{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 08 - a - Titan - Feasibility Charts - Lift"
   ]
  },
  {
   "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": [
    "# Create a planet object for Titan\n",
    "planet=Planet(\"TITAN\")\n",
    "\n",
    "# Load an nominal atmospheric profile with height, temp, pressure, density data\n",
    "planet.loadAtmosphereModel('../atmdata/Titan/titan-gram-avg.dat', 0 , 1 , 2, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "vinf_kms_array = np.linspace( 0.0,   20.0,  11)\n",
    "LD_array       = np.linspace( 0.0,    0.4 , 11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs('../data/jsr-paper/titan/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "runID = 'titan-lift-'\n",
    "\n",
    "num_total      = len(vinf_kms_array)*len(LD_array)\n",
    "count = 1\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 +\\\n",
    "                          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(LD_array)))\n",
    "underShootLimit_array = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "exitflag_os_array     = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "exitflag_us_array     = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "TCW_array             = np.zeros((len(v0_kms_array),len(LD_array)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000000.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "planet.h_skip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run #1 of 121: Arrival V_infty: 0.0 km/s, L/D:0.0 OSL: -25.514971257482102 USL: -25.514971257482102, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #2 of 121: Arrival V_infty: 0.0 km/s, L/D:0.04 OSL: -25.45138018635771 USL: -25.580314400805946, TCW: 0.12893421444823616 EFOS: 1.0 EFUS: 1.0\n",
      "Run #3 of 121: Arrival V_infty: 0.0 km/s, L/D:0.08 OSL: -25.38948930773404 USL: -25.64745317793495, TCW: 0.2579638702009106 EFOS: 1.0 EFUS: 1.0\n",
      "Run #4 of 121: Arrival V_infty: 0.0 km/s, L/D:0.12 OSL: -25.32925233032438 USL: -25.716441067765118, TCW: 0.3871887374407379 EFOS: 1.0 EFUS: 1.0\n",
      "Run #5 of 121: Arrival V_infty: 0.0 km/s, L/D:0.16 OSL: -25.270583539615473 USL: -25.78731656072705, TCW: 0.5167330211115768 EFOS: 1.0 EFUS: 1.0\n",
      "Run #6 of 121: Arrival V_infty: 0.0 km/s, L/D:0.2 OSL: -25.213493534782174 USL: -25.86014109790267, TCW: 0.6466475631204958 EFOS: 1.0 EFUS: 1.0\n",
      "Run #7 of 121: Arrival V_infty: 0.0 km/s, L/D:0.24 OSL: -25.15796347541982 USL: -25.93496696183138, TCW: 0.7770034864115587 EFOS: 1.0 EFUS: 1.0\n",
      "Run #8 of 121: Arrival V_infty: 0.0 km/s, L/D:0.28 OSL: -25.10358803123745 USL: -26.011832889293146, TCW: 0.9082448580556957 EFOS: 1.0 EFUS: 1.0\n",
      "Run #9 of 121: Arrival V_infty: 0.0 km/s, L/D:0.32 OSL: -25.050954196871317 USL: -26.090807851131103, TCW: 1.0398536542597867 EFOS: 1.0 EFUS: 1.0\n",
      "Run #10 of 121: Arrival V_infty: 0.0 km/s, L/D:0.36 OSL: -24.99971933953566 USL: -26.171878132998245, TCW: 1.172158793462586 EFOS: 1.0 EFUS: 1.0\n",
      "Run #11 of 121: Arrival V_infty: 0.0 km/s, L/D:0.4 OSL: -24.949835860508756 USL: -26.255228782465565, TCW: 1.305392921956809 EFOS: 1.0 EFUS: 1.0\n",
      "Run #12 of 121: Arrival V_infty: 2.0 km/s, L/D:0.0 OSL: -31.015925318410154 USL: -31.015925318410154, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #13 of 121: Arrival V_infty: 2.0 km/s, L/D:0.04 OSL: -30.903608585220354 USL: -31.133143656363245, TCW: 0.22953507114289096 EFOS: 1.0 EFUS: 1.0\n",
      "Run #14 of 121: Arrival V_infty: 2.0 km/s, L/D:0.08 OSL: -30.795854513995437 USL: -31.25540595901839, TCW: 0.459551445022953 EFOS: 1.0 EFUS: 1.0\n",
      "Run #15 of 121: Arrival V_infty: 2.0 km/s, L/D:0.12 OSL: -30.692822433265974 USL: -31.38304972487822, TCW: 0.6902272916122456 EFOS: 1.0 EFUS: 1.0\n",
      "Run #16 of 121: Arrival V_infty: 2.0 km/s, L/D:0.16 OSL: -30.59419914830505 USL: -31.51631139749952, TCW: 0.9221122491944698 EFOS: 1.0 EFUS: 1.0\n",
      "Run #17 of 121: Arrival V_infty: 2.0 km/s, L/D:0.2 OSL: -30.49964146029015 USL: -31.655628093983978, TCW: 1.1559866336938285 EFOS: 1.0 EFUS: 1.0\n",
      "Run #18 of 121: Arrival V_infty: 2.0 km/s, L/D:0.24 OSL: -30.409022368101432 USL: -31.800695425281447, TCW: 1.3916730571800144 EFOS: 1.0 EFUS: 1.0\n",
      "Run #19 of 121: Arrival V_infty: 2.0 km/s, L/D:0.28 OSL: -30.32214499220936 USL: -31.95157759664653, TCW: 1.62943260443717 EFOS: 1.0 EFUS: 1.0\n",
      "Run #20 of 121: Arrival V_infty: 2.0 km/s, L/D:0.32 OSL: -30.238926814559818 USL: -32.109300839016214, TCW: 1.870374024456396 EFOS: 1.0 EFUS: 1.0\n",
      "Run #21 of 121: Arrival V_infty: 2.0 km/s, L/D:0.36 OSL: -30.15904302841227 USL: -32.2739311681471, TCW: 2.1148881397348305 EFOS: 1.0 EFUS: 1.0\n",
      "Run #22 of 121: Arrival V_infty: 2.0 km/s, L/D:0.4 OSL: -30.08237587226904 USL: -32.445119427142345, TCW: 2.3627435548733047 EFOS: 1.0 EFUS: 1.0\n",
      "Run #23 of 121: Arrival V_infty: 4.0 km/s, L/D:0.0 OSL: -34.97237434810813 USL: -34.97237434810813, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #24 of 121: Arrival V_infty: 4.0 km/s, L/D:0.04 OSL: -34.787472070365766 USL: -35.169872504193336, TCW: 0.38240043382756994 EFOS: 1.0 EFUS: 1.0\n",
      "Run #25 of 121: Arrival V_infty: 4.0 km/s, L/D:0.08 OSL: -34.61436116441837 USL: -35.38073633092063, TCW: 0.7663751665022573 EFOS: 1.0 EFUS: 1.0\n",
      "Run #26 of 121: Arrival V_infty: 4.0 km/s, L/D:0.12 OSL: -34.45243507477062 USL: -35.60600105056437, TCW: 1.1535659757937538 EFOS: 1.0 EFUS: 1.0\n",
      "Run #27 of 121: Arrival V_infty: 4.0 km/s, L/D:0.16 OSL: -34.30082951927761 USL: -35.84596524540757, TCW: 1.5451357261299563 EFOS: 1.0 EFUS: 1.0\n",
      "Run #28 of 121: Arrival V_infty: 4.0 km/s, L/D:0.2 OSL: -34.15872400577791 USL: -36.10159908828791, TCW: 1.9428750825099996 EFOS: 1.0 EFUS: 1.0\n",
      "Run #29 of 121: Arrival V_infty: 4.0 km/s, L/D:0.24 OSL: -34.025490372539934 USL: -36.37381047389863, TCW: 2.348320101358695 EFOS: 1.0 EFUS: 1.0\n",
      "Run #30 of 121: Arrival V_infty: 4.0 km/s, L/D:0.28 OSL: -33.90041375951114 USL: -36.662981463021424, TCW: 2.7625677035102854 EFOS: 1.0 EFUS: 1.0\n",
      "Run #31 of 121: Arrival V_infty: 4.0 km/s, L/D:0.32 OSL: -33.7828604920287 USL: -36.9701674915741, TCW: 3.187306999545399 EFOS: 1.0 EFUS: 1.0\n",
