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 21.0 TCW: 0.41404338288703 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 25.0 TCW: 0.438563992298441 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 29.0 TCW: 0.45876530148962047 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 33.0 TCW: 0.47562700958224013 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 37.0 TCW: 0.49006787584221456 deg.\n",
      "VINF: 30.0 km/s, BETA RATIO: 41.0 TCW: 0.5026777471066453 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-10,4000.0)\n",
    "        overShootLimit_array[i,j] , exitflag_os_array[i,j] = vehicle.findOverShootLimitD (2400.0, 1.0, -15.0,-4.0,1E-10,4000.0)\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/jupiter/'+runID+'vinf_kms_array.txt',vinf_kms_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'v0_kms_array.txt',v0_kms_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'betaRatio_array.txt',betaRatio_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'overShootLimit_array.txt',overShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'exitflag_os_array.txt',exitflag_os_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'underShootLimit_array.txt',underShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'exitflag_us_array.txt',exitflag_us_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'TCW_array.txt',TCW_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 0.0 km/s, BR: 1.0 G_MAX: 28.123401441184843 QDOT_MAX: 6620.818090179809 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 5.0 G_MAX: 28.123401441184843 QDOT_MAX: 9171.31992635625 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 9.0 G_MAX: 28.123401441184843 QDOT_MAX: 9895.565111584066 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 13.0 G_MAX: 28.123401441184843 QDOT_MAX: 10321.759363668096 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 17.0 G_MAX: 28.123401441184843 QDOT_MAX: 10628.786756903619 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 21.0 G_MAX: 28.123401441184843 QDOT_MAX: 10872.998698541747 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 25.0 G_MAX: 28.123401441184843 QDOT_MAX: 11065.380917028317 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 29.0 G_MAX: 28.123401441184843 QDOT_MAX: 11227.161144547983 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 33.0 G_MAX: 28.123401441184843 QDOT_MAX: 11363.200297799936 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 37.0 G_MAX: 28.123401441184843 QDOT_MAX: 11476.167535509627 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 0.0 km/s, BR: 41.0 G_MAX: 28.123401441184843 QDOT_MAX: 11579.143216703149 J_MAX: 593560.6703787534 STAG. PRES: 0.05446142114560911\n",
      "V_infty: 3.0 km/s, BR: 1.0 G_MAX: 28.25870861244563 QDOT_MAX: 6654.751508890209 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 5.0 G_MAX: 28.25870861244563 QDOT_MAX: 9222.503173433572 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 9.0 G_MAX: 28.25870861244563 QDOT_MAX: 9949.267489345517 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 13.0 G_MAX: 28.25870861244563 QDOT_MAX: 10381.468876994608 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 17.0 G_MAX: 28.25870861244563 QDOT_MAX: 10692.817240908442 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 21.0 G_MAX: 28.25870861244563 QDOT_MAX: 10931.980241415564 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 25.0 G_MAX: 28.25870861244563 QDOT_MAX: 11123.20209795268 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 29.0 G_MAX: 28.25870861244563 QDOT_MAX: 11286.73462563254 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 33.0 G_MAX: 28.25870861244563 QDOT_MAX: 11427.650496896615 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 37.0 G_MAX: 28.25870861244563 QDOT_MAX: 11545.314376716273 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 3.0 km/s, BR: 41.0 G_MAX: 28.25870861244563 QDOT_MAX: 11640.185889455539 J_MAX: 595354.7034801741 STAG. PRES: 0.05472347243625391\n",
