Integer_Optimizer_antenna.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e30a631d",
   "metadata": {},
   "source": [
    "# Loads packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3dcb71eb-b0a7-46b0-b843-dabb47086fd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "import torch\n",
    "import torch.optim as optim\n",
    "from scipy.spatial import ConvexHull\n",
    "from matplotlib.patches import Polygon\n",
    "import sys,os\n",
    "sys.path.append(os.path.realpath('./src/'))\n",
    "import pandas as pd\n",
    "from materialEncoder import MaterialEncoder\n",
    "import time\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facd1d4f",
   "metadata": {},
   "source": [
    "## Loads the Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6443eef2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocessData():\n",
    "  df = pd.read_excel('./data/MaterialDatabase_FULL.xlsx')# # \n",
    "  dataIdentifier = {'name': df[df.columns[0]], 'className':df[df.columns[1]], 'classID':df[df.columns[2]]} # name of the material and type\n",
    "  trainInfo = torch.tensor((df[df.columns[3:]].to_numpy())).float()\n",
    "\n",
    "  return dataIdentifier, trainInfo, df\n",
    "dataIdentifier, trainInfo, df = preprocessData()\n",
    "\n",
    "props = df.columns[3:].tolist()\n",
    "nmat, nprop = trainInfo.size()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02018f95",
   "metadata": {},
   "source": [
    "## Loads the truss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "59649404-c5ec-4dc5-8de0-1061ddab8047",
   "metadata": {},
   "outputs": [],
   "source": [
    "from examples import getExample\n",
    "from trussFE import TrussFE\n",
    "\n",
    "#Loads the example truss\n",
    "exampleName, nodeXY, connectivity, bc = getExample(6)\n",
    "#Changes the force\n",
    "#bc['forces'] = {'nodes':np.array([2]), 'fx':1.E3*torch.tensor([0.]), 'fy':1.E2*torch.tensor([125.])}\n",
    "\n",
    "#Loads the truss in truss\n",
    "truss = TrussFE(nodeXY, connectivity, bc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "babab7af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a plot\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.title(f\"Structure: {exampleName}\")\n",
    "\n",
    "# Plot nodes\n",
    "plt.plot(nodeXY[:, 0], nodeXY[:, 1], 'ro', markersize=8)\n",
    "\n",
    "# Plot elements\n",
    "for i in range(len(connectivity)):\n",
    "    node1 = connectivity[i, 0]\n",
    "    node2 = connectivity[i, 1]\n",
    "    x = [nodeXY[node1, 0], nodeXY[node2, 0]]\n",
    "    y = [nodeXY[node1, 1], nodeXY[node2, 1]]\n",
    "    plt.plot(x, y, 'b')\n",
    "\n",
    "\n",
    "# Set axis limits\n",
    "plt.xlim(-1, 2.5)\n",
    "plt.ylim(-1, 6)\n",
    "\n",
    "# Add labels\n",
    "plt.xlabel('X Position')\n",
    "plt.ylabel('Y Position')\n",
    "\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4219c821",
   "metadata": {},
   "source": [
    "## SELECT CONSTRAINTS AND OBJECTIVES HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef40e2f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Defines constraints and objectives\n",
    "constraints = {'massCons': {'isOn':False, 'maxMass':5}, \\\n",
    "               'costCons': {'isOn':False, 'maxCost':5},\\\n",
    "               'tensionCons': {'isOn':True, 'FOS':4.},\\\n",
    "               'complianceCons': {'isOn':False, 'maxJ':35},\\\n",
    "               'compressionCons': {'isOn':True, 'FOS':4.},\\\n",
    "               'co2Cons': {'isOn':False, 'maxco2':30},\\\n",
    "               'energyCons': {'isOn':False, 'maxenergy' : 1e10},\\\n",
    "               'waterCons': {'isOn':False, 'maxwater':4e3}}\n",
    "\n",
    "\n",
    "objectives = {'cost': {'isOn':True},\\\n",
    "              'mass': {'isOn':True}, \\\n",
    "              'co2': {'isOn':False},\\\n",
    "              'water': {'isOn':False},\\\n",
    "              'energy': {'isOn':False},\\\n",
    "              'compliance': {'isOn': False}}\n",
    "               \n",
    "# count the number of entries with 'isOn' set to True\n",
    "no = sum(1 for v in objectives.values() if v['isOn'])\n",
    "nc = sum(1 for v in constraints.values() if v['isOn'])\n",
    "\n",
    "# print an error message in red if there are 3 or more entries with 'isOn' set to True\n",
    "if no >= 3:\n",
    "    print('Error: Three or more entries have isOn=True')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b63a6d91",
   "metadata": {},
   "source": [
    "## ---------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "154d475d",
   "metadata": {},
   "source": [
    "## Defines problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ac0f696e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from pymoo.core.problem import ElementwiseProblem\n",
    "from pymoo.core.variable import Real, Integer, Choice, Binary\n",
    "from pymoo.termination.default import DefaultMultiObjectiveTermination\n",
    "\n",
    "class MixedVarsZDT1(ElementwiseProblem):\n",
    "\n",
    "    def __init__(self, truss, trainInfo , constraints, objectives, nc, no, nmat, **kwargs):\n",
    "\n",
    "        variables = dict()\n",
    "\n",
    "        variables[f\"x01\"] = Integer(bounds=(0, nmat-1))\n",
    "\n",
    "        for k in range(2, 49):\n",
    "            variables[f\"x{k:02}\"] = Real(bounds=(2e-8, 2e-3))\n",
    "\n",
    "        super().__init__(vars=variables, n_obj=no, n_ieq_constr=nc, **kwargs)\n",
    "        \n",
    "        self.truss=truss\n",
    "        self.trainInfo=trainInfo\n",
    "        self.constraints=constraints\n",
    "        self.objectives=objectives\n",
    "        \n",
    "    def _evaluate(self, x, out, *args, **kwargs):\n",
    "        x = np.array([x[f\"x{k:02}\"] for k in range(1, 49)])\n",
    "        \n",
    "        matprop=trainInfo[int(x[0]),:]  \n",
    "        \n",
    "        x_tensor = torch.from_numpy(x[1:])\n",
    "        area = x_tensor * torch.ones((connectivity.shape[0]))   \n",
    "        u, _, _, _, internalForce = truss.solveFE(E = torch.tensor([matprop[0]]).float(), A=area)\n",
    "        compliance = truss.computeCompliance(u)\n",
    "        volume = truss.getVolume(area)\n",
    "        mass = matprop[2]*volume\n",
    "        cost = mass*matprop[1]\n",
    "        co2 = mass*matprop[4]\n",
    "        energy = mass*matprop[5]        \n",
    "        water = mass*matprop[6] \n",
    "        \n",
    "        \n",
    "        \n",
    "        con_values = []\n",
    "        \n",
    "        if(constraints['massCons']['isOn']):\n",
    "            constraints['massCons']['value'] = (mass/constraints['massCons']['maxMass']) - 1.\n",
    "            con_values.append(constraints['massCons']['value'])\n",
    "\n",
    "        if(constraints['costCons']['isOn']):\n",
    "            constraints['costCons']['value'] = (cost/constraints['costCons']['maxCost']) - 1.\n",
    "            con_values.append(constraints['costCons']['value'])\n",
    "\n",
    "        if(constraints['tensionCons']['isOn']):\n",
    "            tensileForce = 0.001+torch.relu(internalForce)\n",
    "            tensileStress = tensileForce/area\n",
    "            maxTensileStressExperienced = torch.pow(torch.sum(tensileStress**6), 1./6)*constraints['tensionCons']['FOS']\n",
    "            constraints['tensionCons']['value'] = (maxTensileStressExperienced/matprop[3]) - 1.\n",
    "            con_values.append(constraints['tensionCons']['value'])\n",
    "\n",
    "        if(constraints['complianceCons']['isOn']):\n",
    "            constraints['complianceCons']['value'] = (compliance/constraints['complianceCons']['maxJ']) - 1.\n",
    "            con_values.append(constraints['complianceCons']['value'])\n",
    "\n",
    "        if(constraints['compressionCons']['isOn']):\n",
    "            compressiveForce = 0.001+torch.relu(-internalForce)\n",
    "            k = 4. # used in geom factor... see buckling theory\n",
    "            geomFactor = k*(self.truss.barLength/(np.pi*area))**2\n",
    "            compressiveStress = compressiveForce*geomFactor\n",
    "            maxCompressiveStressExperienced = torch.pow(torch.sum(compressiveStress**6), 1./6)*constraints['compressionCons']['FOS']\n",
    "            constraints['compressionCons']['value'] = (maxCompressiveStressExperienced/matprop[0]) - 1.\n",
    "            con_values.append(constraints['compressionCons']['value'])\n",
    "\n",
    "        if(constraints['co2Cons']['isOn']):\n",
    "            constraints['co2Cons']['value'] = (co2/constraints['co2Cons']['maxco2']) - 1.\n",
    "            con_values.append(constraints['co2Cons']['value'])\n",
    "\n",
    "        if(constraints['energyCons']['isOn']):\n",
    "            constraints['energyCons']['value'] = (energy/constraints['energyCons']['maxenergy']) - 1.\n",
    "            con_values.append(constraints['energyCons']['value'])\n",
    "\n",
    "        if(constraints['waterCons']['isOn']):\n",
    "            constraints['waterCons']['value'] = (water/constraints['waterCons']['maxwater']) - 1.\n",
    "            con_values.append(constraints['waterCons']['value'])\n",
    "            \n",
    "        \n",
    "        \n",
    "        obj_values = []\n",
    "        \n",
    "        if(objectives['cost']['isOn']):\n",
    "            obj_values.append(cost)\n",
    "            \n",
    "        if(objectives['mass']['isOn']):\n",
    "            obj_values.append(mass)\n",
    "            \n",
    "        if(objectives['co2']['isOn']):\n",
    "            obj_values.append(co2)\n",
    "            \n",
    "        if(objectives['water']['isOn']):\n",
    "            obj_values.append(water)\n",
    "            \n",
    "        if(objectives['energy']['isOn']):\n",
    "            obj_values.append(energy)\n",
    "            \n",
    "        if(objectives['compliance']['isOn']):\n",
    "            obj_values.append(compliance)\n",
    "            \n",
    "  \n",
    "\n",
    "        out[\"F\"] = np.array(obj_values)\n",
    "        out[\"G\"] = np.array(con_values)\n",
    "        \n",
    "  \n",
    "problem = MixedVarsZDT1(truss,trainInfo , constraints, objectives, nc, no, nmat)\n",
    "\n",
    "    \n",
    "from pymoo.visualization.scatter import Scatter\n",
    "from pymoo.algorithms.moo.nsga2 import NSGA2, RankAndCrowdingSurvival\n",
    "from pymoo.core.mixed import MixedVariableMating, MixedVariableGA, MixedVariableSampling, MixedVariableDuplicateElimination\n",