      "Run #32 of 121: Arrival V_infty: 4.0 km/s, L/D:0.36 OSL: -33.6722075456164 USL: -37.29582787098116, TCW: 3.6236203253647545 EFOS: 1.0 EFUS: 1.0\n",
      "Run #33 of 121: Arrival V_infty: 4.0 km/s, L/D:0.4 OSL: -33.56788355479148 USL: -37.640593710872054, TCW: 4.072710156080575 EFOS: 1.0 EFUS: 1.0\n",
      "Run #34 of 121: Arrival V_infty: 6.0 km/s, L/D:0.0 OSL: -36.55339961955906 USL: -36.55339961955906, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #35 of 121: Arrival V_infty: 6.0 km/s, L/D:0.04 OSL: -36.30991351896955 USL: -36.81863568785775, TCW: 0.5087221688881982 EFOS: 1.0 EFUS: 1.0\n",
      "Run #36 of 121: Arrival V_infty: 6.0 km/s, L/D:0.08 OSL: -36.08649113976935 USL: -37.10681944811222, TCW: 1.0203283083428687 EFOS: 1.0 EFUS: 1.0\n",
      "Run #37 of 121: Arrival V_infty: 6.0 km/s, L/D:0.12 OSL: -35.88128173923178 USL: -37.42006860019683, TCW: 1.5387868609650468 EFOS: 1.0 EFUS: 1.0\n",
      "Run #38 of 121: Arrival V_infty: 6.0 km/s, L/D:0.16 OSL: -35.69216382782179 USL: -37.759508941322565, TCW: 2.067345113500778 EFOS: 1.0 EFUS: 1.0\n",
      "Run #39 of 121: Arrival V_infty: 6.0 km/s, L/D:0.2 OSL: -35.51825936667592 USL: -38.12718914391007, TCW: 2.6089297772341524 EFOS: 1.0 EFUS: 1.0\n",
      "Run #40 of 121: Arrival V_infty: 6.0 km/s, L/D:0.24 OSL: -35.35803283409405 USL: -38.52427348592391, TCW: 3.1662406518298667 EFOS: 1.0 EFUS: 1.0\n",
      "Run #41 of 121: Arrival V_infty: 6.0 km/s, L/D:0.28 OSL: -35.20994569329196 USL: -38.95232763955937, TCW: 3.7423819462674146 EFOS: 1.0 EFUS: 1.0\n",
      "Run #42 of 121: Arrival V_infty: 6.0 km/s, L/D:0.32 OSL: -35.07268943973759 USL: -39.411855873411696, TCW: 4.339166433674109 EFOS: 1.0 EFUS: 1.0\n",
      "Run #43 of 121: Arrival V_infty: 6.0 km/s, L/D:0.36 OSL: -34.94514826366867 USL: -39.90427581026961, TCW: 4.959127546600939 EFOS: 1.0 EFUS: 1.0\n",
      "Run #44 of 121: Arrival V_infty: 6.0 km/s, L/D:0.4 OSL: -34.82630711933598 USL: -40.43011636465599, TCW: 5.603809245320008 EFOS: 1.0 EFUS: 1.0\n",
      "Run #45 of 121: Arrival V_infty: 8.0 km/s, L/D:0.0 OSL: -37.30830402138599 USL: -37.30830402138599, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #46 of 121: Arrival V_infty: 8.0 km/s, L/D:0.04 OSL: -37.01922867968824 USL: -37.62797248840434, TCW: 0.608743808716099 EFOS: 1.0 EFUS: 1.0\n",
      "Run #47 of 121: Arrival V_infty: 8.0 km/s, L/D:0.08 OSL: -36.75789386102406 USL: -37.98048920803922, TCW: 1.222595347015158 EFOS: 1.0 EFUS: 1.0\n",
      "Run #48 of 121: Arrival V_infty: 8.0 km/s, L/D:0.12 OSL: -36.52138110681335 USL: -38.36921853662716, TCW: 1.8478374298138078 EFOS: 1.0 EFUS: 1.0\n",
      "Run #49 of 121: Arrival V_infty: 8.0 km/s, L/D:0.16 OSL: -36.306709369353484 USL: -38.796157593489625, TCW: 2.48944822413614 EFOS: 1.0 EFUS: 1.0\n",
      "Run #50 of 121: Arrival V_infty: 8.0 km/s, L/D:0.2 OSL: -36.11226072874706 USL: -39.26360473242676, TCW: 3.1513440036796965 EFOS: 1.0 EFUS: 1.0\n",
      "Run #51 of 121: Arrival V_infty: 8.0 km/s, L/D:0.24 OSL: -35.935070643321524 USL: -39.77331844205764, TCW: 3.83824779873612 EFOS: 1.0 EFUS: 1.0\n",
      "Run #52 of 121: Arrival V_infty: 8.0 km/s, L/D:0.28 OSL: -35.77242139813097 USL: -40.32779188503628, TCW: 4.5553704869053036 EFOS: 1.0 EFUS: 1.0\n",
      "Run #53 of 121: Arrival V_infty: 8.0 km/s, L/D:0.32 OSL: -35.624574055218545 USL: -40.927684062386106, TCW: 5.303110007167561 EFOS: 1.0 EFUS: 1.0\n",
      "Run #54 of 121: Arrival V_infty: 8.0 km/s, L/D:0.36 OSL: -35.48770683895782 USL: -41.57504633086501, TCW: 6.087339491907187 EFOS: 1.0 EFUS: 1.0\n",
      "Run #55 of 121: Arrival V_infty: 8.0 km/s, L/D:0.4 OSL: -35.36111286779487 USL: -42.27051441576623, TCW: 6.909401547971356 EFOS: 1.0 EFUS: 1.0\n",
      "Run #56 of 121: Arrival V_infty: 10.0 km/s, L/D:0.0 OSL: -37.73500176645757 USL: -37.73500176645757, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #57 of 121: Arrival V_infty: 10.0 km/s, L/D:0.04 OSL: -37.40933102440977 USL: -38.0995362964386, TCW: 0.6902052720288339 EFOS: 1.0 EFUS: 1.0\n",
      "Run #58 of 121: Arrival V_infty: 10.0 km/s, L/D:0.08 OSL: -37.11848095314417 USL: -38.50691511950208, TCW: 1.3884341663579107 EFOS: 1.0 EFUS: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run #59 of 121: Arrival V_infty: 10.0 km/s, L/D:0.12 OSL: -36.858614949484036 USL: -38.96069325457938, TCW: 2.102078305095347 EFOS: 1.0 EFUS: 1.0\n",
      "Run #60 of 121: Arrival V_infty: 10.0 km/s, L/D:0.16 OSL: -36.625891531512025 USL: -39.46397802513093, TCW: 2.8380864936189028 EFOS: 1.0 EFUS: 1.0\n",
      "Run #61 of 121: Arrival V_infty: 10.0 km/s, L/D:0.2 OSL: -36.416870136745274 USL: -40.020147596951574, TCW: 3.6032774602063 EFOS: 1.0 EFUS: 1.0\n",
      "Run #62 of 121: Arrival V_infty: 10.0 km/s, L/D:0.24 OSL: -36.22781270735504 USL: -40.63134053834801, TCW: 4.403527830992971 EFOS: 1.0 EFUS: 1.0\n",
      "Run #63 of 121: Arrival V_infty: 10.0 km/s, L/D:0.28 OSL: -36.057115732255625 USL: -41.299823124270915, TCW: 5.242707392015291 EFOS: 1.0 EFUS: 1.0\n",
      "Run #64 of 121: Arrival V_infty: 10.0 km/s, L/D:0.32 OSL: -35.90142396457668 USL: -42.027264101248875, TCW: 6.1258401366721955 EFOS: 1.0 EFUS: 1.0\n",
      "Run #65 of 121: Arrival V_infty: 10.0 km/s, L/D:0.36 OSL: -35.75892305646266 USL: -42.81509491542238, TCW: 7.056171858959715 EFOS: 1.0 EFUS: 1.0\n",
      "Run #66 of 121: Arrival V_infty: 10.0 km/s, L/D:0.4 OSL: -35.62774777177037 USL: -43.66371442764648, TCW: 8.03596665587611 EFOS: 1.0 EFUS: 1.0\n",
      "Run #67 of 121: Arrival V_infty: 12.0 km/s, L/D:0.0 OSL: -38.00705658584411 USL: -38.00705658584411, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #68 of 121: Arrival V_infty: 12.0 km/s, L/D:0.04 OSL: -37.651045319136756 USL: -38.409662422640395, TCW: 0.7586171035036386 EFOS: 1.0 EFUS: 1.0\n",
      "Run #69 of 121: Arrival V_infty: 12.0 km/s, L/D:0.08 OSL: -37.33656026625613 USL: -38.8638374414877, TCW: 1.5272771752315748 EFOS: 1.0 EFUS: 1.0\n",
      "Run #70 of 121: Arrival V_infty: 12.0 km/s, L/D:0.12 OSL: -37.058427575277165 USL: -39.37490949487983, TCW: 2.3164819196026656 EFOS: 1.0 EFUS: 1.0\n",
      "Run #71 of 121: Arrival V_infty: 12.0 km/s, L/D:0.16 OSL: -36.81180312178185 USL: -39.94635842737989, TCW: 3.1345553055980417 EFOS: 1.0 EFUS: 1.0\n",
      "Run #72 of 121: Arrival V_infty: 12.0 km/s, L/D:0.2 OSL: -36.592206591820286 USL: -40.58190076709798, TCW: 3.989694175277691 EFOS: 1.0 EFUS: 1.0\n",