      "V_infty: 6.0 km/s, BR: 1.0 G_MAX: 28.687277159711083 QDOT_MAX: 6761.083202890501 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 5.0 G_MAX: 28.687277159711083 QDOT_MAX: 9370.619933863161 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 9.0 G_MAX: 28.687277159711083 QDOT_MAX: 10114.069912369974 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 13.0 G_MAX: 28.687277159711083 QDOT_MAX: 10552.400020679994 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 17.0 G_MAX: 28.687277159711083 QDOT_MAX: 10868.904672971448 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 21.0 G_MAX: 28.687277159711083 QDOT_MAX: 11120.849776187604 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 25.0 G_MAX: 28.687277159711083 QDOT_MAX: 11319.389329149131 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 29.0 G_MAX: 28.687277159711083 QDOT_MAX: 11484.969251173641 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 33.0 G_MAX: 28.687277159711083 QDOT_MAX: 11625.369023714635 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 37.0 G_MAX: 28.687277159711083 QDOT_MAX: 11738.128673595116 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 6.0 km/s, BR: 41.0 G_MAX: 28.687277159711083 QDOT_MAX: 11846.848045522936 J_MAX: 600941.962688217 STAG. PRES: 0.05555323340495844\n",
      "V_infty: 9.0 km/s, BR: 1.0 G_MAX: 29.412088611638797 QDOT_MAX: 6940.133655299161 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 5.0 G_MAX: 29.412088611638797 QDOT_MAX: 9628.2555910856 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 9.0 G_MAX: 29.412088611638797 QDOT_MAX: 10393.253314046353 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 13.0 G_MAX: 29.412088611638797 QDOT_MAX: 10851.669132073657 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 17.0 G_MAX: 29.412088611638797 QDOT_MAX: 11180.317124423982 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 21.0 G_MAX: 29.412088611638797 QDOT_MAX: 11435.881729463228 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 25.0 G_MAX: 29.412088611638797 QDOT_MAX: 11639.68566424089 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 29.0 G_MAX: 29.412088611638797 QDOT_MAX: 11814.10310841768 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 33.0 G_MAX: 29.412088611638797 QDOT_MAX: 11961.54893475019 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 37.0 G_MAX: 29.412088611638797 QDOT_MAX: 12081.497530247967 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 9.0 km/s, BR: 41.0 G_MAX: 29.412088611638797 QDOT_MAX: 12188.501877127896 J_MAX: 610339.7160869257 STAG. PRES: 0.056956725111444444\n",
      "V_infty: 12.0 km/s, BR: 1.0 G_MAX: 30.42346976701272 QDOT_MAX: 7197.068442043545 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 5.0 G_MAX: 30.42346976701272 QDOT_MAX: 9994.275986354933 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 9.0 G_MAX: 30.42346976701272 QDOT_MAX: 10797.02657575086 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 13.0 G_MAX: 30.42346976701272 QDOT_MAX: 11273.088942405027 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 17.0 G_MAX: 30.42346976701272 QDOT_MAX: 11621.244279686163 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 21.0 G_MAX: 30.42346976701272 QDOT_MAX: 11894.517216795875 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 25.0 G_MAX: 30.42346976701272 QDOT_MAX: 12114.225215825589 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 29.0 G_MAX: 30.42346976701272 QDOT_MAX: 12295.187202360043 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 33.0 G_MAX: 30.42346976701272 QDOT_MAX: 12441.870730331451 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 37.0 G_MAX: 30.42346976701272 QDOT_MAX: 12574.115926623475 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 12.0 km/s, BR: 41.0 G_MAX: 30.42346976701272 QDOT_MAX: 12686.167603700022 J_MAX: 623484.4308107734 STAG. PRES: 0.05891492976327301\n",
      "V_infty: 15.0 km/s, BR: 1.0 G_MAX: 31.732463655778965 QDOT_MAX: 7537.861769057522 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 5.0 G_MAX: 31.732463655778965 QDOT_MAX: 10488.234357897958 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 9.0 G_MAX: 31.732463655778965 QDOT_MAX: 11338.686937448285 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 13.0 G_MAX: 31.732463655778965 QDOT_MAX: 11843.027874089228 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 17.0 G_MAX: 31.732463655778965 QDOT_MAX: 12218.5386957783 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 15.0 km/s, BR: 21.0 G_MAX: 31.732463655778965 QDOT_MAX: 12511.577086800833 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 25.0 G_MAX: 31.732463655778965 QDOT_MAX: 12745.313842175558 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 29.0 G_MAX: 31.732463655778965 QDOT_MAX: 12937.734673104183 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 33.0 G_MAX: 31.732463655778965 QDOT_MAX: 13091.5909681296 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 37.0 G_MAX: 31.732463655778965 QDOT_MAX: 13237.086059552761 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 15.0 km/s, BR: 41.0 G_MAX: 31.732463655778965 QDOT_MAX: 13351.999875333666 J_MAX: 640555.5001101592 STAG. PRES: 0.06144948794916808\n",