    "from pymoo.optimize import minimize\n",
    "\n",
    "algorithm = NSGA2(pop_size=100,\n",
    "                  sampling=MixedVariableSampling(),\n",
    "                  mating=MixedVariableMating(eliminate_duplicates=MixedVariableDuplicateElimination()),\n",
    "                  eliminate_duplicates=MixedVariableDuplicateElimination(),\n",
    "                  )\n",
    "\n",
    "termination=('n_gen', 350)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c05ba216",
   "metadata": {},
   "source": [
    "## Runs the solver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a8c922d3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================================================\n",
      "n_gen  |  n_eval  | n_nds  |     cv_min    |     cv_avg    |      eps      |   indicator  \n",
      "==========================================================================================\n",
      "     1 |      100 |      1 |  0.2129996812 |  3.700016E+04 |             - |             -\n",
      "     2 |      200 |      1 |  0.000000E+00 |  8.8249697052 |             - |             -\n",
      "     3 |      300 |      4 |  0.000000E+00 |  2.4109131133 |  1.0000000000 |         ideal\n",
      "     4 |      400 |      2 |  0.000000E+00 |  0.6301372314 |  0.5008287458 |         ideal\n",
      "     5 |      500 |      3 |  0.000000E+00 |  0.1422860879 |  0.0887422215 |         ideal\n",
      "     6 |      600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1302770108 |         ideal\n",
      "     7 |      700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.2535141827 |         ideal\n",
      "     8 |      800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0138548970 |             f\n",
      "     9 |      900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0155077529 |         ideal\n",
      "    10 |     1000 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0181721535 |             f\n",
      "    11 |     1100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0726931823 |         ideal\n",
      "    12 |     1200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0103478863 |         ideal\n",
      "    13 |     1300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0045139830 |         ideal\n",
      "    14 |     1400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0429629108 |         nadir\n",
      "    15 |     1500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0307885920 |         ideal\n",
      "    16 |     1600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0040471305 |         ideal\n",
      "    17 |     1700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0551839392 |         nadir\n",
      "    18 |     1800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0073550774 |         ideal\n",
      "    19 |     1900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    20 |     2000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0189750700 |         ideal\n",
      "    21 |     2100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0114308768 |         ideal\n",
      "    22 |     2200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0049015371 |         ideal\n",
      "    23 |     2300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0277507544 |         nadir\n",
      "    24 |     2400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0097479656 |         ideal\n",
      "    25 |     2500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0093474107 |         ideal\n",
      "    26 |     2600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0391504740 |         nadir\n",
      "    27 |     2700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0664367452 |         nadir\n",
      "    28 |     2800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0177943487 |         ideal\n",
      "    29 |     2900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0044313692 |         ideal\n",
      "    30 |     3000 |      7 |  0.000000E+00 |  0.000000E+00 |  0.0027418739 |         ideal\n",
      "    31 |     3100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0075522362 |             f\n",
      "    32 |     3200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0126670470 |         ideal\n",
      "    33 |     3300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0277052904 |         nadir\n",
      "    34 |     3400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0469214868 |         nadir\n",
      "    35 |     3500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0186672136 |             f\n",
      "    36 |     3600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0050775235 |         nadir\n",
      "    37 |     3700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0278828875 |         ideal\n",
      "    38 |     3800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    39 |     3900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0029232901 |             f\n",
      "    40 |     4000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0107310700 |             f\n",
      "    41 |     4100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0082770509 |             f\n",
      "    42 |     4200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0228187145 |         nadir\n",
      "    43 |     4300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0194780204 |         ideal\n",
      "    44 |     4400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0302274303 |         ideal\n",
      "    45 |     4500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0117836537 |             f\n",
      "    46 |     4600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0008372108 |             f\n",
      "    47 |     4700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0055394689 |         nadir\n",
      "    48 |     4800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0317548041 |         nadir\n",
      "    49 |     4900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0411997005 |         nadir\n",
      "    50 |     5000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0027741638 |         ideal\n",
      "    51 |     5100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    52 |     5200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0026617401 |         ideal\n",
      "    53 |     5300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0102653681 |         nadir\n",
      "    54 |     5400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0143849845 |         ideal\n",
      "    55 |     5500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    56 |     5600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0020406798 |             f\n",
      "    57 |     5700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0112899979 |         ideal\n",
      "    58 |     5800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    59 |     5900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0543759788 |         nadir\n",
      "    60 |     6000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    61 |     6100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    62 |     6200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0125069543 |         ideal\n",
      "    63 |     6300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0100504310 |         nadir\n",
      "    64 |     6400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0077539290 |         nadir\n",
      "    65 |     6500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0069898479 |             f\n",
      "    66 |     6600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0265136827 |         nadir\n",
      "    67 |     6700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    68 |     6800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    69 |     6900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0045376031 |             f\n",
      "    70 |     7000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0076758074 |         nadir\n",
      "    71 |     7100 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0057865343 |             f\n",
      "    72 |     7200 |      6 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    73 |     7300 |      7 |  0.000000E+00 |  0.000000E+00 |  0.0047043745 |             f\n",
      "    74 |     7400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0224019238 |         nadir\n",
      "    75 |     7500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019023626 |             f\n",
      "    76 |     7600 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0046165059 |         nadir\n",
      "    77 |     7700 |      7 |  0.000000E+00 |  0.000000E+00 |  0.0027777005 |         nadir\n",
      "    78 |     7800 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0178602814 |         nadir\n",
      "    79 |     7900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0282393049 |         nadir\n",
      "    80 |     8000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0085067600 |         ideal\n",
      "    81 |     8100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0083842317 |         ideal\n",
      "    82 |     8200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0167096493 |         nadir\n",
      "    83 |     8300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0111248877 |         nadir\n",
      "    84 |     8400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    85 |     8500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0043612161 |             f\n",
      "    86 |     8600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0064909073 |             f\n",
      "    87 |     8700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0065949650 |             f\n",
      "    88 |     8800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0164572911 |         nadir\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    89 |     8900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    90 |     9000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    91 |     9100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0027005114 |             f\n",
      "    92 |     9200 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0019541165 |             f\n",
      "    93 |     9300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0081506724 |         ideal\n",