      "Run #73 of 121: Arrival V_infty: 12.0 km/s, L/D:0.24 OSL: -36.395653579158534 USL: -41.28433297963056, TCW: 4.888679400472029 EFOS: 1.0 EFUS: 1.0\n",
      "Run #74 of 121: Arrival V_infty: 12.0 km/s, L/D:0.28 OSL: -36.21811121468272 USL: -42.05645120369809, TCW: 5.838339989015367 EFOS: 1.0 EFUS: 1.0\n",
      "Run #75 of 121: Arrival V_infty: 12.0 km/s, L/D:0.32 OSL: -36.057930737475544 USL: -42.89915537464185, TCW: 6.841224637166306 EFOS: 1.0 EFUS: 1.0\n",
      "Run #76 of 121: Arrival V_infty: 12.0 km/s, L/D:0.36 OSL: -35.91175047795696 USL: -43.81437718100278, TCW: 7.902626703045826 EFOS: 1.0 EFUS: 1.0\n",
      "Run #77 of 121: Arrival V_infty: 12.0 km/s, L/D:0.4 OSL: -35.777677630212565 USL: -44.80187549837865, TCW: 9.024197868166084 EFOS: 1.0 EFUS: 1.0\n",
      "Run #78 of 121: Arrival V_infty: 14.0 km/s, L/D:0.0 OSL: -38.19568794645966 USL: -38.19568794645966, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #79 of 121: Arrival V_infty: 14.0 km/s, L/D:0.04 OSL: -37.813956308047636 USL: -38.631183661727846, TCW: 0.8172273536802095 EFOS: 1.0 EFUS: 1.0\n",
      "Run #80 of 121: Arrival V_infty: 14.0 km/s, L/D:0.08 OSL: -37.47999176555459 USL: -39.12694387337251, TCW: 1.6469521078179241 EFOS: 1.0 EFUS: 1.0\n",
      "Run #81 of 121: Arrival V_infty: 14.0 km/s, L/D:0.12 OSL: -37.1872010103325 USL: -39.68888433560642, TCW: 2.501683325273916 EFOS: 1.0 EFUS: 1.0\n",
      "Run #82 of 121: Arrival V_infty: 14.0 km/s, L/D:0.16 OSL: -36.92970369957766 USL: -40.32111611176515, TCW: 3.391412412187492 EFOS: 1.0 EFUS: 1.0\n",
      "Run #83 of 121: Arrival V_infty: 14.0 km/s, L/D:0.2 OSL: -36.70208573294076 USL: -41.0287545419269, TCW: 4.326668808986142 EFOS: 1.0 EFUS: 1.0\n",
      "Run #84 of 121: Arrival V_infty: 14.0 km/s, L/D:0.24 OSL: -36.499621000071784 USL: -41.81471172023157, TCW: 5.3150907201597875 EFOS: 1.0 EFUS: 1.0\n",
      "Run #85 of 121: Arrival V_infty: 14.0 km/s, L/D:0.28 OSL: -36.31829377235408 USL: -42.680748409053194, TCW: 6.362454636699113 EFOS: 1.0 EFUS: 1.0\n",
      "Run #86 of 121: Arrival V_infty: 14.0 km/s, L/D:0.32 OSL: -36.154223885005194 USL: -43.62922828438241, TCW: 7.475004399377212 EFOS: 1.0 EFUS: 1.0\n",
      "Run #87 of 121: Arrival V_infty: 14.0 km/s, L/D:0.36 OSL: -36.00554739051586 USL: -44.66006945122717, TCW: 8.654522060711315 EFOS: 1.0 EFUS: 1.0\n",
      "Run #88 of 121: Arrival V_infty: 14.0 km/s, L/D:0.4 OSL: -35.86953031488156 USL: -45.773085576285666, TCW: 9.903555261404108 EFOS: 1.0 EFUS: 1.0\n",
      "Run #89 of 121: Arrival V_infty: 16.0 km/s, L/D:0.0 OSL: -38.334795668240986 USL: -38.334795668240986, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #90 of 121: Arrival V_infty: 16.0 km/s, L/D:0.04 OSL: -37.93104953922739 USL: -38.799327109591104, TCW: 0.8682775703637162 EFOS: 1.0 EFUS: 1.0\n",
      "Run #91 of 121: Arrival V_infty: 16.0 km/s, L/D:0.08 OSL: -37.58043908113177 USL: -39.33223628217456, TCW: 1.7517972010427911 EFOS: 1.0 EFUS: 1.0\n",
      "Run #92 of 121: Arrival V_infty: 16.0 km/s, L/D:0.12 OSL: -37.27554415151462 USL: -39.940170897760254, TCW: 2.664626746245631 EFOS: 1.0 EFUS: 1.0\n",
      "Run #93 of 121: Arrival V_infty: 16.0 km/s, L/D:0.16 OSL: -37.00929536396143 USL: -40.62822910277464, TCW: 3.6189337388132117 EFOS: 1.0 EFUS: 1.0\n",
      "Run #94 of 121: Arrival V_infty: 16.0 km/s, L/D:0.2 OSL: -36.77539663400603 USL: -41.40138798663611, TCW: 4.625991352630081 EFOS: 1.0 EFUS: 1.0\n",
      "Run #95 of 121: Arrival V_infty: 16.0 km/s, L/D:0.24 OSL: -36.56842432279518 USL: -42.26356028429291, TCW: 5.695135961497726 EFOS: 1.0 EFUS: 1.0\n",
      "Run #96 of 121: Arrival V_infty: 16.0 km/s, L/D:0.28 OSL: -36.383834564116114 USL: -43.21647359938288, TCW: 6.832639035266766 EFOS: 1.0 EFUS: 1.0\n",
      "Run #97 of 121: Arrival V_infty: 16.0 km/s, L/D:0.32 OSL: -36.21736386305565 USL: -44.2612672174364, TCW: 8.043903354380745 EFOS: 1.0 EFUS: 1.0\n",
      "Run #98 of 121: Arrival V_infty: 16.0 km/s, L/D:0.36 OSL: -36.06689985177945 USL: -45.39768820158497, TCW: 9.330788349805516 EFOS: 1.0 EFUS: 1.0\n",
      "Run #99 of 121: Arrival V_infty: 16.0 km/s, L/D:0.4 OSL: -35.929522839061974 USL: -46.625458093883935, TCW: 10.695935254821961 EFOS: 1.0 EFUS: 1.0\n",
      "Run #100 of 121: Arrival V_infty: 18.0 km/s, L/D:0.0 OSL: -38.44211545330836 USL: -38.44211545330836, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #101 of 121: Arrival V_infty: 18.0 km/s, L/D:0.04 OSL: -38.019047516736464 USL: -38.932749327421334, TCW: 0.91370181068487 EFOS: 1.0 EFUS: 1.0\n",
      "Run #102 of 121: Arrival V_infty: 18.0 km/s, L/D:0.08 OSL: -37.65421579478425 USL: -39.49912609837702, TCW: 1.8449103035927692 EFOS: 1.0 EFUS: 1.0\n",
      "Run #103 of 121: Arrival V_infty: 18.0 km/s, L/D:0.12 OSL: -37.33909472367304 USL: -40.14884140600043, TCW: 2.8097466823273862 EFOS: 1.0 EFUS: 1.0\n",
      "Run #104 of 121: Arrival V_infty: 18.0 km/s, L/D:0.16 OSL: -37.06566023533742 USL: -40.888145559740224, TCW: 3.8224853244028054 EFOS: 1.0 EFUS: 1.0\n",
      "Run #105 of 121: Arrival V_infty: 18.0 km/s, L/D:0.2 OSL: -36.82671503585152 USL: -41.72235094074131, TCW: 4.895635904889787 EFOS: 1.0 EFUS: 1.0\n",
      "Run #106 of 121: Arrival V_infty: 18.0 km/s, L/D:0.24 OSL: -36.616204994472355 USL: -42.65459139428276, TCW: 6.038386399810406 EFOS: 1.0 EFUS: 1.0\n",
      "Run #107 of 121: Arrival V_infty: 18.0 km/s, L/D:0.28 OSL: -36.429112633963086 USL: -43.68728968647338, TCW: 7.258177052510291 EFOS: 1.0 EFUS: 1.0\n",
      "Run #108 of 121: Arrival V_infty: 18.0 km/s, L/D:0.32 OSL: -36.261264120559645 USL: -44.82096457939406, TCW: 8.559700458834413 EFOS: 1.0 EFUS: 1.0\n",
      "Run #109 of 121: Arrival V_infty: 18.0 km/s, L/D:0.36 OSL: -36.10904980258783 USL: -46.0543223132554, TCW: 9.945272510667564 EFOS: 1.0 EFUS: 1.0\n",
      "Run #110 of 121: Arrival V_infty: 18.0 km/s, L/D:0.4 OSL: -35.97068549478354 USL: -47.388277523074066, TCW: 11.417592028290528 EFOS: 1.0 EFUS: 1.0\n",
      "Run #111 of 121: Arrival V_infty: 20.0 km/s, L/D:0.0 OSL: -38.52810854533891 USL: -38.52810854533891, TCW: 0.0 EFOS: 1.0 EFUS: 1.0\n",
      "Run #112 of 121: Arrival V_infty: 20.0 km/s, L/D:0.04 OSL: -38.08775701387276 USL: -39.04229659404882, TCW: 0.9545395801760606 EFOS: 1.0 EFUS: 1.0\n",