      "V_infty: 18.0 km/s, BR: 1.0 G_MAX: 33.342814221473915 QDOT_MAX: 7969.121670998365 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 5.0 G_MAX: 33.342814221473915 QDOT_MAX: 11120.2791820013 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 9.0 G_MAX: 33.342814221473915 QDOT_MAX: 12030.571714498848 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 13.0 G_MAX: 33.342814221473915 QDOT_MAX: 12589.657518416201 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 17.0 G_MAX: 33.342814221473915 QDOT_MAX: 12994.900235379775 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 21.0 G_MAX: 33.342814221473915 QDOT_MAX: 13309.47983415835 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 25.0 G_MAX: 33.342814221473915 QDOT_MAX: 13561.080874966116 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 29.0 G_MAX: 33.342814221473915 QDOT_MAX: 13772.104991136222 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 33.0 G_MAX: 33.342814221473915 QDOT_MAX: 13944.486526203913 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 37.0 G_MAX: 33.342814221473915 QDOT_MAX: 14088.40755367261 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 18.0 km/s, BR: 41.0 G_MAX: 33.342814221473915 QDOT_MAX: 14222.734976794563 J_MAX: 661547.9906496889 STAG. PRES: 0.0645673203749776\n",
      "V_infty: 21.0 km/s, BR: 1.0 G_MAX: 35.25629610488565 QDOT_MAX: 8504.027529309797 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 5.0 G_MAX: 35.25629610488565 QDOT_MAX: 11912.966318016492 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 9.0 G_MAX: 35.25629610488565 QDOT_MAX: 12914.403584313537 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 13.0 G_MAX: 35.25629610488565 QDOT_MAX: 13518.638503207088 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 17.0 G_MAX: 35.25629610488565 QDOT_MAX: 13967.8528877019 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 21.0 G_MAX: 35.25629610488565 QDOT_MAX: 14314.534807326258 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 25.0 G_MAX: 35.25629610488565 QDOT_MAX: 14595.323421676849 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 29.0 G_MAX: 35.25629610488565 QDOT_MAX: 14818.355919328198 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 33.0 G_MAX: 35.25629610488565 QDOT_MAX: 15015.942006157587 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 37.0 G_MAX: 35.25629610488565 QDOT_MAX: 15181.517458124772 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 21.0 km/s, BR: 41.0 G_MAX: 35.25629610488565 QDOT_MAX: 15317.689902460526 J_MAX: 686728.7661683634 STAG. PRES: 0.06827213416877696\n",
      "V_infty: 24.0 km/s, BR: 1.0 G_MAX: 37.46656555434994 QDOT_MAX: 9156.945774694308 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 5.0 G_MAX: 37.46656555434994 QDOT_MAX: 12897.214440059095 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 9.0 G_MAX: 37.46656555434994 QDOT_MAX: 14009.792674972136 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 13.0 G_MAX: 37.46656555434994 QDOT_MAX: 14681.731207653429 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 17.0 G_MAX: 37.46656555434994 QDOT_MAX: 15195.350787521085 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 21.0 G_MAX: 37.46656555434994 QDOT_MAX: 15569.990822765183 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 25.0 G_MAX: 37.46656555434994 QDOT_MAX: 15881.126485980409 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 29.0 G_MAX: 37.46656555434994 QDOT_MAX: 16146.753124059203 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 33.0 G_MAX: 37.46656555434994 QDOT_MAX: 16367.106174402867 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 37.0 G_MAX: 37.46656555434994 QDOT_MAX: 16533.02524918924 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 24.0 km/s, BR: 41.0 G_MAX: 37.46656555434994 QDOT_MAX: 16705.67130415972 J_MAX: 716274.8950910422 STAG. PRES: 0.07255125420676158\n",