      "    94 |     9400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0042338057 |         nadir\n",
      "    95 |     9500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0095617828 |         nadir\n",
      "    96 |     9600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0014078612 |             f\n",
      "    97 |     9700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0102450845 |         nadir\n",
      "    98 |     9800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0183249443 |         nadir\n",
      "    99 |     9900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   100 |    10000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0049762908 |             f\n",
      "   101 |    10100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0025830243 |             f\n",
      "   102 |    10200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   103 |    10300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0181870297 |         nadir\n",
      "   104 |    10400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0032917780 |         ideal\n",
      "   105 |    10500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0036508185 |             f\n",
      "   106 |    10600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0045402911 |         ideal\n",
      "   107 |    10700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0074629273 |         nadir\n",
      "   108 |    10800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0063763135 |             f\n",
      "   109 |    10900 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0016854880 |             f\n",
      "   110 |    11000 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0040887907 |             f\n",
      "   111 |    11100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0626728358 |         nadir\n",
      "   112 |    11200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0047737417 |         ideal\n",
      "   113 |    11300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   114 |    11400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   115 |    11500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0021850201 |             f\n",
      "   116 |    11600 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0075065503 |             f\n",
      "   117 |    11700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0084000413 |         nadir\n",
      "   118 |    11800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0059919718 |         ideal\n",
      "   119 |    11900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0203138202 |         nadir\n",
      "   120 |    12000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0067153039 |         ideal\n",
      "   121 |    12100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   122 |    12200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0009730519 |             f\n",
      "   123 |    12300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0056261921 |         ideal\n",
      "   124 |    12400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0092399416 |         nadir\n",
      "   125 |    12500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0088007958 |         nadir\n",
      "   126 |    12600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0048028303 |             f\n",
      "   127 |    12700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   128 |    12800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0080894609 |             f\n",
      "   129 |    12900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0082618696 |         nadir\n",
      "   130 |    13000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0102374453 |         nadir\n",
      "   131 |    13100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0045175665 |         nadir\n",
      "   132 |    13200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0032944852 |         ideal\n",
      "   133 |    13300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0238576056 |         nadir\n",
      "   134 |    13400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0030993475 |         nadir\n",
      "   135 |    13500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0032827519 |         ideal\n",
      "   136 |    13600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0047258960 |         ideal\n",
      "   137 |    13700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0110171371 |             f\n",
      "   138 |    13800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   139 |    13900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0003622634 |             f\n",
      "   140 |    14000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0007330752 |             f\n",
      "   141 |    14100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0088504621 |         nadir\n",
      "   142 |    14200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004723919 |             f\n",
      "   143 |    14300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0335534373 |         nadir\n",
      "   144 |    14400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   145 |    14500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   146 |    14600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0125013766 |             f\n",
      "   147 |    14700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0262588665 |         nadir\n",
      "   148 |    14800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0071369542 |         ideal\n",
      "   149 |    14900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   150 |    15000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0035965369 |         nadir\n",
      "   151 |    15100 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0023569999 |             f\n",
      "   152 |    15200 |      7 |  0.000000E+00 |  0.000000E+00 |  0.0065048963 |             f\n",
      "   153 |    15300 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0148086145 |         nadir\n",
      "   154 |    15400 |      6 |  0.000000E+00 |  0.000000E+00 |  0.0147002041 |         nadir\n",
      "   155 |    15500 |      7 |  0.000000E+00 |  0.000000E+00 |  0.0000637477 |             f\n",
      "   156 |    15600 |      7 |  0.000000E+00 |  0.000000E+00 |  0.0002873038 |             f\n",
      "   157 |    15700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0230759197 |         nadir\n",
      "   158 |    15800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   159 |    15900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0033909472 |             f\n",
      "   160 |    16000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   161 |    16100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   162 |    16200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0096557807 |         ideal\n",
      "   163 |    16300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0116073570 |         nadir\n",
      "   164 |    16400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0135075154 |         nadir\n",
      "   165 |    16500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   166 |    16600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   167 |    16700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0217310236 |         nadir\n",
      "   168 |    16800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   169 |    16900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0091697106 |             f\n",
      "   170 |    17000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0035623546 |         ideal\n",
      "   171 |    17100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   172 |    17200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   173 |    17300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   174 |    17400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   175 |    17500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0007864296 |             f\n",
      "   176 |    17600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0007864296 |             f\n",
      "   177 |    17700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0026685099 |             f\n",
      "   178 |    17800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0047437359 |         nadir\n",
      "   179 |    17900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0304245479 |         nadir\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   180 |    18000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   181 |    18100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   182 |    18200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   183 |    18300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0034289970 |         nadir\n",
      "   184 |    18400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   185 |    18500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0026412414 |             f\n",
      "   186 |    18600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0175682357 |         nadir\n",
      "   187 |    18700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0006407632 |             f\n",
      "   188 |    18800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0006407632 |             f\n",
      "   189 |    18900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0105083076 |         nadir\n",
      "   190 |    19000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   191 |    19100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0072285029 |         ideal\n",
      "   192 |    19200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   193 |    19300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   194 |    19400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0088191741 |             f\n",
      "   195 |    19500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0031253182 |             f\n",
      "   196 |    19600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0074651560 |         nadir\n",
      "   197 |    19700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0001128917 |             f\n",
      "   198 |    19800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0029836360 |             f\n",
      "   199 |    19900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0221901825 |         nadir\n",
      "   200 |    20000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   201 |    20100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   202 |    20200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   203 |    20300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0026681314 |         nadir\n",
      "   204 |    20400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0006089207 |             f\n",
      "   205 |    20500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0006089207 |             f\n",
      "   206 |    20600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0039258773 |             f\n",
      "   207 |    20700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   208 |    20800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   209 |    20900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0039614780 |         ideal\n",
      "   210 |    21000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0005695622 |             f\n",
      "   211 |    21100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0060131702 |         nadir\n",
      "   212 |    21200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0129426043 |         nadir\n",
      "   213 |    21300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   214 |    21400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0010591632 |             f\n",
      "   215 |    21500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0024243088 |             f\n",
      "   216 |    21600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0039852722 |             f\n",
      "   217 |    21700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   218 |    21800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0006216462 |             f\n",
      "   219 |    21900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0060081111 |         ideal\n",
      "   220 |    22000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0039589513 |             f\n",
      "   221 |    22100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   222 |    22200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0008476750 |             f\n",
      "   223 |    22300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0012404922 |             f\n",
      "   224 |    22400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0012404922 |             f\n",
      "   225 |    22500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0033944853 |         nadir\n",
      "   226 |    22600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   227 |    22700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0031945993 |             f\n",
      "   228 |    22800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0058416242 |             f\n",
      "   229 |    22900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0269003847 |         ideal\n",
      "   230 |    23000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   231 |    23100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0213998858 |         nadir\n",
      "   232 |    23200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   233 |    23300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   234 |    23400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   235 |    23500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   236 |    23600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0058754957 |             f\n",
      "   237 |    23700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   238 |    23800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0002058471 |             f\n",
      "   239 |    23900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0036299362 |             f\n",
      "   240 |    24000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0177984900 |         nadir\n",
      "   241 |    24100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0019715251 |             f\n",
      "   242 |    24200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0071810480 |             f\n",
      "   243 |    24300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0000296978 |             f\n",
      "   244 |    24400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0002337724 |             f\n",
      "   245 |    24500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0002337724 |             f\n",
      "   246 |    24600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0002337724 |             f\n",
      "   247 |    24700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0089551233 |             f\n",
      "   248 |    24800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   249 |    24900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   250 |    25000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0056156102 |             f\n",
      "   251 |    25100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   252 |    25200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004336238 |             f\n",
      "   253 |    25300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004336238 |             f\n",
      "   254 |    25400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004336238 |             f\n",
      "   255 |    25500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0033163642 |             f\n",
      "   256 |    25600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   257 |    25700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   258 |    25800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0031394128 |             f\n",
      "   259 |    25900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   260 |    26000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0021518999 |             f\n",
      "   261 |    26100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0021518999 |             f\n",
      "   262 |    26200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0079713830 |         nadir\n",
      "   263 |    26300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0009566898 |             f\n",
      "   264 |    26400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019164361 |             f\n",
      "   265 |    26500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019164361 |             f\n",
      "   266 |    26600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019164361 |             f\n",
      "   267 |    26700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0022358510 |             f\n",
      "   268 |    26800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0043924409 |         ideal\n",
      "   269 |    26900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   270 |    27000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0116239708 |         nadir\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   271 |    27100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0008465309 |             f\n",
      "   272 |    27200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0088026903 |         nadir\n",
      "   273 |    27300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0030831617 |             f\n",
      "   274 |    27400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019727744 |             f\n",
      "   275 |    27500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019727744 |             f\n",
      "   276 |    27600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0039411244 |             f\n",
      "   277 |    27700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   278 |    27800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   279 |    27900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0105411629 |         nadir\n",
      "   280 |    28000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0096130970 |         nadir\n",
      "   281 |    28100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0015468414 |             f\n",
      "   282 |    28200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0015468414 |             f\n",
      "   283 |    28300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0015468414 |             f\n",
      "   284 |    28400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0015468414 |             f\n",
      "   285 |    28500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0015468414 |             f\n",
      "   286 |    28600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0031317001 |         ideal\n",
      "   287 |    28700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0001551275 |             f\n",
      "   288 |    28800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0038131655 |             f\n",
      "   289 |    28900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0041556393 |         nadir\n",
      "   290 |    29000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0061273183 |         nadir\n",
      "   291 |    29100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   292 |    29200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004101964 |             f\n",
      "   293 |    29300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004101964 |             f\n",
      "   294 |    29400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0016248950 |             f\n",
      "   295 |    29500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0048968135 |             f\n",
      "   296 |    29600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0000968403 |             f\n",
      "   297 |    29700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0060628735 |             f\n",
      "   298 |    29800 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0065287229 |             f\n",
      "   299 |    29900 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   300 |    30000 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   301 |    30100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0007450075 |             f\n",
      "   302 |    30200 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0307426351 |         nadir\n",
      "   303 |    30300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   304 |    30400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0056748314 |             f\n",
      "   305 |    30500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   306 |    30600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   307 |    30700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0011444197 |             f\n",
      "   308 |    30800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0064059894 |             f\n",