      "Run #113 of 121: Arrival V_infty: 20.0 km/s, L/D:0.08 OSL: -37.71045087079983 USL: -39.63922655926217, TCW: 1.9287756884623377 EFOS: 1.0 EFUS: 1.0\n",
      "Run #114 of 121: Arrival V_infty: 20.0 km/s, L/D:0.12 OSL: -37.38658995805963 USL: -40.32754955024575, TCW: 2.9409595921861182 EFOS: 1.0 EFUS: 1.0\n",
      "Run #115 of 121: Arrival V_infty: 20.0 km/s, L/D:0.16 OSL: -37.10711297497983 USL: -41.11429143950227, TCW: 4.00717846452244 EFOS: 1.0 EFUS: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run #116 of 121: Arrival V_infty: 20.0 km/s, L/D:0.2 OSL: -36.864039080552175 USL: -42.00467576134906, TCW: 5.140636680796888 EFOS: 1.0 EFUS: 1.0\n",
      "Run #117 of 121: Arrival V_infty: 20.0 km/s, L/D:0.24 OSL: -36.65067914721294 USL: -43.00229972909801, TCW: 6.351620581885072 EFOS: 1.0 EFUS: 1.0\n",
      "Run #118 of 121: Arrival V_infty: 20.0 km/s, L/D:0.28 OSL: -36.46157456237779 USL: -44.1088317787835, TCW: 7.6472572164057055 EFOS: 1.0 EFUS: 1.0\n",
      "Run #119 of 121: Arrival V_infty: 20.0 km/s, L/D:0.32 OSL: -36.2923777405631 USL: -45.325105611358595, TCW: 9.032727870795497 EFOS: 1.0 EFUS: 1.0\n",
      "Run #120 of 121: Arrival V_infty: 20.0 km/s, L/D:0.36 OSL: -36.13915873747828 USL: -46.649327029157575, TCW: 10.510168291679292 EFOS: 1.0 EFUS: 1.0\n",
      "Run #121 of 121: Arrival V_infty: 20.0 km/s, L/D:0.4 OSL: -36.00003748846211 USL: -48.08002977605793, TCW: 12.079992287595815 EFOS: 1.0 EFUS: 1.0\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(LD_array)):\n",
    "        vehicle=Vehicle('Apollo', 1000.0, 200.0, LD_array[j], 3.1416, 0.0, 1.00, 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-5)\n",
    "        overShootLimit_array[i,j],  exitflag_os_array[i,j]  = vehicle.findOverShootLimit (6000.0, 1.0, -80.0, -4.0, 1E-10, 1700.0)\n",
    "        underShootLimit_array[i,j], exitflag_us_array[i,j] =  vehicle.findUnderShootLimit(6000.0, 1.0, -80.0, -4.0, 1E-10, 1700.0)\n",
    "\n",
    "        TCW_array[i,j] = overShootLimit_array[i,j] - underShootLimit_array[i,j]\n",
    "\n",
    "        print(\"Run #\"+str(count)+\" of \"+ str(num_total)+\": Arrival V_infty: \"+str(vinf_kms_array[i])+\" km/s\"+\", L/D:\"+str(LD_array[j]) + \" OSL: \"+str(overShootLimit_array[i,j])+\" USL: \"+str(underShootLimit_array[i,j])+\", TCW: \"+str(TCW_array[i,j])+\" EFOS: \"+str(exitflag_os_array[i,j])+ \" EFUS: \"+str(exitflag_us_array[i,j]))\n",
    "        count = count +1\n",
    "\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'vinf_kms_array.txt',vinf_kms_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'v0_kms_array.txt',v0_kms_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'LD_array.txt',LD_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'overShootLimit_array.txt',overShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'exitflag_os_array.txt',exitflag_os_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'undershootLimit_array.txt',underShootLimit_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'exitflag_us_array.txt',exitflag_us_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'TCW_array.txt',TCW_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 0.0 km/s, L/D: 0.0 G_MAX: 0.08200396558397373 QDOT_MAX: 1.6128023798798288 J_MAX: 1536.7086077036138 STAG. PRES: 0.0016205665732171328\n",
      "V_infty: 0.0 km/s, L/D: 0.04 G_MAX: 0.08392311894606015 QDOT_MAX: 1.629819830215325 J_MAX: 1549.4686315554088 STAG. PRES: 0.0015848275560768955\n",
      "V_infty: 0.0 km/s, L/D: 0.08 G_MAX: 0.08602869422199302 QDOT_MAX: 1.647087864777911 J_MAX: 1562.3255686202442 STAG. PRES: 0.0015499792633722183\n",
      "V_infty: 0.0 km/s, L/D: 0.12 G_MAX: 0.08833020521536614 QDOT_MAX: 1.6646061156614458 J_MAX: 1575.276555200694 STAG. PRES: 0.0015160120666174665\n",
      "V_infty: 0.0 km/s, L/D: 0.16 G_MAX: 0.09083565523967044 QDOT_MAX: 1.6823680825887173 J_MAX: 1588.1226906463787 STAG. PRES: 0.0014829109068668015\n",
      "V_infty: 0.0 km/s, L/D: 0.2 G_MAX: 0.0935543723443794 QDOT_MAX: 1.70038296987158 J_MAX: 1601.1925719050464 STAG. PRES: 0.0014506111469076305\n",
      "V_infty: 0.0 km/s, L/D: 0.24 G_MAX: 0.09649463153723462 QDOT_MAX: 1.7186421978655568 J_MAX: 1614.4140234010536 STAG. PRES: 0.0014192129769681368\n",
      "V_infty: 0.0 km/s, L/D: 0.28 G_MAX: 0.09966344227079614 QDOT_MAX: 1.7371440214502123 J_MAX: 1627.7659387523051 STAG. PRES: 0.0013886063120675952\n",
      "V_infty: 0.0 km/s, L/D: 0.32 G_MAX: 0.10306957222300325 QDOT_MAX: 1.755887339198168 J_MAX: 1641.1544465176628 STAG. PRES: 0.0013588378997132294\n",
      "V_infty: 0.0 km/s, L/D: 0.36 G_MAX: 0.10671606316476555 QDOT_MAX: 1.774850897368081 J_MAX: 1654.6101009789288 STAG. PRES: 0.0013298715843119422\n",
      "V_infty: 0.0 km/s, L/D: 0.4 G_MAX: 0.11061461581237138 QDOT_MAX: 1.793968336482542 J_MAX: 1668.148643045104 STAG. PRES: 0.001301690365784232\n",
      "V_infty: 2.0 km/s, L/D: 0.0 G_MAX: 0.2638073796828546 QDOT_MAX: 4.434145648097929 J_MAX: 2668.4893893028634 STAG. PRES: 0.005180739708437693\n",
      "V_infty: 2.0 km/s, L/D: 0.04 G_MAX: 0.27326671384492407 QDOT_MAX: 4.500726621233144 J_MAX: 2705.5431365747245 STAG. PRES: 0.005006016250111582\n",
      "V_infty: 2.0 km/s, L/D: 0.08 G_MAX: 0.28354602040719107 QDOT_MAX: 4.568822566103753 J_MAX: 2743.024832455704 STAG. PRES: 0.004838116998771817\n",
      "V_infty: 2.0 km/s, L/D: 0.12 G_MAX: 0.29474855824442464 QDOT_MAX: 4.638932005661415 J_MAX: 2780.899943976725 STAG. PRES: 0.004677137413136057\n",
      "V_infty: 2.0 km/s, L/D: 0.16 G_MAX: 0.3068442203455496 QDOT_MAX: 4.710110912612215 J_MAX: 2819.0900630632123 STAG. PRES: 0.004523245904956351\n",
      "V_infty: 2.0 km/s, L/D: 0.2 G_MAX: 0.3199739828192184 QDOT_MAX: 4.783024265276189 J_MAX: 2857.619511525302 STAG. PRES: 0.004375416880426746\n",
      "V_infty: 2.0 km/s, L/D: 0.24 G_MAX: 0.3341023955818388 QDOT_MAX: 4.8572257708764175 J_MAX: 2896.658877302795 STAG. PRES: 0.004233941185399024\n",
      "V_infty: 2.0 km/s, L/D: 0.28 G_MAX: 0.34927518514615646 QDOT_MAX: 4.9321651023103845 J_MAX: 2935.737523251334 STAG. PRES: 0.004098535326060483\n",
      "V_infty: 2.0 km/s, L/D: 0.32 G_MAX: 0.3656578268906325 QDOT_MAX: 5.009271465612286 J_MAX: 2975.080784528254 STAG. PRES: 0.003969724140371822\n",
      "V_infty: 2.0 km/s, L/D: 0.36 G_MAX: 0.3832155587150466 QDOT_MAX: 5.087728540134605 J_MAX: 3014.6343578966585 STAG. PRES: 0.0038462603955086412\n",