      "V_infty: 27.0 km/s, BR: 1.0 G_MAX: 40.00461875987526 QDOT_MAX: 9950.2284184526 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 5.0 G_MAX: 40.00461875987526 QDOT_MAX: 14109.418169015195 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 9.0 G_MAX: 40.00461875987526 QDOT_MAX: 15362.234549951985 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 13.0 G_MAX: 40.00461875987526 QDOT_MAX: 16139.194596085326 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 17.0 G_MAX: 40.00461875987526 QDOT_MAX: 16718.889462812625 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 21.0 G_MAX: 40.00461875987526 QDOT_MAX: 17148.124416030307 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 25.0 G_MAX: 40.00461875987526 QDOT_MAX: 17503.635408420476 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 29.0 G_MAX: 40.00461875987526 QDOT_MAX: 17805.50772257199 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 33.0 G_MAX: 40.00461875987526 QDOT_MAX: 18047.683334006007 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 37.0 G_MAX: 40.00461875987526 QDOT_MAX: 18244.37977537699 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 27.0 km/s, BR: 41.0 G_MAX: 40.00461875987526 QDOT_MAX: 18430.830014775995 J_MAX: 750642.7164227875 STAG. PRES: 0.07746540591409933\n",
      "V_infty: 30.0 km/s, BR: 1.0 G_MAX: 42.85957081318483 QDOT_MAX: 10908.915869994991 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 5.0 G_MAX: 42.85957081318483 QDOT_MAX: 15601.645205669738 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 9.0 G_MAX: 42.85957081318483 QDOT_MAX: 17038.451274928273 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 13.0 G_MAX: 42.85957081318483 QDOT_MAX: 17955.22228529556 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 17.0 G_MAX: 42.85957081318483 QDOT_MAX: 18613.006183842313 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 21.0 G_MAX: 42.85957081318483 QDOT_MAX: 19110.252164980666 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 25.0 G_MAX: 42.85957081318483 QDOT_MAX: 19523.30405014775 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 29.0 G_MAX: 42.85957081318483 QDOT_MAX: 19872.270641168612 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 33.0 G_MAX: 42.85957081318483 QDOT_MAX: 20149.123993962516 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 30.0 km/s, BR: 37.0 G_MAX: 42.85957081318483 QDOT_MAX: 20380.3404375406 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\n",
      "V_infty: 30.0 km/s, BR: 41.0 G_MAX: 42.85957081318483 QDOT_MAX: 20588.780002122272 J_MAX: 790386.6944246079 STAG. PRES: 0.08299270637133607\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/jupiter/'+runID+'acc_net_g_max_array.txt',acc_net_g_max_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'stag_pres_atm_max_array.txt',stag_pres_atm_max_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'q_stag_total_max_array.txt',q_stag_total_max_array)\n",
    "np.savetxt('../data/jsr-paper/jupiter/'+runID+'heatload_max_array.txt',heatload_max_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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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YIUSQEGKbECJZCPGXEOIVc3qsEGKrEOKIEGKREKLSGbcMOp/LyYmjKMg8696KLMJahR08B4WEEhQSWmae0FAVNIrjySFxAdBTStkGaAv0E0LcAswA3pNStgAuAg96sE12EXPMxF0fZfJjUtkOf13CO+9A06aF3u6qGPl5OeTn5ZSZJydHBY3ieExgpcLy3+BvDhLoCSw2p38JDPVUm+wlub0v1x8PYcLQnzjFKfdW1rYt3Hmnc5oDXkBm+iky08v+Nzx1SgVnWLNmDWvWeGiR8Ap++ukn3nzzTR5/3H32rz266CSE8BVC7AbOAT8DR4FMKaX5BDcngUo5g0mv54MBA28dSXSvBlSvXqqXDdfUIp2hX79+9OvXr9Tn48aNY//+/QBMmDCBl156CYD169dbvdGdOnWKJ5980uG6+/Tpw/PPP4/ejaMjjwqslNIopWwLNALiALtcpuvSdeR1zLMG/eyKGS522pTPO9et4sDy6e6tSEpl36kKz2Urik6dOrF9+3YAsrOzOX78OKA8sFs82P3888/07u3cAuP777/PuHHjSn0+e/ZsOnbsSMeOHQEcPmxbIds6UspM4FegMxAhhLCsVjeC4mPOgKgAQnaEWIN/YsXYtN3a2YfpLwXwaLevMOLGwwjr10ObNvDTT+6ro4qh0+kYMmQI/fr1Y9iwYVZbTFcSFxfHtm3b0Ol0BAQEYDIfpbQV2A0bNtCtWzceeughunfvTn+zcfekpCQGDBjA4MGD6dy5M3PnzqVXr14MHDgQKSUff/wx27ZtY+vWrZR2qCYxMZEdO3awY8cOADuO5hfFk6vEUUKICHM8GOgNHEAJrsV04Thguafa5ChGP8GMlwI4VDuDL3GjC8v4eOXlriopsCckFJqQ0OvV/YIF6t5icmLRIgB8LmURc08CLF2qntthcmLZsmV2WYlo27YtycnJJCcn06ZNGxo3bkxqaiqpqanExsYipSQ3N5d169ZRt25dNmzYwMqVK63v+/v788MPP3D77beza9cu1q1bR8OGDdm1axcTJkxg4cKFPPnkkwg3bc95ch82GvhSCOGL+qH4Vkq5QgixH/hGCPE6sAuY48E2OUXdo5eo/8xjZH/UlZrRbjCI7e8PiYmuL9dLaNgQyjCqWCIpKSm0a9cOKNtKhMWp8+bNm+nYsSPp6emsWrXK6nHdIsiHDx+mS5cuAPjY2Pm66aabAGjQoAFRUVHW+MWLFx1rsJN4cpV4j5SynZSytZTyJinlq+b0FCllnJSyhZRypJSywFNtchYhoePvBXyzb2r5mZ3FYFA9zB9/uK8OT5KUVGhCwt9f3d99t7q3mJwYPVrdRofjuzFJuTUBu0xOxMbGFrMSYTAYOHu2+N55mzZtmDt3Lu3ataNDhw7MmjXLahLGMn9t2bIlW7ZsAbAOm4EiPadt3FPnyjXVRCdIaeHD9cdDmNI7iSMccU8lQigbKp984p7yKzHZ2So4wtChQ4tZiUhNTWXq1OI/qnFxcRiNRkJCQoiJieHcuXPW+euOHTvo2LEjgwcPJi0tjfj4eAYNGnS1n+QyNIsTV4EvviRuvom3Om9yj0rh4cPQrBn4eacGqbMWJw6pLA6fh7VgWXAKCwsjMjKSnj172v3ut99+y6hRo5yruBxcYXHCO/8SKgl9fizgrcG/s++H6dx0+/Our+Daa11fZgVjjy6xqxg+fLjD77hLWF2FJrBXwU/9fXnsf4Fs6buQbTyLL76ur+SLL2DnTvjvf11fdgVQnh6xK6gsbjXcgTaHvQqMfoJ5D/pzKiCdecxzTyUpKbBrV5XRLbZHl1ijdDSBdQHXbcvmpq6PkpPuBo9z//638iVbitlOb8MeXWKN0tEE1gXkhAnCLxiZd/IN1xfuax5mV5Eetnb9JtSu36TMPE2aqKBRHE1gXcCh633o+FcQL7dbxglOuL6CdeuU5/aDB11ftofxDwwq09UkKDeTrnI1WdXQBNZFSB+BNOhZ9OPdri/8hhuU86wqQN6lTPIuZZaZJzNTBY3iaALrQu6ak8+kwRs5uMXFesbR0bBwIVxn1+GmSk32hbNkXyjbcsfZsypoFEfb1nEhX93nx5mGPqTd/BkbuReBi5Up0tLUXLZxY9eWq+E1aD2sC9EFClYP8uVvcYSVcoWLC9fB9dfDq6+6tlwNl1HlLE5UF3p+n0Wz9iPR52W5rtCAAJgzB5591nVlVjHWrl1Lt27dSEhIYOLEiRiNJauzJiUlFdMxtk3TLE5UMzKiBBcjTHx9/kPXFjx8eJVUV3QFGRkZTJs2jTVr1pCUlERUVBSffvqpU2W50+LE1aIJrBv441Zf+v0ayOSYj8jGwWMn5bFzJ3zo4h+CSkZsrAqOsHLlSu655x5q1KgBwFNPPcWyZcvKfCc7O5vBgwfz119/FUnfsGED3bt3x2QyFbE64QqLE1eLJrBuJCirgOXLHnBtoUuXwvPPO37+zIsICFDBEdLS0mhg458oKCgIXRk2sbKzs7n77rt58803ufHGG63pFosToaGhLF++vJjViepkcaLa8eRrlxj9wRJOn9hFg3rtXFPoxInwzDNQs6ZryvMQb49PAEBXoMy3BgSGFMvT+tZB9Bk7iQsX4NPnEug+5D66DLqPS5kZhEWUfYg9Ojqa0zZuTvLz8/H1Lf0wxuLFi3n44YeLCCsUWpwASrQ6UW0sTlRH3nvWn95bw3ih3n9cV2itWlXeBGp6uuOamP3792fevHnk5uYC8N5773HHHXeUanXi/vvv58SJE8WGzbbz15KsTlS0xQmth3UjGXV9yKgr2c9K9pn2cJNP66IZcnKc80mRkqKsUbzyitc4gJ40KwnA6rmuPPXE0c8nWQ+wl9e7AtStW5fnn3+efv36kZmZyQ033MDChQv5559/mDFjBp999lmR/EIIZs+ezZgxY4iMjERKia+vLzt27LDaJx48eDA//vgj8fHxhIaG8mwlWKHXLE54gFoXBa2C41gR9Eth4vHj8MQTMHRooa0je7l0SQnq9OkweLArm+pSSrI4YQ9Xa3Hi2LFjjBo1ih9//JFNmzbZZXVi/vz55OTkULt2bc3iRHXnQqRkO3vZwAa6010lNm4MPXrACy/AvfeCjwOzk7Aw+Osvr/R0Z9EjdqdT5yZNmrB161bAPqsTixYtYvbs2SxZsoS6deu6rV2uQJvDeog88nja9BQmTHDmjFrp/fLLwt7V0ZGOEOqd8+dd3lZ3Yo8usacZPXo0mzZtqvTCCloP63aESfL4u3o+m+DPyZDT7P50PO3n7IIWLeDbb9UVnPPXM3iwOtayaZNL2+xOoho2KzdPs/KzVFs0gXUz0kfQ4KTk+36XSa+bjyF9HvrXF+PfZ6DKUFAA+/erOe2QIY4VPnYs5OcrYfeS4bGvX/mWM6qIcQ23cNVDYiHEc65oSFXmpRkBXLffxOmGPty+oSaf9TmmHuj1EBgIMTFqiGzjEsIuxoxRQ2ovEVaAnMwMcjLLdr2RkWGXd45qicMCK4T41iZ8BzzkhnZVKXSBgukvBSCFmsvO0L1Gtswq7Ep+/10NbVevdrzwy5fhq69UT1sJuXIXIifrPDlZZc+7z5/3uql5ubhqN8aZIXG2lNIqpEKIWS5pSRXnkycCuDXJQMMTJi7EGHmHd3ll6wB47z3lDOr998EBg9dWNm9WLi+CgtThgEpEUFAQ58+fp3bt2m5T1fMGpJScP3+eIBfYvXFGYKddcT/lqltRTfinuQ+vPatj8nsQ9e5MCnasI3DgHUrQYmIKDa45Qo8eyi9NfLzL23u1NGrUiJMnT5Kenm5Nyz5/BoCLeabSXuOMyoKp9CxeR1BQEI0aNbrqcjTFCQ+zpP9lOv9m5MNngjEN6MuU1ouKa7pfuKBUEKsgFp1ii+ZTSSSoLCSVnqVK4IzihF1zWCFEuE38QSHER0KIJ4QQxTW4Ncrk8c8CyQ8WfDtG8H7H3zgUYGPLODsb3npLnXndv9+xgt99V7NGUQ0oV2CFEG8A+4UQJ4UQHwHDgS3AtcB8N7evynG6kQ//G+9H141G9Oh5lmfBaFQLTt27K728kSPhtdccK3jvXnVW1gtGTOWxapUKGsWxZw57OxADXA8kA3WklJnAfCFEshvbVmV545VAAGqdN7Cl9hZ+991C1zNn1ORtjtmfdUKCskfcq5d9hX72mdd6ubuSEG3cVir2DIkDgDAp5V/AVLOwIoRoAe7w/lQ9iDlm4plpOvLIY6LpSeT990HnzkpdEWDmTMd6S4uwZmd7/WrNxx+roFEcewT2v8BRIcReYKwQYo8QYg+wA6hvc6/hACea+NBmp5E75+k55nOCpSxVK8XR0SpDp05w222OFbpjBzRsCGvXur7BHuTbb1XQKE65Yygp5YdCiNlAPbTDAi5l6sxAPnqwgNwaWZhW3odpR1N8Jk4szJCSog6rR0bad5qndWsYNw6aNnVbm6+WR95cXNFN8GrsmvRIKXXgDqcx1ZudnXyZ9moAvdYaOFvHh8+/H8RDTZqo/YwvvlAaUF26qON0H31UfoEBAZXeQJs9h9E1SscrVikuH89DtjCAQPXxPqjZsw9Kj9YHpG2ar/nemibU1Tb4gfAV6l/AfG8Jws+c7q+C8BfWOP4gAsz3ASqIAKHigSACC+PWe9t4kPkds+bPiqF+rBiq/hvCdXO4c2oBNXYehK5d1UQuJEQZED9wQF3t4dgx2L4dRoxw/h/dTWxeMReALoPuq9B2eCvlCqwQojOwRV6lhoUQIgaYhxpaS2C2lPI/QohawCKgKZAKjJJSFrFoVSvQRM84iV6CNKldEJPJvLYipTVuskm3BKNeXQ1G9Z4lGAwqzWCwubfE9Squ16u4O9ZwfAJBBIEwC3JdP8niMzmsD/qIBS3acHHDBoK2biVKCJ7MzuanZ5/lRPPmBAUFERwcTHBwMCEhISWGa999l1pr1nC2TRuCo6IIDQ3Fr5KsIG9eORfQBNZZytV0MusK3wwcBtYAa6SUZxyuSIhoIFpKuVMIEQb8CQwF7gMuSCmnCyEmA5FSyiIngDp2rCl3bKs4r90mk1TCa1AeM3Q6JcyWa0GBCjqduubrIL/Ah/wCSYFOcDlfUKCT5OdDfgEUFEgK8s3v5UN+vqTpKeicAv9tCbr8m9FfhtBLl0jIyCCsoIDXgoK4fPkyly9fLteyfAPUoMF2DhMQEECNGjUIDQ21Bst9WFiYNc0St71eGbfcl2WVsLKTmZnJzJkz+frrrxkyZAjPPfcc9evXLzHv3r17CQkJoXnz5i5tgzOaTnarJgohrgP6A32BcOBXlAD/LqV0WG9QCLEc+NAcEqSUaWahTpJSFrHmU9EC6xGWS3gR2OML+26Ac+/CokXqYMD06WoF2YzRaLQKb15envWal5dHbm4uubm5ReK5ubnk5OQUub906ZI1zRK/dOmS1eqgPYSEhBQR4itDaGgoNWvWLFHgrww1atTw6AGBp59+Gp1Ox0svvcQzzzxD27Zti7jnMBqN+Pr6sm3bNgYMGEDv3r2ZP38+fn5+bNy4kenTp7Nt2zYef/xxJk+eTGBgoMNtcKtNJynlQeAg8J4QIhjoAYwE3gUc+5UQoinQDtgK1JNSppkfnUENmYuQnq6nY1zhD0viQ5CYWMVOfwwRsExCLyM0PAC6l2DgI2rVd/FieOMNZZ0iJgbfUaOsPWKpXL4MDz8Mt96qbBnbiclkIi8vr4gQW+LZ2dlF0koKaWlpHD582Hp/5Q9AK3MntveKMZqPj49VwHW6JwgKCuK661ZQs2ZNwsPDi4SIiAgiIiKKxCMiIqhZs6bVfnBZ5ObmcvbsWUaOHElUVBS9evVi9+7dpKWlER0djclkwtfXl7S0NNauXUvjxo3p1q0bAAUFBXzwwQeMGDGCVatWMWTIEL7//