      "   309 |    30900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0010075762 |             f\n",
      "   310 |    31000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0017655372 |             f\n",
      "   311 |    31100 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0036631245 |             f\n",
      "   312 |    31200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0051147253 |             f\n",
      "   313 |    31300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0035226858 |         nadir\n",
      "   314 |    31400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0052488456 |         ideal\n",
      "   315 |    31500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0001244481 |             f\n",
      "   316 |    31600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0003592423 |             f\n",
      "   317 |    31700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0034146358 |         ideal\n",
      "   318 |    31800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0030158349 |         ideal\n",
      "   319 |    31900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   320 |    32000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   321 |    32100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0178997682 |         nadir\n",
      "   322 |    32200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   323 |    32300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0003252755 |             f\n",
      "   324 |    32400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0003252755 |             f\n",
      "   325 |    32500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0003252755 |             f\n",
      "   326 |    32600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0063253829 |             f\n",
      "   327 |    32700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   328 |    32800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004317776 |             f\n",
      "   329 |    32900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0004317776 |             f\n",
      "   330 |    33000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0037340799 |             f\n",
      "   331 |    33100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   332 |    33200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0029602795 |         ideal\n",
      "   333 |    33300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0054708721 |         ideal\n",
      "   334 |    33400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0028364029 |             f\n",
      "   335 |    33500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0044868570 |             f\n",
      "   336 |    33600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0038826874 |         ideal\n",
      "   337 |    33700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   338 |    33800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   339 |    33900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   340 |    34000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   341 |    34100 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0025087362 |         ideal\n",
      "   342 |    34200 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0054424018 |         nadir\n",
      "   343 |    34300 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   344 |    34400 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   345 |    34500 |      5 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   346 |    34600 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0019984802 |             f\n",
      "   347 |    34700 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0020761863 |             f\n",
      "   348 |    34800 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0020761863 |             f\n",
      "   349 |    34900 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0020761863 |             f\n",
      "   350 |    35000 |      5 |  0.000000E+00 |  0.000000E+00 |  0.0067443765 |         ideal\n",
      "Solver time : 112.20\n"
     ]
    }
   ],
   "source": [
    "start = time.perf_counter()\n",
    "res = minimize(problem,\n",
    "               algorithm,\n",
    "               termination,\n",
    "               seed=1,\n",
    "               save_history=True,\n",
    "               verbose=True)\n",
    "print('Solver time : {:.2F}'.format(time.perf_counter() - start))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdcaefa0",
   "metadata": {},
   "source": [
    "## Plots the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "aaae91ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      " {'x01': 14, 'x02': 0.0003771339556337345, 'x03': 0.00011361895541847275, 'x04': 0.00016947948529050239, 'x05': 0.0003727563848156051, 'x06': 6.550358439319795e-06, 'x07': 0.0003645176337074167, 'x08': 2.973473457420421e-05, 'x09': 3.297604959322221e-05, 'x10': 0.0004008135057197896, 'x11': 9.61966947313631e-07, 'x12': 0.000347552734124836, 'x13': 6.641918932751157e-07, 'x14': 2.656403922164266e-07, 'x15': 0.0003418433374500965, 'x16': 4.824314959774508e-05, 'x17': 0.00024115444208164182, 'x18': 3.013126472196695e-07, 'x19': 4.091062322694051e-06, 'x20': 0.00023552914309592695, 'x21': 0.00015697058009957353, 'x22': 0.00017755111048219972, 'x23': 0.0001311207702952006, 'x24': 0.00012113634649195286, 'x25': 0.00019694485008104676, 'x26': 4.1580820249260534e-05, 'x27': 0.00015196082383919587, 'x28': 0.00021039618617201334, 'x29': 0.00019063420028751993, 'x30': 0.00021278501616967224, 'x31': 0.0002615971583460213, 'x32': 0.0003113798649883251, 'x33': 1.930353965950921e-05, 'x34': 6.319816532821756e-06, 'x35': 2.821803210380282e-06, 'x36': 2.004535389576695e-05, 'x37': 0.000268020747730177, 'x38': 0.00028740954918455566, 'x39': 1.4845080169989692e-05, 'x40': 1.8346639469266097e-05, 'x41': 3.184931468414705e-07, 'x42': 1.951102600063735e-06, 'x43': 0.0002879262065530007, 'x44': 0.00014395621392054373, 'x45': 0.00013681087112450978, 'x46': 0.00019409825822856562, 'x47': 0.00018045316240477408, 'x48': 0.00012312980609109774}\n",
      " {'x01': 9, 'x02': 0.0003747043853034819, 'x03': 0.00022371880129531613, 'x04': 0.00016965062167348475, 'x05': 0.00032459401795146317, 'x06': 7.855172256524893e-06, 'x07': 0.0004132589424373491, 'x08': 2.6755807838615674e-05, 'x09': 2.1542620963577106e-05, 'x10': 0.000400355903035435, 'x11': 1.0781420109855235e-06, 'x12': 0.00033899252806617893, 'x13': 6.306898472942803e-07, 'x14': 2.7006467956694144e-07, 'x15': 0.00034235529532402763, 'x16': 6.209954215128821e-05, 'x17': 0.00024402955369461654, 'x18': 1.5230158092304134e-07, 'x19': 1.3925305262039954e-06, 'x20': 0.0002333595565897344, 'x21': 0.00016036943831961647, 'x22': 0.00017714759184265423, 'x23': 0.00013141210729629793, 'x24': 0.00013450792247474602, 'x25': 0.00016434240184427462, 'x26': 8.576798218534816e-05, 'x27': 0.0001533038868026774, 'x28': 0.00020655877417945673, 'x29': 0.00021039168793767038, 'x30': 0.0002157322037734604, 'x31': 0.0002621462504886377, 'x32': 0.00031115199527198073, 'x33': 4.9079505369302974e-05, 'x34': 8.722934361399282e-06, 'x35': 5.6339770416912185e-06, 'x36': 2.0871421680885038e-05, 'x37': 0.0002725454771954126, 'x38': 0.0002864154599617121, 'x39': 0.0002413132578000466, 'x40': 2.5016566288899066e-05, 'x41': 3.396418404275525e-07, 'x42': 1.5554258245663767e-06, 'x43': 0.0003083922627302164, 'x44': 0.00015225184626780781, 'x45': 0.0001483868987481541, 'x46': 0.00022396156565668887, 'x47': 0.00019808167686673298, 'x48': 0.0002094902020867095}\n",
      " {'x01': 5, 'x02': 0.0006045602014179762, 'x03': 0.00021820620289151308, 'x04': 0.00017044393293596779, 'x05': 0.0005982629417929222, 'x06': 5.881300796244287e-06, 'x07': 0.0004173740428029993, 'x08': 0.00016051872655814222, 'x09': 0.0002132571850802912, 'x10': 0.0004762329828743746, 'x11': 5.636172511396791e-07, 'x12': 0.0005142453567768864, 'x13': 3.403206933456143e-05, 'x14': 4.965721465598639e-07, 'x15': 0.00046008197355341024, 'x16': 6.229803211532923e-05, 'x17': 0.0003148915336430855, 'x18': 1.2062205157658205e-06, 'x19': 5.720589497136353e-06, 'x20': 0.00037520379080698257, 'x21': 0.00017061129349508155, 'x22': 0.0003595453730755853, 'x23': 0.0001593628995273196, 'x24': 0.0001406760678955947, 'x25': 0.00023515272086059046, 'x26': 5.432596751648571e-05, 'x27': 0.000266982720373258, 'x28': 0.00029307859542253664, 'x29': 0.00022136677161799424, 'x30': 0.0002593618173467408, 'x31': 0.0003250741770255484, 'x32': 0.0004204990383305327, 'x33': 4.7711236389612696e-05, 'x34': 7.320837472087367e-05, 'x35': 5.037928564169418e-05, 'x36': 2.1196602208992314e-05, 'x37': 0.00040422368963516744, 'x38': 0.000410454885717036, 'x39': 0.0002274164461270493, 'x40': 3.0361765202100586e-05, 'x41': 1.7010374905762545e-06, 'x42': 2.2137010580043507e-06, 'x43': 0.00046794329973530484, 'x44': 0.00024759984702030354, 'x45': 0.0002020811782469221, 'x46': 0.0003180167775878184, 'x47': 0.0005589504727115843, 'x48': 0.0001301866053872087}]\n"
     ]
    }
   ],
   "source": [
    "X = res.X\n",
    "F = res.F\n",
    "G = res.G\n",
    "Z_res = [[d['x01']] for d in X]\n",
    "\n",
    "\n",
    "names = []\n",
    "types = []\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "legend_dict = {}\n",
    "\n",
    "for xData in Z_res:\n",
    "    matname = dataIdentifier['name'][int(xData[0])]\n",
    "    mattype = dataIdentifier['className'][int(xData[0])]\n",
    "    names.append(matname)\n",
    "    types.append(mattype)\n",
    "    \n",
    "unique_labels = list(set(types))\n",
    "\n",
    "# Define specific colors for each material type\n",
    "mat_colors = {\n",
    "    'Steel': 'slategrey',\n",
    "    'Aluminium Alloys': 'violet',\n",
    "    'Plastics': 'lawngreen',\n",
    "    'Titanium Alloys': 'indigo',\n",
    "    'Copper Alloys': 'chocolate',\n",
    "    'Composites': 'gold',\n",
    "    # Add more material types and corresponding colors as needed\n",
    "}\n",
    "\n",
    "\n",
    "for i, mattype in enumerate(types):\n",
    "    if mattype not in mat_colors:\n",
    "        mat_colors[mattype] = plt.cm.get_cmap('jet')(i / len(set(types)))\n",
    "        \n",
    "\n",
    "\n",
    "# add scatter plot for each unique label\n",
    "for i, (x, y) in enumerate(F):\n",
    "    #if i == 3:  # Exclude the third value (index 2)\n",
    "        #continue\n",
    "    material = names[i]\n",
    "    mattype = types[i]\n",
    "    color = mat_colors[mattype]\n",