      "V_infty: 2.0 km/s, L/D: 0.4 G_MAX: 0.4020756358923829 QDOT_MAX: 5.1675389786719625 J_MAX: 3054.3523405019178 STAG. PRES: 0.003728397913279993\n",
      "V_infty: 4.0 km/s, L/D: 0.0 G_MAX: 0.9263568992994788 QDOT_MAX: 16.871437535918666 J_MAX: 5478.797506523767 STAG. PRES: 0.018068719367894514\n",
      "V_infty: 4.0 km/s, L/D: 0.04 G_MAX: 0.9745175576927899 QDOT_MAX: 17.215662909518116 J_MAX: 5592.8375219515365 STAG. PRES: 0.017197610105633622\n",
      "V_infty: 4.0 km/s, L/D: 0.08 G_MAX: 1.0271579527459642 QDOT_MAX: 17.572038353741583 J_MAX: 5708.789547737131 STAG. PRES: 0.01638174908528245\n",
      "V_infty: 4.0 km/s, L/D: 0.12 G_MAX: 1.084651798812686 QDOT_MAX: 17.941146785744735 J_MAX: 5825.744386806142 STAG. PRES: 0.01561436556709808\n",
      "V_infty: 4.0 km/s, L/D: 0.16 G_MAX: 1.1471983927643528 QDOT_MAX: 18.32157192584817 J_MAX: 5943.622489293895 STAG. PRES: 0.014896137197050253\n",
      "V_infty: 4.0 km/s, L/D: 0.2 G_MAX: 1.2151706487692244 QDOT_MAX: 18.71455783772116 J_MAX: 6062.679292092828 STAG. PRES: 0.01422325036296005\n",
      "V_infty: 4.0 km/s, L/D: 0.24 G_MAX: 1.2888546057016637 QDOT_MAX: 19.117641949932672 J_MAX: 6182.14971617858 STAG. PRES: 0.013595474476124539\n",
      "V_infty: 4.0 km/s, L/D: 0.28 G_MAX: 1.3685235465896208 QDOT_MAX: 19.53117276135494 J_MAX: 6301.990416607923 STAG. PRES: 0.013009926980340756\n",
      "V_infty: 4.0 km/s, L/D: 0.32 G_MAX: 1.4544619439638884 QDOT_MAX: 19.95320791097998 J_MAX: 6422.025737330282 STAG. PRES: 0.012464904364997085\n",
      "V_infty: 4.0 km/s, L/D: 0.36 G_MAX: 1.546952008826183 QDOT_MAX: 20.382761223722635 J_MAX: 6542.032282031632 STAG. PRES: 0.011957029027896105\n",
      "V_infty: 4.0 km/s, L/D: 0.4 G_MAX: 1.6463565376667149 QDOT_MAX: 20.821096665362713 J_MAX: 6661.830208721439 STAG. PRES: 0.011483495887908046\n",
      "V_infty: 6.0 km/s, L/D: 0.0 G_MAX: 2.175844844429933 QDOT_MAX: 47.433533442775826 J_MAX: 9768.521343430966 STAG. PRES: 0.04230087144089911\n",
      "V_infty: 6.0 km/s, L/D: 0.04 G_MAX: 2.316057118754916 QDOT_MAX: 48.605137695859156 J_MAX: 10018.924947401618 STAG. PRES: 0.03981138099231835\n",
      "V_infty: 6.0 km/s, L/D: 0.08 G_MAX: 2.4703356114689226 QDOT_MAX: 49.821568135570374 J_MAX: 10272.610890558266 STAG. PRES: 0.03751302707573121\n",
      "V_infty: 6.0 km/s, L/D: 0.12 G_MAX: 2.6399863400268386 QDOT_MAX: 51.088743995113276 J_MAX: 10529.129302513027 STAG. PRES: 0.03539371960533041\n",
      "V_infty: 6.0 km/s, L/D: 0.16 G_MAX: 2.825222401643777 QDOT_MAX: 52.404181138103525 J_MAX: 10786.195403490372 STAG. PRES: 0.03344291129254538\n",
      "V_infty: 6.0 km/s, L/D: 0.2 G_MAX: 3.0277206471603475 QDOT_MAX: 53.76591637856806 J_MAX: 11045.492708094855 STAG. PRES: 0.0316627788549649\n",
      "V_infty: 6.0 km/s, L/D: 0.24 G_MAX: 3.248021600292358 QDOT_MAX: 55.17106422591286 J_MAX: 11304.715495684302 STAG. PRES: 0.030029829638943684\n",
      "V_infty: 6.0 km/s, L/D: 0.28 G_MAX: 3.4873067418096433 QDOT_MAX: 56.61408308142272 J_MAX: 11563.408468472935 STAG. PRES: 0.028534164171455503\n",
      "V_infty: 6.0 km/s, L/D: 0.32 G_MAX: 3.745926978365309 QDOT_MAX: 58.089039398927476 J_MAX: 11820.935061271419 STAG. PRES: 0.02716546413502329\n",
      "V_infty: 6.0 km/s, L/D: 0.36 G_MAX: 4.024636949642774 QDOT_MAX: 59.595842484183585 J_MAX: 12076.908342788965 STAG. PRES: 0.025911043312423953\n",
      "V_infty: 6.0 km/s, L/D: 0.4 G_MAX: 4.324991950751927 QDOT_MAX: 61.1403199382865 J_MAX: 12331.206269737715 STAG. PRES: 0.024761739904812872\n",
      "V_infty: 8.0 km/s, L/D: 0.0 G_MAX: 4.054008250370041 QDOT_MAX: 105.56911837912692 J_MAX: 15531.601067560725 STAG. PRES: 0.07868651928953858\n",
      "V_infty: 8.0 km/s, L/D: 0.04 G_MAX: 4.353634619287322 QDOT_MAX: 108.49466901687259 J_MAX: 15983.168446939162 STAG. PRES: 0.07342580108325782\n",
      "V_infty: 8.0 km/s, L/D: 0.08 G_MAX: 4.686055719457706 QDOT_MAX: 111.58706736347281 J_MAX: 16440.29258423726 STAG. PRES: 0.06863097738467279\n",
      "V_infty: 8.0 km/s, L/D: 0.12 G_MAX: 5.053595553841607 QDOT_MAX: 114.81627529290499 J_MAX: 16901.023994133022 STAG. PRES: 0.0642760587224046\n",
      "V_infty: 8.0 km/s, L/D: 0.16 G_MAX: 5.458155095891558 QDOT_MAX: 118.2025307006553 J_MAX: 17361.951352867407 STAG. PRES: 0.060329205620983754\n",
      "V_infty: 8.0 km/s, L/D: 0.2 G_MAX: 5.901976615695981 QDOT_MAX: 121.70898514929463 J_MAX: 17825.05815538779 STAG. PRES: 0.05677211005406319\n",
      "V_infty: 8.0 km/s, L/D: 0.24 G_MAX: 6.385226366342336 QDOT_MAX: 125.32748913365943 J_MAX: 18285.560696928187 STAG. PRES: 0.05356047959405269\n",
      "V_infty: 8.0 km/s, L/D: 0.28 G_MAX: 6.91008302430456 QDOT_MAX: 129.0540363448925 J_MAX: 18742.838130665932 STAG. PRES: 0.05066537187976081\n",
      "V_infty: 8.0 km/s, L/D: 0.32 G_MAX: 7.47866738507253 QDOT_MAX: 132.86214575153573 J_MAX: 19197.48855178626 STAG. PRES: 0.04804851519980136\n",
      "V_infty: 8.0 km/s, L/D: 0.36 G_MAX: 8.092246709897635 QDOT_MAX: 136.7421649545037 J_MAX: 19646.821640187616 STAG. PRES: 0.04568386935740233\n",
      "V_infty: 8.0 km/s, L/D: 0.4 G_MAX: 8.749972889326413 QDOT_MAX: 140.63629257368333 J_MAX: 20090.25321879853 STAG. PRES: 0.04353258384829593\n",
      "V_infty: 10.0 km/s, L/D: 0.0 G_MAX: 6.580957929014517 QDOT_MAX: 200.87111099948714 J_MAX: 22763.105424387126 STAG. PRES: 0.12762392946642506\n",
      "V_infty: 10.0 km/s, L/D: 0.04 G_MAX: 7.118251970674219 QDOT_MAX: 206.9945644521199 J_MAX: 23485.484604654983 STAG. PRES: 0.11828957621245373\n",
      "V_infty: 10.0 km/s, L/D: 0.08 G_MAX: 7.717973044757411 QDOT_MAX: 213.42483825375712 J_MAX: 24215.12150541604 STAG. PRES: 0.1098649362067035\n",
      "V_infty: 10.0 km/s, L/D: 0.12 G_MAX: 8.385611575944319 QDOT_MAX: 220.28017308958283 J_MAX: 24949.714966908323 STAG. PRES: 0.10231956624999546\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 10.0 km/s, L/D: 0.16 G_MAX: 9.123211843153566 QDOT_MAX: 227.4346212823398 J_MAX: 25684.036690082015 STAG. PRES: 0.09556239020263844\n",
      "V_infty: 10.0 km/s, L/D: 0.2 G_MAX: 9.933163243987483 QDOT_MAX: 234.86622292278759 J_MAX: 26416.068104729147 STAG. PRES: 0.08953886838442343\n",
      "V_infty: 10.0 km/s, L/D: 0.24 G_MAX: 10.8179558577175 QDOT_MAX: 242.52834053232309 J_MAX: 27139.842437467654 STAG. PRES: 0.08415278974308961\n",