nvGjBmDlLLcH53Zs2cze/Zsy63DK3BOTWyklJeBVebgEEKIUGAJ8KSUMvsK265SCFGsy4+K8mfHtgJnmupdfABcBHwMUP8o7GsJ7durhbWnn1ZKEVOmQLduhfu1pREUpAz8XrrkUBMsglPmj4EDmEwmq5Dn5OSw8LW7MBqNvH7nq1ahzs7OtsazsrJYsWIA2dkGMjMXcPz4cbKyssjKyiIvL6/MuoQQ1KxZs4gQ2wr36NGj6dKlC+np6QQFBRFjHrXExsbyxx9/cOHCBaKjo61nV6dNm0b//v05d+4ceXl5+Pn5sXz5cpo2bWo1MB4bG8upU6es9ZdHYmIiiYmJlvwOH9P36EqEEMIfJaxfSSmXmpPPCiGibYbE5zzZpkpFmIAwwCjhw0yYNRCenQEP2dgISEqCJUvgX/8quywhYM2aCrdG4ePjQ82aNalp9lQQFhYGKJu/pVF4WmdrkXS9Xk92djZZWVlkZmZar5b4xYsXyczMtF4zMzNJSUmx5mvbti1dunQhPz8fKaXVD4/JZMJgMFiHtb6+vixdupQGDRowcOBAkpKSiIyMBODEiRNERkZSp47qHKOiojAYDFy6dAk/Pz8CAgLcOrf3mMAK9fMzBzggpXzX5tEPwDhguvm63FNtqrTkAvt18G0etOlTmJ6SovZkhw2zrxyLsO7dCzfdVOHCe7X4+/tTu3ZtateufVXlhIWFkZGRYV05T09Pt66wW5g6dSp9+vRh/fr1/PnnnwQHBwPKBUhAQAD+ZmshOp2O4OBgfHx8eOSRR5g/fz41atSwDtdLuoaHh9OqVSun2u7JHrYrcA+wVwix25z2AkpQvxVCPAgcA9xjxdmb+A3YB7Q2ghwPYiV8+inMmKGsS0RF2W947aefoG9f+PFHGDTI3S33Cho2bMjff//NJfN0Ye7cuYwcObKIM60HHniAXbt28cknn3Dw4EEOHTpEjx49iI6O5sCBA1bfs8eOHaN3794EBQUxcuRImjdvbh3CW3r+9PR0jhw5Yu319Xo9I0eOdK7xUkqHAtAb+Axoa75PdLQMR0OHDmFSGkX1Cp2Q8imk/DBAyrjrpLzxRinXrZMOo9NJ+d57UmZmOv6uG5j5aHc589HuZebp108Fd7Jy5UrZrl072a5dOzlmzBiZk5MjFy5cKH/77TdpMpmK5O3du7fctm2blFLKjIwM2a5dO3n69GkppZSxsbHy6NGjdtdrMplkXl6ezMrKksAO6aAsONPDPgCMB6aalR7aOvdToVEmnwC7gRQdTDgH96aBCCg8wWPv8NbfH5zwJl6ROGOLzlEGDBhAmzZtuHjxInXr1qVGjRo0b96csLAwhBAYjUYlIH5+3HjjjdZ5ae3atXnggQfo0aMHRqORKVOm0MwBQ8pCCKviizM4bCJGCDFbSplojk8HekkpOzlVu51Ui33YspjuB5e6wLT1jrn0sGXTJvjhB3VsrwKxx0SMNyDNfmRDQkLs2koqCU/51rEaz5VSThZCPO5EGRqOkKqH7N9AngCaOFfGjh2wcCE8+6yaA1cQ9giqxdjGiy+6ty1XgxDCZVtfDtVrTw8rhAiXUmaZ4w+hlB4OAf+TUpa9OeYCqn0Pa5Tg6w/cBj5O2k6x2C12galNd6MZYSsdZ2w6DUOz6eRZfAVggNNJsG66c2UEBakgJXjIW3hpZJ8/y7GDf3Li72Qu52ZXaFu8Dc2mkzeReBn2TIGUCRBQ07ky+vUrVKrwMCf+Tuabd5/g4tkTXDh7gsYt25OTlcE1bboxeuJ/CAmt2p7lXYFm08mbeBf4NRD83nS+jNGj4a67KsS64rw3HuLe5z/jjaUpTP7fHzSIvYE3lhzl2vbdmfeG5vHFHuzpYS02ndIAhBB3mdMbAwaLPScpZWv3NFHDyrUCyAc+gLwxENLG8TIeeMDVrbIbo0FPvcbXAtD0+o6c+FsN0LoOup+189+y5rtKRaYqjWbTyRt5+TIs7ww7Mot7DbAHo1GtGF97Ldx8s8ubVxpRDZrx4/9e4bqOvdj562KaXq/WW4wGA8Jma2TJEo81yeuwSwCllDop5Qkp5bHSgrsbqmFDJwl9DaCf59z7BQXwzDMwd65Lm1Ue4178Al1+HmvnzyCoRk1GP/UfAHQFeYyb8rlH2+KteIVvnWq/rVMqNUEcBeHEGDIlRVlXdFYRw8XMnjqGxNe/AZSrXIA3r2Kq7g24zbeORiUl+TJM7OrcAlKzZkpYL1/22ALU3NfuZ98fazAZixsoOXv8kDX+xx8qaBRHE1hv5ncdfHUIUr927v1Dh5QVi+WeOdHYrFVn1syfwbO3N+Srtybw9+5NNk+9++ifp6gcpvQ0nONR4E4gchLIoeCoM8HmzZV/WZtjZe4kfmgi8UMTyUw/zfZfFvHdB0+Tdf4MHXuNIu9SxSpzeAtaD+vN+AiIFCAzYd09jr/v5wcLFkBcnMubVhYRUQ3ofedTvPD5NiZ9nERIaAQhYZEebYO3oglsVWDRZei9FH76r3Pv5+Sow/EOWEx0FVENmzHwgam8OG+nNa1RIxU0iqMNiasCIwAD0PMdkInKOrkj7NkDkyerhShnLSHYyel/9pO86QcyzynDZRF1G9K22xCiYwu9GixY4NYmeDVaD1sV8BNwtwCfDMiZ5Piqb5cuyhWIm4V19ZdvMuflsQgEzVp1plmrzggE/3v5LlZ/WcX3cFyFoyYqKiJUSxMxzoSjSNlYSPnlVLtNlhTjwgXn3y2HF4Y3l3pdQbF0g14vpwxvYb3/v/9ToaqDEyZitB62KhEDJEi4ZhZIJxRN1q9XHga2bHF50wB8ff3JTD9VLP3iuZP4+BbOznbvVkGjONoctirhK+ALgDyQj4JwcDLYqROMHeu2bZ7RE//De0/0pm6jFkRGqVWli+mnOHfyb+56RnO5bg+awFZFTJfhjW/B1wRTFtr/XliYMqfqJm68uQ8RdRqSfeEc3YYo6/cRUQ2JvTHOo351vBltSFwVEcBhPRz8Dkypjr9/9qzyNnDGYSeF5SKEILhGTdr3GEb7HsNodtPNmrA6gCawVREhlI+FuRK4A2TZ7imLkZkJ335bYQq9116rgkZxtCFxVcVfACY4fQg+7ALTtoC9Pl9atoQTJyC8Yky2FDp307gSrYet6qy9DP/dAfs+cuw9i7D+8QdkZbm+XRpOoQlsVec+4ADQairIo469e+IExMd7/GBqYqIKGsXRhsRVHSGgEUAeLLsVbloL19hpfismBr77Dm67zZ0tLMbhwx6tzqvQetjqQrYRHj4Drw1yTHVx6FAIDVV2oBx0Dq3hejSBrS7UFPAL8MkFkA4OcU0m6NMH7r23QsyjahSiDYmrE60FkAf5r8OayzDsNfve8/GB4cPVQtRV7pm2vlXzUXs1aAJbHXn/Mkx9Hf7qDNcPsO+dCRMK4/Y6ky6BPmMnlZunbVuniq4WaEPi6shTwGoBLR8B6aBplhUrlLeqy5fd0TIA3n9fBY3iaAJbHQkU0BsgHZJ7wCkHzEr7+SlhddKh1tvjE6w+YjUcRxsSV2cuF0D/PRDXHZan2vdOv35qAcpJe8ZdBt5Xbp6771ZXzfJEcTSBrc4EC5gv4bpzYPoQfP5l33s+Psrf7OTJ8NhjcM01dlfZZdB95eY5edLu4qodHhsSCyE+F0KcE0Lss0mrJYT4WQjxt/mqmc7zND0FNMgH+Sz89r7972VkqC5w7VqHqruUmcGlzAzH2qhhxZNz2LlAvyvSJgPrpJTXAOvM9xoVwdzL0O0p2PSVffkbNVKGyP9lZ69s5tPnR/Dp8yOcaKD7SU5OJj4+npiYGF5++WXyzV7rpXnvefXq1QwYMIDbbruNIUOG8Pfff1vf3bZtGw8++CDDhw9n7969bmujx4bEUsqNQoimVyQPARLM8S+BJOC5K981GCSnTknrToLt1TbYptnm8/Ep/R3bYMlXPFSD85p3ASYBXZ4F2R9ErfLfsfiF3L8fjhyBwYPd2kR388ADDzBt2jT69etHly5d6NWrF/Hx8db//9atWzNjxgwMBgPbt2/nzTff5J133iEyMpIpU6YwZMgQAgICmDx5MgsWLCAy0vUDxoqew9aTUqaZ42dQLi2LcfhwHo0ae65RxZFWYfbxoVi8pODrW/b9lWmWeIn5bPJcmc+SZvvMz694up9f8XTbNH9/8PWV+H12jtDL7fDjCQz1ovH19cXPz6/McN3TTxN07BhHmzTBLzgYPz8//P39i+Tx9/fH398fiUSU45ajc2cP/bfakJKSQp06dejQoQMAI0aMYMOGDcTFxREUFARAw4YNadiwIQDBwcF89JE6AbVixQqio6OZMGECPj4+zJkzh4MHD9K5hA+ZPXs2swvPD9ZxtJ0VLbBWpJRSCFGi3lujRlFMmlgXEEhpsuRXgcIhi0oDMJmvKo/JVBiXsnRLkSZT8WcmU/Fr0TQwGk