    "    label = mattype\n",
    "    ax.scatter(x, y, color=color, label=label)\n",
    "    ax.text(x + 0.1, y + 0.1, material)\n",
    "    if mattype not in legend_dict:\n",
    "        legend_dict[mattype] = ax.scatter(x, y, color=color, label=label)\n",
    "\n",
    "\n",
    "# set legend colors and remove duplicates\n",
    "handles, labels = [], []\n",
    "for label in legend_dict:\n",
    "    handles.append(legend_dict[label])\n",
    "    labels.append(label)\n",
    "    legend_dict[label].set_color(mat_colors[label])\n",
    "    \n",
    "ax.legend(handles, labels, loc=\"upper right\")\n",
    "\n",
    "\n",
    "# show plot\n",
    "plt.title(\"Objective Space\")\n",
    "entry_order = ['cost', 'mass', 'co2', 'water', 'energy', 'compliance']\n",
    "enabled_entries = [entry for entry in entry_order if objectives[entry]['isOn']]\n",
    "ax.set_xlabel(enabled_entries[0])\n",
    "ax.set_ylabel(enabled_entries[1])\n",
    "plt.savefig('./figures_Integer/Integer_mass_cost.png',bbox_inches='tight', dpi = 200)\n",
    "plt.show()\n",
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "559e39c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "objectives2 = {'cost': {'isOn':True},\\\n",
    "              'mass': {'isOn':False}, \\\n",
    "              'co2': {'isOn':True},\\\n",
    "              'water': {'isOn':False},\\\n",
    "              'energy': {'isOn':False},\\\n",
    "              'compliance': {'isOn': False}}\n",
    "               \n",
    "# count the number of entries with 'isOn' set to True\n",
    "no = sum(1 for v in objectives.values() if v['isOn'])\n",
    "nc = sum(1 for v in constraints.values() if v['isOn'])\n",
    "\n",
    "# print an error message in red if there are 3 or more entries with 'isOn' set to True\n",
    "if no >= 3:\n",
    "    print('Error: Three or more entries have isOn=True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8c312728",
   "metadata": {},
   "outputs": [],
   "source": [
    "class MixedVarsZDT1(ElementwiseProblem):\n",
    "\n",
    "    def __init__(self, truss, trainInfo , constraints, objectives2, nc, no, nmat, **kwargs):\n",
    "\n",
    "        variables = dict()\n",
    "\n",
    "        variables[f\"x01\"] = Integer(bounds=(0, nmat-1))\n",
    "\n",
    "        for k in range(2, 49):\n",
    "            variables[f\"x{k:02}\"] = Real(bounds=(2e-8, 2e-3))\n",
    "\n",
    "        super().__init__(vars=variables, n_obj=no, n_ieq_constr=nc, **kwargs)\n",
    "        \n",
    "        self.truss=truss\n",
    "        self.trainInfo=trainInfo\n",
    "        self.constraints=constraints\n",
    "        self.objectives=objectives2\n",
    "        \n",
    "    def _evaluate(self, x, out, *args, **kwargs):\n",
    "        x = np.array([x[f\"x{k:02}\"] for k in range(1, 49)])\n",
    "        \n",
    "        matprop=trainInfo[int(x[0]),:]  \n",
    "        \n",
    "        x_tensor = torch.from_numpy(x[1:])\n",
    "        area = x_tensor * torch.ones((connectivity.shape[0]))   \n",
    "        u, _, _, _, internalForce = truss.solveFE(E = torch.tensor([matprop[0]]).float(), A=area)\n",
    "        compliance = truss.computeCompliance(u)\n",
    "        volume = truss.getVolume(area)\n",
    "        mass = matprop[2]*volume\n",
    "        cost = mass*matprop[1]\n",
    "        co2 = mass*matprop[4]\n",
    "        energy = mass*matprop[5]        \n",
    "        water = mass*matprop[6] \n",
    "        \n",
    "        \n",
    "        \n",
    "        con_values = []\n",
    "        \n",
    "        if(constraints['massCons']['isOn']):\n",
    "            constraints['massCons']['value'] = (mass/constraints['massCons']['maxMass']) - 1.\n",
    "            con_values.append(constraints['massCons']['value'])\n",
    "\n",
    "        if(constraints['costCons']['isOn']):\n",
    "            constraints['costCons']['value'] = (cost/constraints['costCons']['maxCost']) - 1.\n",
    "            con_values.append(constraints['costCons']['value'])\n",
    "\n",
    "        if(constraints['tensionCons']['isOn']):\n",
    "            tensileForce = 0.001+torch.relu(internalForce)\n",
    "            tensileStress = tensileForce/area\n",
    "            maxTensileStressExperienced = torch.pow(torch.sum(tensileStress**6), 1./6)*constraints['tensionCons']['FOS']\n",
    "            constraints['tensionCons']['value'] = (maxTensileStressExperienced/matprop[3]) - 1.\n",
    "            con_values.append(constraints['tensionCons']['value'])\n",
    "\n",
    "        if(constraints['complianceCons']['isOn']):\n",
    "            constraints['complianceCons']['value'] = (compliance/constraints['complianceCons']['maxJ']) - 1.\n",
    "            con_values.append(constraints['complianceCons']['value'])\n",
    "\n",
    "        if(constraints['compressionCons']['isOn']):\n",
    "            compressiveForce = 0.001+torch.relu(-internalForce)\n",
    "            k = 4. # used in geom factor... see buckling theory\n",
    "            geomFactor = k*(self.truss.barLength/(np.pi*area))**2\n",
    "            compressiveStress = compressiveForce*geomFactor\n",
    "            maxCompressiveStressExperienced = torch.pow(torch.sum(compressiveStress**6), 1./6)*constraints['compressionCons']['FOS']\n",
    "            constraints['compressionCons']['value'] = (maxCompressiveStressExperienced/matprop[0]) - 1.\n",
    "            con_values.append(constraints['compressionCons']['value'])\n",
    "\n",
    "        if(constraints['co2Cons']['isOn']):\n",
    "            constraints['co2Cons']['value'] = (co2/constraints['co2Cons']['maxco2']) - 1.\n",
    "            con_values.append(constraints['co2Cons']['value'])\n",
    "\n",
    "        if(constraints['energyCons']['isOn']):\n",
    "            constraints['energyCons']['value'] = (energy/constraints['energyCons']['maxenergy']) - 1.\n",
    "            con_values.append(constraints['energyCons']['value'])\n",
    "\n",
    "        if(constraints['waterCons']['isOn']):\n",
    "            constraints['waterCons']['value'] = (water/constraints['waterCons']['maxwater']) - 1.\n",
    "            con_values.append(constraints['waterCons']['value'])\n",
    "            \n",
    "        \n",
    "        \n",
    "        obj_values = []\n",
    "        \n",
    "        if(objectives2['cost']['isOn']):\n",
    "            obj_values.append(cost)\n",
    "            \n",
    "        if(objectives2['mass']['isOn']):\n",
    "            obj_values.append(mass)\n",
    "            \n",
    "        if(objectives2['co2']['isOn']):\n",
    "            obj_values.append(co2)\n",
    "            \n",
    "        if(objectives2['water']['isOn']):\n",
    "            obj_values.append(water)\n",
    "            \n",
    "        if(objectives2['energy']['isOn']):\n",
    "            obj_values.append(energy)\n",
    "            \n",
    "        if(objectives2['compliance']['isOn']):\n",
    "            obj_values.append(compliance)\n",
    "            \n",
    "  \n",
    "\n",
    "        out[\"F\"] = np.array(obj_values)\n",
    "        out[\"G\"] = np.array(con_values)\n",
    "        \n",
    "  \n",
    "problem2 = MixedVarsZDT1(truss,trainInfo , constraints, objectives2, nc, no, nmat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "529e7496",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================================================\n",
      "n_gen  |  n_eval  | n_nds  |     cv_min    |     cv_avg    |      eps      |   indicator  \n",
      "==========================================================================================\n",
      "     1 |      100 |      1 |  0.2129996812 |  3.700016E+04 |             - |             -\n",
      "     2 |      200 |      1 |  0.000000E+00 |  8.8249697052 |             - |             -\n",
      "     3 |      300 |      2 |  0.000000E+00 |  2.4707742610 |  3.3726215167 |         ideal\n",
      "     4 |      400 |      3 |  0.000000E+00 |  0.7012653364 |  0.2712884129 |         ideal\n",
      "     5 |      500 |      3 |  0.000000E+00 |  0.1345439833 |  0.1738551891 |         ideal\n",
      "     6 |      600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1433514120 |         ideal\n",
      "     7 |      700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "     8 |      800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "     9 |      900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    10 |     1000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1134043968 |             f\n",
      "    11 |     1100 |      2 |  0.000000E+00 |  0.000000E+00 |  0.2757702204 |         ideal\n",
      "    12 |     1200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0724505543 |         ideal\n",
      "    13 |     1300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0330088166 |         ideal\n",
      "    14 |     1400 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0491751102 |         ideal\n",
      "    15 |     1500 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0043626283 |         ideal\n",
      "    16 |     1600 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0246470387 |         ideal\n",
      "    17 |     1700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0862312059 |         ideal\n",
      "    18 |     1800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0345299900 |         ideal\n",
      "    19 |     1900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0296133020 |         ideal\n",
      "    20 |     2000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001303289 |             f\n",
      "    21 |     2100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0670745659 |         ideal\n",
      "    22 |     2200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0475755712 |         ideal\n",
      "    23 |     2300 |      4 |  0.000000E+00 |  0.000000E+00 |  0.1322705533 |             f\n",
      "    24 |     2400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1343291665 |             f\n",
      "    25 |     2500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    26 |     2600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0039615650 |         ideal\n",
      "    27 |     2700 |      4 |  0.000000E+00 |  0.000000E+00 |  0.0052907750 |         ideal\n",
      "    28 |     2800 |      2 |  0.000000E+00 |  0.000000E+00 |  0.2945841883 |         ideal\n",