      "V_infty: 10.0 km/s, L/D: 0.28 G_MAX: 11.779550705937144 QDOT_MAX: 250.42522708056995 J_MAX: 27859.708420616673 STAG. PRES: 0.07936159198627832\n",
      "V_infty: 10.0 km/s, L/D: 0.32 G_MAX: 12.818848674870084 QDOT_MAX: 258.4227391209814 J_MAX: 28569.882306295385 STAG. PRES: 0.07507493040976887\n",
      "V_infty: 10.0 km/s, L/D: 0.36 G_MAX: 13.937298288361724 QDOT_MAX: 266.50847024215614 J_MAX: 29269.434006154133 STAG. PRES: 0.07122255489885879\n",
      "V_infty: 10.0 km/s, L/D: 0.4 G_MAX: 15.133601440757603 QDOT_MAX: 274.7470623382852 J_MAX: 29958.14746933824 STAG. PRES: 0.06775744436973026\n",
      "V_infty: 12.0 km/s, L/D: 0.0 G_MAX: 9.771585175172138 QDOT_MAX: 343.0732068215123 J_MAX: 31461.254189157426 STAG. PRES: 0.18940068874035587\n",
      "V_infty: 12.0 km/s, L/D: 0.04 G_MAX: 10.630920253141388 QDOT_MAX: 354.2654460861265 J_MAX: 32526.360963666484 STAG. PRES: 0.1745495460728383\n",
      "V_infty: 12.0 km/s, L/D: 0.08 G_MAX: 11.596583633493966 QDOT_MAX: 366.12371654711893 J_MAX: 33601.91077475781 STAG. PRES: 0.1612846311045952\n",
      "V_infty: 12.0 km/s, L/D: 0.12 G_MAX: 12.678991085231992 QDOT_MAX: 378.82198405728604 J_MAX: 34681.583043800274 STAG. PRES: 0.1495393905938058\n",
      "V_infty: 12.0 km/s, L/D: 0.16 G_MAX: 13.875310434061126 QDOT_MAX: 392.05792084047 J_MAX: 35757.890457462025 STAG. PRES: 0.1391252799863858\n",
      "V_infty: 12.0 km/s, L/D: 0.2 G_MAX: 15.191426815692076 QDOT_MAX: 405.85533130748445 J_MAX: 36826.49594084157 STAG. PRES: 0.1299271646361282\n",
      "V_infty: 12.0 km/s, L/D: 0.24 G_MAX: 16.63388966408865 QDOT_MAX: 420.09695244841714 J_MAX: 37883.25701718947 STAG. PRES: 0.12179820014183382\n",
      "V_infty: 12.0 km/s, L/D: 0.28 G_MAX: 18.193663901829083 QDOT_MAX: 434.70815748095396 J_MAX: 38922.44461334187 STAG. PRES: 0.11458857482393983\n",
      "V_infty: 12.0 km/s, L/D: 0.32 G_MAX: 19.88506710705116 QDOT_MAX: 449.39434806283623 J_MAX: 39950.45047363489 STAG. PRES: 0.10821717964128581\n",
      "V_infty: 12.0 km/s, L/D: 0.36 G_MAX: 21.70554613312197 QDOT_MAX: 464.44519627486255 J_MAX: 40958.62260179634 STAG. PRES: 0.10251522044362592\n",
      "V_infty: 12.0 km/s, L/D: 0.4 G_MAX: 23.653660788866436 QDOT_MAX: 479.50831056946794 J_MAX: 41948.50738700389 STAG. PRES: 0.09741481983079994\n",
      "V_infty: 14.0 km/s, L/D: 0.0 G_MAX: 13.633072355301616 QDOT_MAX: 541.9668906917879 J_MAX: 41621.2948158369 STAG. PRES: 0.26415704244496413\n",
      "V_infty: 14.0 km/s, L/D: 0.04 G_MAX: 14.904714986820048 QDOT_MAX: 560.5344571328511 J_MAX: 43107.19272823718 STAG. PRES: 0.2423442138428575\n",
      "V_infty: 14.0 km/s, L/D: 0.08 G_MAX: 16.34630995769644 QDOT_MAX: 580.5248450887474 J_MAX: 44601.51706345395 STAG. PRES: 0.22296164408850758\n",
      "V_infty: 14.0 km/s, L/D: 0.12 G_MAX: 17.96273603744006 QDOT_MAX: 601.8246087408376 J_MAX: 46099.260904347444 STAG. PRES: 0.20593550196165325\n",
      "V_infty: 14.0 km/s, L/D: 0.16 G_MAX: 19.75972724386411 QDOT_MAX: 624.2447697235775 J_MAX: 47588.03592610851 STAG. PRES: 0.19100210288920463\n",
      "V_infty: 14.0 km/s, L/D: 0.2 G_MAX: 21.742367800497945 QDOT_MAX: 647.7277610096666 J_MAX: 49062.77082348141 STAG. PRES: 0.17791518298159625\n",
      "V_infty: 14.0 km/s, L/D: 0.24 G_MAX: 23.90397120782904 QDOT_MAX: 671.6673260768241 J_MAX: 50516.6281838183 STAG. PRES: 0.1664529949621547\n",
      "V_infty: 14.0 km/s, L/D: 0.28 G_MAX: 26.25004148238334 QDOT_MAX: 695.9938058492222 J_MAX: 51945.735789353224 STAG. PRES: 0.15635793526400765\n",
      "V_infty: 14.0 km/s, L/D: 0.32 G_MAX: 28.786442143311795 QDOT_MAX: 720.5996659818618 J_MAX: 53347.31780135171 STAG. PRES: 0.14745188592904213\n",
      "V_infty: 14.0 km/s, L/D: 0.36 G_MAX: 31.510100387425904 QDOT_MAX: 745.8200317571147 J_MAX: 54721.82853845848 STAG. PRES: 0.13953542220776213\n",
      "V_infty: 14.0 km/s, L/D: 0.4 G_MAX: 34.395059331460736 QDOT_MAX: 770.9111165168554 J_MAX: 56069.031522876685 STAG. PRES: 0.13249311949345746\n",
      "V_infty: 16.0 km/s, L/D: 0.0 G_MAX: 18.174204209769016 QDOT_MAX: 807.2123759809732 J_MAX: 53240.122017628135 STAG. PRES: 0.3520746869240099\n",
      "V_infty: 16.0 km/s, L/D: 0.04 G_MAX: 19.961198285593326 QDOT_MAX: 836.3524909377646 J_MAX: 55220.94919923972 STAG. PRES: 0.3216694492087816\n",
      "V_infty: 16.0 km/s, L/D: 0.08 G_MAX: 21.986691871936237 QDOT_MAX: 867.5658082515399 J_MAX: 57214.04026293348 STAG. PRES: 0.29490261398264983\n",
      "V_infty: 16.0 km/s, L/D: 0.12 G_MAX: 24.274626330393254 QDOT_MAX: 901.2148700980175 J_MAX: 59205.091906757756 STAG. PRES: 0.27152094042040115\n",
      "V_infty: 16.0 km/s, L/D: 0.16 G_MAX: 26.81847854006644 QDOT_MAX: 936.5037003850927 J_MAX: 61180.591364129374 STAG. PRES: 0.2511880282647549\n",
      "V_infty: 16.0 km/s, L/D: 0.2 G_MAX: 29.624491394620595 QDOT_MAX: 973.2825671102875 J_MAX: 63129.37685739893 STAG. PRES: 0.23348546444224255\n",
      "V_infty: 16.0 km/s, L/D: 0.24 G_MAX: 32.68760661922699 QDOT_MAX: 1011.045240637255 J_MAX: 65046.27901681584 STAG. PRES: 0.21807854032651336\n",
      "V_infty: 16.0 km/s, L/D: 0.28 G_MAX: 35.988196189251745 QDOT_MAX: 1049.4143842722467 J_MAX: 66925.61165611167 STAG. PRES: 0.2046071541536996\n",
      "V_infty: 16.0 km/s, L/D: 0.32 G_MAX: 39.59943776537322 QDOT_MAX: 1088.2983476063428 J_MAX: 68764.4088897787 STAG. PRES: 0.19277455345944705\n",
      "V_infty: 16.0 km/s, L/D: 0.36 G_MAX: 43.410126066838046 QDOT_MAX: 1127.233849745889 J_MAX: 70564.57671779353 STAG. PRES: 0.18228431858416022\n",
      "V_infty: 16.0 km/s, L/D: 0.4 G_MAX: 47.53576635230533 QDOT_MAX: 1165.4144161092822 J_MAX: 72325.91792138599 STAG. PRES: 0.17300440328578173\n",
      "V_infty: 18.0 km/s, L/D: 0.0 G_MAX: 23.40336885491152 QDOT_MAX: 1148.6085537867393 J_MAX: 66309.08163666763 STAG. PRES: 0.45330149804706965\n",
      "V_infty: 18.0 km/s, L/D: 0.04 G_MAX: 25.80098114943073 QDOT_MAX: 1191.6399268942846 J_MAX: 68871.21999632231 STAG. PRES: 0.41264838005377935\n",
      "V_infty: 18.0 km/s, L/D: 0.08 G_MAX: 28.541303584556886 QDOT_MAX: 1238.7666200450362 J_MAX: 71439.58433195124 STAG. PRES: 0.3770882891181772\n",
      "V_infty: 18.0 km/s, L/D: 0.12 G_MAX: 31.62903082824123 QDOT_MAX: 1288.299049235977 J_MAX: 74000.3250876273 STAG. PRES: 0.3462891879493052\n",
      "V_infty: 18.0 km/s, L/D: 0.16 G_MAX: 35.080507439470765 QDOT_MAX: 1340.961352340724 J_MAX: 76534.96161525689 STAG. PRES: 0.31963171414662817\n",