3mdDCZVNxoVHH1XJrTCutQzwvTTCaVT0owmgrT9HooMClVXqNRmN8R5vxFgyXNYLBNl0XSDIaytQsFBnZxnEtMopud/3f1zdczdmg8DLxeGcR4ISDAKtS2wm0RbH9/f1av9i+Wx/LsyrylBdt8AeY6bUPnzp1p1qwZJ06coEGDBlbhbNasGWvXrsV4heOu7777jlmzZnHy5Enef/99IiMj2bJlC507d6agoIDg4GDatWtHSkoKN998Mz5XrKYnJiaSaD6KJIRweDJf0QJ7VggRLaVME0JEA+dKylSzZiMSH93h4aZVEqQJMAK2VxPKcrglzXhF3DYYit1Lqcdg0GE06jAa9ej1+RgMOgwGPUajDv/1+6ldoxuHWrVHr9djNBoxGo3WuF6vx2AwYDAYiqbp9dTat49TLVqUmM9gMHBq02yklEwaehd6vd4abPNdmW57zcvLK/asrCDL0X2eO3cuzZo1w2AwIITA13zIX/3YSuu9hR49etCyZUuWLFnCzp07GTBgAAUFBdYfAICgoCB0Oh1SSqZMmcKKFSuK/FgEBAQQHx/v1J9DRQvsD8A4YLr56hk3at6E8MHVa4NCgH8A+JeW4V6beEqK8ghgD4sWwbRp8NNP0Lt3iVnePq5WlSe98UapxQwfrq6ucKpnNBoxGAzodLpiwqzT6ahXT83C6tWrR1pamnW+mpaWRlRUVLEesk6dOtSpU4fWrVvTsGFDnnnmGWrWrEl+fj5GoxE/Pz8uXLhAZGQkPj4+1KtXj9jYWGt9Op2O3Nxc8vLynPsgRw0ZOxuAr4E0QA+cBB4EaqNWh/9GnSWpVdK7HTp0cNZWs8bVsGaNlL6+Uq5ebV9+vV7KuXOlNBpLzTLz0e5y5qPdyyyme3cVPE3z5s3l0aNHpZRSdurUSf7+++9FnmdkZFjjKSkpMjo6WhYUFMjNmzfL7jYNjo2NlceOHSu3PpwwJO7JVeI7S3nUy1Nt0HCQ7t3hhRegm52zWT8/GDdOxbOyIDgYAgLc1z4X89///pdBgwah1+u544476NKlC2+88QatW7dm0KBBzJw5kz/++IOgoCAMBgMffPABAQEBxMXFERMTw7BhwzAajQwbNozGjd2zSiqkF5xv7Nixo9yxo5rOYSsLer3ybhcRUX7ezExo1w5GjICZM4s8sugRT5qVVOrrCSoLSaVncRsFBQXo9XoCAwPx9/cnKysLf39/QkJCOHPmDBkZGej1evz8/GjVqpX1vZMnT7J582aMRiODBg0iLCys3LqEEH9KKTs60r6KnsNqeANSwpAhSmB//bV8PeKICHjwwRJNy9ijS1wRgmohMDCQwMBC73/hNpYj69evT/369Ut6jUaNGjFq1Ci3t08TWI3yEUJZmzAY7Ff6nzq1MG4wqOEy9ukSa5SOdrxOwz7GjCk8RpOWVnZeWz78ELp2BfOqqD26xHv3KlXlkigosL/qqogmsBqOcegQXH89zJplX/6mTaFJE6u2hj26xOPGKc0rC0rxRcm8k9uXVQZtSKzhGC1awCOPwCA7bTMNGlSYV6+n950TyzUvYzIVdTrQoQPs2gUhIaDTOdnuKoLWw2o4hq8vzJihbBZLCb/8Yp8lxdxcuO022vxxgDbdbi8zq8lUaIEmOxuOHlW9q0W1sjqjCayG8yxerDSafvyx/LzBwdCkCWfCAzlz7FCZWUePhr594bXX4I471Bn5+Hg1FR5ROU/meQxtH1bDeUwmpY44Zox9VhSl5O0JPQCY9MQs5XSrlFXnVavg4EFlkeaGG2D7dlXdzTe78gMqFmf2YbUeVsN5fHzgzjuVsGZkQI8esHt36fktQl1QAHFx8PLLJWbr1Qvat4eJE9WR2/vvh48/hk8+UfHqjLbopOEaTp9WxpjsmWQGBsJbbylljBLIyACLfkK9erBlC7z+upL3SeWbNa7SaD2shmto3RoOHICO5hHeF1+o1aLSGD8eGjRQC1aPPaacbplRZ5ZVXK9X8j18OAwbVmEuaysNmsBquA6zNhOZmfD00/Duu+W/k5sLO3eqCauZtm3VcHjDBnj4YTVEtlAdrPWUhTYk1nA9ERGwb59aGQb4+2+lvnTHHcXzhobCxo2F91u28EnXv3k99W7eeUcQFwfP2Vj5mjvXnQ2v/GgCq+EeGjQojL/zDnz9tVqUKglbtaZPPiH7m1/Z0WkEP20KLpa1tZ2ubasq2pBYw/18+CFs2gQWK4IpKeq+JD7/nCfabkLnG6w0JZ56Slll1AA0gdXwBH5+hV2jXg9nz6qNVSi0HGfBx4dzQebD3wcOwJw5ajitAWgCq+Fheo+bTO93vy50X7lqFTRvDocPF898003wzz8wcqS6nz1b2T6uxp7gtTmshkcppkccHq6UKGJj1f2vv3JTVgD7wruqe4uxcijsjUND1f2uXerkkNk0aXVAU03U8CgWPeL6TVqWnKFzZ86dNrD4ue2qE87JKRRQWwoKlLuQfv1g/nz3NdiNaKqJGpWeBdMfYcH0R0rP8PPP1P1pgRJWnU4Nl6dNK57P31+tPD/1lLpPT1cbtpa5cRVFGxJreJQ7xpdujxiA0FDyYlpCHoQYC+DRRwt9d5w5o063v/mmUja2tRl19CicOgU1aqj7Q4eUMsaAAUW3jbwcTWA1PErz1l3KzTNggLomJYXBK68UPkhNVU63LHPWXbtg/XqlDnXLLWpV2aIK9cUX8N57quf194fjx6FOHXUK3ovRhsQaHuXons0c3bPZuZdvuUUJ7A03qPufflJ2ky1Cun270meUUh2m/f13qFlTPXvssUI9Z/Ba41CawGp4lO9nvcD3s15wvgBbZeLnnoMTJ8BiA3jatMLzd/7+ymzFkSPqftIkJcQWLArLXoYmsBreTd26hfF582Dp0kKhfvhhePxxFe/eXfW2p0+rI4CjR0MX8/A8L0/Zqlq0yLNtdwJNYDWqDuHhque0sGIFTJ+u4gUFSuni7beV5tXLL6s93TNn1Omi9u0hKkrlPXhQDbs3Ozl0dyOawGpUOu67T4WrpkULaNNGxf391ZzWomF15IgybbNsmTqoMHs2/PWXWmm+fFmZZrWcol++XP0QpKaq+yt8xnoSTWA1Kh0uE1hbfHxUL9qihbpv1kytMlt8W27bBk88oY4CtmunThjNmaOMpgcHQ3S0CqD8BTVvXmjaMTPTY+YcNYHVqHRkZJRu+d9l+PqqXtMyDO7TB44dK9zz3blTmbGRUj176CE17714UalD9u9feN73qafg2msLy05OVttIbkATWI1Kx4gRFWTOtHFjZY8GlFuS7OzCc705OUoIw8OVLarwcLjmGjU8HjlSrU5bhHTCBBg7trDcL79UTsRcgCawGhqlEWxzgH7cONXrWsyytm+vLGj4+ipNjz17oGdP9ezDD9Vhfcuq8+TJRfWd77xTCbETVAqBFUJ8LoQ4J4TYV9Lz9PR0TzfJyuzZs7V6tXqLM3y4GjJbeOEFJaig5sC//KK0rUCpTV68CC++qPSjjx2zGKir43C9jrpsd0cA4oH2wL6SnoeEhJTrft5ddOjQQavXhRxJ/l0eSf69zHq7d1fBE7jte41GKS9cKLx/4AEpX3+98D4xUQK50kFZqRS6xFLKjUKIphXdDg33Y48ucZXAx6fQJA6oFWcLUqoVaSd690ohsOWRl5dXIISw3fxKB9y9jmihjhDCU3Vp9drgIZOmnv7eOoB5aRpfR1/2CoGVUlYfkwIaGmVQKRadNDQ07EMTWA0NL6JSCKwQ4mvgD6ClEOKkEOJBm2f9hBCHhBBHhBCTPdimVCHEXiHEbiGEWw1KlbStJYSoJYT4WQjxt/kaWVYZLqz330KIU+bv3i2EGOCGemOEEL8KIfYLIf4SQvyfOd2t31xGvW79ZiFEkBBimxAi2VzvK+b0WCHEVvPf9iIhREC5hTm6rOzJgJqUHwWaAQFAMnCDh+pOBep4qK5i21rAW8Bkc3wyMMND9f4bmOTm740G2pvjYcBh4AZ3f3MZ9br1mwEBhJrj/sBW4BbgW2CMOf0TYHx5ZVWKHrYM4oAjUsoUKaUO+AYo2UehFyOl3AhcuCJ5CGBRh/kSGOqhet2OlDJNSrnTHL8EHAAa4uZvLqNetyIVOeZbf3OQQE9gsTndru+t7ALbEDhhc38SD/wDm5HAT0KIP4UQiR6q05Z6Uso0c/wMUM+Ddf9LCLHHPGR2+VDcFvP+eztUr+Oxb76iXnDzNwshfIUQu4FzwM+okWOmlNJyzMeuv+3KLrAVya1SyvZAf+AxIUR8RTVEqjGTpwxIzwKaA22BNOAdd1UkhAgFlgBPSimzbZ+585tLqNft3yylNEop2wKNUCPH65wpp7IL7Ckgxua+kTnN7UgpT5mv54DvUf/InuSsECIawHw954lKpZRnzX9cJuAz3PTdQgh/lNB8JaVcak52+zeXVK+nvtlcVybwK9AZiBBCWHQh7PrbruwCux24xryaFgCMAX5wd6VCiBpCiDBLHOgDlHgwwY38AIwzx8cByz1RqUVgzNyBG75bCCGAOcABKaWt12e3fnNp9br7m4UQUUKICHM8GOiNmj//ClgOEtr3ve5cDXTRCtsA1GreUWCKh+pshlqRTgb+cne9wNeooZgeNZd5EKgNrAP+Bn4Banmo3vnAXmAPSoCi3VDvrajh7h5gtzkMcPc3l1GvW78ZaA3sMpe/D3jJ5u9sG3AE+A4ILK8sr/Cto6GhoajsQ2INDQ0bNIHV0PAiNIHV0PAiNIHV0PAiNIHV0PAiNIHV0PAiNIHV0PAiNIGtQIQQQ4UQUgjhkF6pEMIpL01CiJwS0n4VQvS9Iu1JIcQsJ+toWpq5WgfK+EQI0fVqyqiqaAJbsdwJ/Ga+FkEofEq6l1K60vTg1yiVT1vGmNMriluALRVYf6VFE9gKwnxi5FaUOuAYc1pTs3WNeSgVtm5X3MeY8+UIIaYLIR6zKe/fQohJ5vgy87HAv+w4GrgYGGixdmA+dtYA2OSCb2wmhNglhOhk/raDQoi5QojDQoivhBC3CSF+N1uYiDO/cz1wWEppNOt0rzRbatgnhBh9tW3yetypI6uFMvVLxwJzzPHNQAegKWACbjGnF7m3eTcHdZZzg03afiDGHK9lvgajBL225b1S2rICGGKOTwbevorvamqusyVKf7aNTboBaIXqKP4EPkdZYxgCLDPnmwg8YI4PBz6zKTu8ov/fKjpoPWzFcSfKggbmq2VYfExKaTscvPIeACnlLqCuEKKBEKINcFFKaTns/4QQIhk1rIwBrimnLbbDYlcMh6NQJ0/GSimTbdL/kVLuleoY21/AOqkkcS9KoAH6AmvM8b1AbyHEDCFENyll1lW2y+vxCrvEVQ0hRC2UeZBWQgiJsl0lgY+A3CuyX3lvy3eo41n1gUXmshOA24DOUso8IUQSUJ5d5+XAe0KI9kCIlPJPc1kCeBVllSEaCJBSfmTHJ2YBx1FD/v026QU2cZPNvQnwE0KEABFSytMAUsrD5jYNAF4XQqyTUr5qR/1VFq2HrRhGAPOllE2klE2llDHAPxQ9rG8Pi1A94giU8AKEo3rbPPPq8y3lFSKVvaFfUUNU2961PbAR6Gi+N9ic61wnhCjNpIkOda70XiHEXQ58Tw9zOzDX0QDIk1IuAGaa21Ot0XrYiuFOYMYVaUuA5x0pREr5l/mg/SlZaAtpDfCoEOIAcAj7V1u/RlnWsF0xTjG3KRXohvp7+cy8Wt2CMgy4SSlzhRCDgJ/N20l77GhDfwqNkoGa784UQphQZ3bH2/ktVRbtPKyGwwghbkItDE10cbk7gZullHpXlluV0ARWQ8OL0OawGhpehCawGhpehCawGhpehCawGhpehCawGhpehCawGhpehCawGhpexP8DtoJZ8pu8iMwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 234x234 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'betaRatio_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/jupiter/'+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([0.3,0.4])\n",
    "\n",
    "Glevels = np.array([35])\n",
    "Qlevels = np.array([11500.0, 12000.0])\n",
    "Hlevels = np.array([670])\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/jupiter/jupiter-drag-small.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/jupiter/jupiter-drag-small.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/jupiter/jupiter-drag-small.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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/jupiter/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'betaRatio_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/jupiter/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/jupiter/'+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([0.1, 0.2, 0.3, 0.4, 0.45])\n",
    "\n",
    "Glevels = np.array([30, 32, 36, 40])\n",
    "Qlevels = np.array([8000.0, 9000.0, 10000.0, 11000.0, 13000.0 ])\n",
    "Hlevels = np.array([600, 650, 675, 700])\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='%.2f',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",
    "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$'+r'-load')\n",
    "\n",
    "\n",
    "for l in Glabels:\n",
    "    l.set_rotation(-90)\n",
    "\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted')\n",
    "\n",
    "plt.clabel(QCS1, inline=1, fontsize=10, colors='red',fmt='%d',inline_spacing=0)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "QCS1.collections[1].set_linewidths(1.5)\n",
    "QCS1.collections[2].set_linewidths(1.5)\n",
    "QCS1.collections[3].set_linewidths(1.5)\n",
    "QCS1.collections[4].set_linewidths(1.5)\n",
    "\n",
    "\n",
    "\n",
    "QCS1.collections[0].set_label(r'$\\dot{q}$'+', '+r'$W/cm^2$')\n",
    "\n",
    "\n",
    "HCS1 = plt.contour(X, Y, np.transpose(H1), levels=Hlevels, colors='xkcd:brown',linestyles='dashdot')\n",
    "\n",
    "Hlabels=plt.clabel(HCS1, inline=1, fontsize=10, colors='xkcd:brown',fmt='%d',inline_spacing=0)\n",
    "HCS1.collections[0].set_linewidths(1.75)\n",
    "HCS1.collections[1].set_linewidths(1.75)\n",
    "HCS1.collections[2].set_linewidths(1.75)\n",
    "HCS1.collections[3].set_linewidths(1.75)\n",
    "\n",
    "\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "for l in Hlabels:\n",
    "    l.set_rotation(-90)\n",
    "\n",
    "plt.ylim(1,40)\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(r'$\\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/jupiter/jupiter-drag-large.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/jupiter/jupiter-drag-large.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/jupiter/jupiter-drag-large.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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