      "    29 |     2900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1981484495 |         ideal\n",
      "    30 |     3000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0339672280 |         ideal\n",
      "    31 |     3100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1870768876 |         ideal\n",
      "    32 |     3200 |      1 |  0.000000E+00 |  0.000000E+00 |  2.688274E+01 |         ideal\n",
      "    33 |     3300 |      1 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    34 |     3400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0934819340 |         ideal\n",
      "    35 |     3500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0361583018 |         ideal\n",
      "    36 |     3600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0783941096 |         ideal\n",
      "    37 |     3700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.2004387135 |         ideal\n",
      "    38 |     3800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1115487380 |         ideal\n",
      "    39 |     3900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0451315431 |         ideal\n",
      "    40 |     4000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    41 |     4100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0368061700 |         ideal\n",
      "    42 |     4200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0835683545 |             f\n",
      "    43 |     4300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0034630855 |         ideal\n",
      "    44 |     4400 |      2 |  0.000000E+00 |  0.000000E+00 |  0.2245456356 |         ideal\n",
      "    45 |     4500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1110416644 |         ideal\n",
      "    46 |     4600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1608660927 |         ideal\n",
      "    47 |     4700 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0743011365 |         ideal\n",
      "    48 |     4800 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    49 |     4900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1139566272 |         ideal\n",
      "    50 |     5000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0711088333 |         ideal\n",
      "    51 |     5100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0334843510 |         ideal\n",
      "    52 |     5200 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0702285777 |         ideal\n",
      "    53 |     5300 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    54 |     5400 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    55 |     5500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0236170910 |         ideal\n",
      "    56 |     5600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0872053709 |         ideal\n",
      "    57 |     5700 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1364678401 |         ideal\n",
      "    58 |     5800 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0347717363 |         ideal\n",
      "    59 |     5900 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    60 |     6000 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    61 |     6100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1342646844 |         ideal\n",
      "    62 |     6200 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1708039065 |         ideal\n",
      "    63 |     6300 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    64 |     6400 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0087436596 |         ideal\n",
      "    65 |     6500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1191622215 |         ideal\n",
      "    66 |     6600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0508191391 |         ideal\n",
      "    67 |     6700 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1438367603 |         ideal\n",
      "    68 |     6800 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    69 |     6900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0750225679 |         ideal\n",
      "    70 |     7000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0210111865 |         ideal\n",
      "    71 |     7100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1101270883 |         ideal\n",
      "    72 |     7200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0198477854 |             f\n",
      "    73 |     7300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0196792539 |         ideal\n",
      "    74 |     7400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0083820989 |         ideal\n",
      "    75 |     7500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0048032017 |             f\n",
      "    76 |     7600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0773197960 |         ideal\n",
      "    77 |     7700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.8275346384 |         nadir\n",
      "    78 |     7800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0836916388 |         ideal\n",
      "    79 |     7900 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0105742818 |         ideal\n",
      "    80 |     8000 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    81 |     8100 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    82 |     8200 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0273164411 |         ideal\n",
      "    83 |     8300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0860009451 |         ideal\n",
      "    84 |     8400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0208575768 |         ideal\n",
      "    85 |     8500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0716839074 |         ideal\n",
      "    86 |     8600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0268377238 |         ideal\n",
      "    87 |     8700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0230435382 |             f\n",
      "    88 |     8800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0153860233 |         ideal\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    89 |     8900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    90 |     9000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0000959666 |             f\n",
      "    91 |     9100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0490977285 |         ideal\n",
      "    92 |     9200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0710317851 |         ideal\n",
      "    93 |     9300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0098089938 |             f\n",
      "    94 |     9400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0243651984 |         ideal\n",
      "    95 |     9500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0211281571 |             f\n",
      "    96 |     9600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0350873807 |         ideal\n",
      "    97 |     9700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "    98 |     9800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0031033919 |         ideal\n",
      "    99 |     9900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0965854360 |         ideal\n",
      "   100 |    10000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0756869935 |         ideal\n",
      "   101 |    10100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0099815263 |             f\n",
      "   102 |    10200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0855170471 |         ideal\n",
      "   103 |    10300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0379340703 |             f\n",
      "   104 |    10400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   105 |    10500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   106 |    10600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0659294724 |             f\n",
      "   107 |    10700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   108 |    10800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0058144330 |         ideal\n",
      "   109 |    10900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0123815276 |             f\n",
      "   110 |    11000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.1398055995 |         ideal\n",
      "   111 |    11100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   112 |    11200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   113 |    11300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0317088181 |         ideal\n",
      "   114 |    11400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   115 |    11500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0227367961 |         ideal\n",
      "   116 |    11600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0559517835 |         ideal\n",
      "   117 |    11700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0180114667 |         ideal\n",
      "   118 |    11800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   119 |    11900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0132553907 |         ideal\n",
      "   120 |    12000 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1342579684 |         ideal\n",
      "   121 |    12100 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   122 |    12200 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0117292752 |         ideal\n",
      "   123 |    12300 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0228022890 |         ideal\n",
      "   124 |    12400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0813989617 |         ideal\n",
      "   125 |    12500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0263467926 |         ideal\n",
      "   126 |    12600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0471272392 |         ideal\n",
      "   127 |    12700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0681787817 |         ideal\n",
      "   128 |    12800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   129 |    12900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0216931810 |         ideal\n",
      "   130 |    13000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0011718333 |             f\n",
      "   131 |    13100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0789529503 |         ideal\n",
      "   132 |    13200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0060820966 |         nadir\n",
      "   133 |    13300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0138097998 |         ideal\n",