      "V_infty: 18.0 km/s, L/D: 0.2 G_MAX: 38.86888723928434 QDOT_MAX: 1395.9254715505815 J_MAX: 79028.80502250443 STAG. PRES: 0.29663573091707657\n",
      "V_infty: 18.0 km/s, L/D: 0.24 G_MAX: 43.03323801429349 QDOT_MAX: 1451.9733448851878 J_MAX: 81475.49644247131 STAG. PRES: 0.2767129234750695\n",
      "V_infty: 18.0 km/s, L/D: 0.28 G_MAX: 47.52989345608378 QDOT_MAX: 1507.9255565482915 J_MAX: 83868.96213504086 STAG. PRES: 0.2593672235552281\n",
      "V_infty: 18.0 km/s, L/D: 0.32 G_MAX: 52.330132578380955 QDOT_MAX: 1566.5945882026124 J_MAX: 86207.93971550549 STAG. PRES: 0.24414525540149773\n",
      "V_infty: 18.0 km/s, L/D: 0.36 G_MAX: 57.54331008764386 QDOT_MAX: 1624.4476650209024 J_MAX: 88488.70122307124 STAG. PRES: 0.23076876811466715\n",
      "V_infty: 18.0 km/s, L/D: 0.4 G_MAX: 63.04827874944529 QDOT_MAX: 1681.655673813861 J_MAX: 90722.22433472415 STAG. PRES: 0.2189129941805156\n",
      "V_infty: 20.0 km/s, L/D: 0.0 G_MAX: 29.322871969781872 QDOT_MAX: 1576.186724110585 J_MAX: 80834.73446696717 STAG. PRES: 0.5678916868556658\n",
      "V_infty: 20.0 km/s, L/D: 0.04 G_MAX: 32.44533774484028 QDOT_MAX: 1637.8972169566634 J_MAX: 84055.05628262646 STAG. PRES: 0.5152833260147726\n",
      "V_infty: 20.0 km/s, L/D: 0.08 G_MAX: 36.01557296481677 QDOT_MAX: 1704.210523905902 J_MAX: 87278.86748565242 STAG. PRES: 0.46958008898730463\n",
      "V_infty: 20.0 km/s, L/D: 0.12 G_MAX: 40.03288180399049 QDOT_MAX: 1775.3354262693774 J_MAX: 90486.35991783126 STAG. PRES: 0.4302244633212311\n",
      "V_infty: 20.0 km/s, L/D: 0.16 G_MAX: 44.57588773046718 QDOT_MAX: 1850.7407498360724 J_MAX: 93653.36688979996 STAG. PRES: 0.3964320722666379\n",
      "V_infty: 20.0 km/s, L/D: 0.2 G_MAX: 49.54891492891966 QDOT_MAX: 1928.752013819814 J_MAX: 96764.68240885387 STAG. PRES: 0.36735436817819556\n",
      "V_infty: 20.0 km/s, L/D: 0.24 G_MAX: 54.952961292639074 QDOT_MAX: 2007.733910643393 J_MAX: 99806.73685337364 STAG. PRES: 0.3423312273605096\n",
      "V_infty: 20.0 km/s, L/D: 0.28 G_MAX: 60.81387838310897 QDOT_MAX: 2090.16523119185 J_MAX: 102780.6156108758 STAG. PRES: 0.3206080630629298\n",
      "V_infty: 20.0 km/s, L/D: 0.32 G_MAX: 67.14633444127692 QDOT_MAX: 2170.824153404984 J_MAX: 105676.66164427123 STAG. PRES: 0.30164335896860567\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V_infty: 20.0 km/s, L/D: 0.36 G_MAX: 73.93027933188917 QDOT_MAX: 2253.050084093605 J_MAX: 108499.25526656646 STAG. PRES: 0.28495880524512573\n",
      "V_infty: 20.0 km/s, L/D: 0.4 G_MAX: 81.23020056719713 QDOT_MAX: 2335.6852079278015 J_MAX: 111257.37725859885 STAG. PRES: 0.2701855500987224\n"
     ]
    }
   ],
   "source": [
    "acc_net_g_max_array       = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "stag_pres_atm_max_array   = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "q_stag_total_max_array    = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "heatload_max_array        = np.zeros((len(v0_kms_array),len(LD_array)))\n",
    "\n",
    "\n",
    "for i in range(0,len(v0_kms_array)):\n",
    "    for j in range(0,len(LD_array)):\n",
    "        vehicle=Vehicle('Apollo', 1000.0, 200.0, LD_array[j], 3.1416, 0.0, 1.00, 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",
    "        vehicle.propogateEntry (6000.0, 1.0, 180.0)\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",
    "        vehicle=Vehicle('Apollo', 1000.0, 200.0, LD_array[j], 3.1416, 0.0, 1.00, 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",
    "        vehicle.propogateEntry (6000.0, 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_us))\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\"+\", L/D: \"+str(LD_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",
    "\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'acc_net_g_max_array.txt',acc_net_g_max_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'stag_pres_atm_max_array.txt',stag_pres_atm_max_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'q_stag_total_max_array.txt',q_stag_total_max_array)\n",
    "np.savetxt('../data/jsr-paper/titan/'+runID+'heatload_max_array.txt',heatload_max_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 450x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.loadtxt('../data/jsr-paper/titan/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/titan/'+runID+'LD_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/titan/'+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, transpose(S1), kind='cubic')\n",
    "\n",
    "\n",
    "x_new =  np.linspace( 0.0,   20,  210)\n",
    "y_new =  np.linspace( 0.0,   0.4 ,110)\n",
    "z_new =  np.zeros((len(x_new),len(y_new)))\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",
    "\n",
    "Zlevels = np.array([0.5,1.0])\n",
    "\n",
    "Glevels = np.array([5.0, 10.0])\n",
    "Qlevels = np.array([100, 400.0])\n",
    "Hlevels = np.array([25.0])\n",
    "#Slevels = np.array([0.8])\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "#plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "#plt.xlim([0.0,30.0])\n",
    "#plt.ylim([0.0,0.4])\n",
    "#plt.tight_layout()\n",
    "#plt.contourf(X, Y, Z, levels=levels)\n",
    "\n",
    "\n",
    "#plt.axvline(x=25.0,linewidth=3, linestyle='dotted' ,color='red',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(LV$'+r' '+r'$C3$'+r' '+r'$limit)$')\n",
    "#plt.axvline(x=13.1,linewidth=1, linestyle='dotted' ,color='cyan',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(Chem. OI)$')\n",
    "\n",
    "fig = plt.figure()\n",
    "fig.set_size_inches([6.25,6.25])\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=12, 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[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",
    "plt.clabel(GCS1, inline=1, fontsize=12, 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[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=12, colors='red',fmt='%d',inline_spacing=0)\n",
    "QCS1.collections[0].set_linewidths(1.5)\n",
    "QCS1.collections[1].set_linewidths(1.5)\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='magenta',linestyles='dashdot')\n",
    "\n",
    "plt.clabel(HCS1, inline=1, fontsize=12, colors='magenta',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",
    "\n",
    "#SCS1 = plt.contour(X, Y, transpose(S1), levels=Slevels, colors='cyan')\n",
    "\n",
    "#plt.clabel(SCS1, inline=1, fontsize=12, colors='cyan',fmt='%.1f',inline_spacing=1)\n",
    "#SCS1.collections[0].set_linewidths(3.0)\n",
    "#SCS1.collections[0].set_label(r'$Peak$'+r' '+r'$stag. pressure,atm$')\n",
    "\n",
    "#plt.axhline(y=0.36,linewidth=1, linestyle='dotted' ,color='white',label=r'$Apollo$'+' '+r'$CM$'+' '+r'$L/D$')\n",
    "\n",
    "\n",
    "\n",
    "#matplotlib.rcParams['text.usetex'] = True\n",
    "#plt.rc('text', usetex=True)\n",
    "\n",
    "\n",
    "# circles for b=50 plot\n",
    "#plt.plot(7.5,0.20,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "#plt.plot(4.95,0.30,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "\n",
    "#plt.plot(7.5,0.211,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "#plt.plot(4.95,0.315,marker='o',mfc='none',mec='k',markersize=16,markeredgewidth=3.0)\n",
    "\n",
    "\n",
    "#plt.grid(True,linestyle='dotted', linewidth=0.1)\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(\"L/D\",fontsize=16)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=16)\n",
    "plt.xticks(np.array([ 0, 4, 8, 12, 16, 20]), fontsize=16)\n",
    "plt.yticks(np.array([ 0.0, 0.1, 0.2, 0.3, 0.4]),fontsize=16)\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=16)\n",
    "\n",
    "dat0 = ZCS1.allsegs[1][0]\n",
    "x1,y1=dat0[:,0],dat0[:,1]\n",
    "F1 = interpolate.interp1d(x1, y1, kind='linear',fill_value='extrapolate', bounds_error=False)\n",
    "\n",
    "dat1 = GCS1.allsegs[0][0]\n",
    "x2,y2=dat1[:,0],dat1[:,1]\n",
    "F2 = interpolate.interp1d(x2, y2, kind='linear',fill_value='extrapolate', bounds_error=False)\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(0,20,101)\n",
    "y4 = F1(x4)\n",
    "y4a =F1a(x4)\n",
    "y5 = F2(x4)\n",
    "y6 = F3(x4)\n",
    "\n",
    "y7 = np.minimum(y5,y6)\n",
    "y8 = np.minimum(y4,y6)\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",
    "plt.xlim([0.0,20.0])\n",
    "plt.ylim([0.0,0.4])\n",
    "\n",
    "plt.savefig('../data/jsr-paper/titan/titan-lift-small.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/titan/titan-lift-small.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/titan/titan-lift-small.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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/titan/'+runID+'vinf_kms_array.txt')\n",
    "y = np.loadtxt('../data/jsr-paper/titan/'+runID+'LD_array.txt')\n",
    "\n",
    "Z1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'TCW_array.txt')\n",
    "G1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'acc_net_g_max_array.txt')\n",
    "Q1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'q_stag_total_max_array.txt')\n",
    "H1 = np.loadtxt('../data/jsr-paper/titan/'+runID+'heatload_max_array.txt')\n",
    "S1 = np.loadtxt('../data/jsr-paper/titan/'+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, transpose(S1), kind='cubic')\n",
    "\n",
    "\n",
    "x_new =  np.linspace( 0.0,   20,  310)\n",
    "y_new =  np.linspace( 0.0,   0.4 ,110)\n",
    "z_new =  np.zeros((len(x_new),len(y_new)))\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",
    "\n",
    "\n",
    "\n",
    "Z1 = z1_new\n",
    "\n",
    "G1 = g1_new\n",
    "\n",
    "Q1 = q1_new\n",
    "\n",
    "#S1 = s1_new\n",
    "\n",
    "H1 = h1_new/1000.0\n",
    "\n",
    "X, Y = np.meshgrid(x_new, y_new)\n",
    "#X, Y = meshgrid(x, y)\n",
    "\n",
    "\n",
    "Zlevels = np.array([0.5,1.0,2.0, 3.0])\n",
    "\n",
    "Glevels = np.array([2.0, 5.0, 10.0, 20.0, 30.0])\n",
    "Qlevels = np.array([50.0, 200.0, 400.0, 700.0])\n",
    "Hlevels = np.array([5.0, 20.0, 30.0, 40.0])\n",
    "#Slevels = np.array([0.8])\n",
    "\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",
    "#plt.xlim([0.0,30.0])\n",
    "#plt.ylim([0.0,0.4])\n",
    "#plt.tight_layout()\n",
    "#plt.contourf(X, Y, Z, levels=levels)\n",
    "\n",
    "\n",
    "#plt.axvline(x=25.0,linewidth=3, linestyle='dotted' ,color='red',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(LV$'+r' '+r'$C3$'+r' '+r'$limit)$')\n",
    "#plt.axvline(x=13.1,linewidth=1, linestyle='dotted' ,color='cyan',label=r'$Max.$'+' '+r'$arrival$'+' '+r'$V_{\\infty}$'+ r' ' +r'$(Chem. OI)$')\n",
    "\n",
    "\n",
    "ZCS1 = plt.contour(X, Y, np.transpose(Z1), levels=Zlevels, colors='black',zorder=0)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.clabel(ZCS1, inline=1, fontsize=10, colors='black',fmt='%.1f',inline_spacing=1,zorder=0)\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",
    "\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',zorder=1)\n",
    "\n",
    "plt.clabel(GCS1, inline=1, fontsize=10, colors='blue',fmt='%d',inline_spacing=0,zorder=1)\n",
    "\n",
    "\n",
    "\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[3].set_linewidths(1.5)\n",
    "GCS1.collections[4].set_linewidths(1.5)\n",
    "\n",
    "GCS1.collections[0].set_label(r'$g$'+r'-load')\n",
    "\n",
    "\n",
    "QCS1 = plt.contour(X, Y, np.transpose(Q1), levels=Qlevels, colors='red',linestyles='dotted',zorder=13)\n",
    "\n",
    "plt.clabel(QCS1, inline=1, fontsize=10, colors='red',fmt='%d',inline_spacing=0,zorder=13)\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",
    "\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',zorder=14)\n",
    "\n",
    "plt.clabel(HCS1, inline=1, fontsize=10, colors='xkcd:brown',fmt='%d',inline_spacing=0,zorder=14)\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",
    "\n",
    "HCS1.collections[0].set_label(r'$Q$'+', '+r'$kJ/cm^2$')\n",
    "\n",
    "\n",
    "params = {'mathtext.default': 'regular' }          \n",
    "plt.rcParams.update(params)\n",
    "plt.ylabel(\"L/D\",fontsize=12)\n",
    "plt.xlabel(\"Arrival \"+r'$V_\\infty$'+r', km/s' ,fontsize=12)\n",
    "plt.xticks(np.array([ 0.0, 5, 10, 15, 20]),fontsize=12)\n",
    "plt.yticks(np.array([ 0.0, 0.1, 0.2, 0.3, 0.4]),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",
    "\n",
    "plt.savefig('../data/jsr-paper/titan/titan-lift-large.png', dpi= 300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/titan/titan-lift-large.pdf', dpi=300,bbox_inches='tight')\n",
    "plt.savefig('../data/jsr-paper/titan/titan-lift-large.eps', dpi=300,bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "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
}