      "   134 |    13400 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0273267644 |         ideal\n",
      "   135 |    13500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0499471862 |         ideal\n",
      "   136 |    13600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0412226263 |         ideal\n",
      "   137 |    13700 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0442054092 |         ideal\n",
      "   138 |    13800 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0266233663 |         ideal\n",
      "   139 |    13900 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0416439415 |         ideal\n",
      "   140 |    14000 |      2 |  0.000000E+00 |  0.000000E+00 |  0.1071716574 |         ideal\n",
      "   141 |    14100 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0156954955 |         ideal\n",
      "   142 |    14200 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   143 |    14300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0556457178 |         ideal\n",
      "   144 |    14400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0095899665 |         ideal\n",
      "   145 |    14500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0221128872 |         ideal\n",
      "   146 |    14600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0153904295 |             f\n",
      "   147 |    14700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0986813453 |         ideal\n",
      "   148 |    14800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   149 |    14900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0203845221 |             f\n",
      "   150 |    15000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0119678130 |         nadir\n",
      "   151 |    15100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0098010876 |             f\n",
      "   152 |    15200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0215725406 |         ideal\n",
      "   153 |    15300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0170646572 |         ideal\n",
      "   154 |    15400 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0816626869 |         ideal\n",
      "   155 |    15500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   156 |    15600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0044478719 |         ideal\n",
      "   157 |    15700 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0555065583 |         ideal\n",
      "   158 |    15800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0205841185 |         ideal\n",
      "   159 |    15900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   160 |    16000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   161 |    16100 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0153873519 |         ideal\n",
      "   162 |    16200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0417484454 |         ideal\n",
      "   163 |    16300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0229578411 |         ideal\n",
      "   164 |    16400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0517552158 |         ideal\n",
      "   165 |    16500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   166 |    16600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0420879855 |         ideal\n",
      "   167 |    16700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0154978499 |             f\n",
      "   168 |    16800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0173333805 |             f\n",
      "   169 |    16900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0213038931 |         ideal\n",
      "   170 |    17000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   171 |    17100 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0494639109 |         ideal\n",
      "   172 |    17200 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   173 |    17300 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   174 |    17400 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   175 |    17500 |      2 |  0.000000E+00 |  0.000000E+00 |  0.0026314161 |         ideal\n",
      "   176 |    17600 |      2 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   177 |    17700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0143079382 |         ideal\n",
      "   178 |    17800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0017480200 |             f\n",
      "   179 |    17900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0017480200 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   180 |    18000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0017480200 |             f\n",
      "   181 |    18100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0087863714 |         nadir\n",
      "   182 |    18200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   183 |    18300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   184 |    18400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0237864781 |         ideal\n",
      "   185 |    18500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0365110649 |         ideal\n",
      "   186 |    18600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   187 |    18700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0033686917 |         ideal\n",
      "   188 |    18800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0114969169 |             f\n",
      "   189 |    18900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0025828381 |         ideal\n",
      "   190 |    19000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0017396373 |             f\n",
      "   191 |    19100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0017396373 |             f\n",
      "   192 |    19200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0202591249 |         ideal\n",
      "   193 |    19300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0060221801 |             f\n",
      "   194 |    19400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   195 |    19500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0026269269 |             f\n",
      "   196 |    19600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   197 |    19700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   198 |    19800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0004128797 |             f\n",
      "   199 |    19900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0399020849 |         ideal\n",
      "   200 |    20000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0039617709 |             f\n",
      "   201 |    20100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0077169823 |             f\n",
      "   202 |    20200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   203 |    20300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0004066448 |             f\n",
      "   204 |    20400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0004066448 |             f\n",
      "   205 |    20500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0053075092 |         ideal\n",
      "   206 |    20600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0088142422 |         ideal\n",
      "   207 |    20700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0229525767 |         ideal\n",
      "   208 |    20800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0058041168 |             f\n",
      "   209 |    20900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   210 |    21000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   211 |    21100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   212 |    21200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0031542289 |         ideal\n",
      "   213 |    21300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   214 |    21400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0058960431 |             f\n",
      "   215 |    21500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   216 |    21600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   217 |    21700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0289193367 |         ideal\n",
      "   218 |    21800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0119508514 |         ideal\n",
      "   219 |    21900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   220 |    22000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0139035914 |         ideal\n",
      "   221 |    22100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   222 |    22200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   223 |    22300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0017272952 |             f\n",
      "   224 |    22400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0071564681 |         ideal\n",
      "   225 |    22500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0014276562 |             f\n",
      "   226 |    22600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0014276562 |             f\n",
      "   227 |    22700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0014276562 |             f\n",
      "   228 |    22800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0014276562 |             f\n",
      "   229 |    22900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0014276562 |             f\n",
      "   230 |    23000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0014276562 |             f\n",
      "   231 |    23100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0019388394 |             f\n",
      "   232 |    23200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0356092977 |         ideal\n",
      "   233 |    23300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   234 |    23400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   235 |    23500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   236 |    23600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   237 |    23700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0008157914 |             f\n",
      "   238 |    23800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0262376558 |         ideal\n",
      "   239 |    23900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   240 |    24000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0035164289 |         ideal\n",
      "   241 |    24100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0089033638 |         ideal\n",
      "   242 |    24200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   243 |    24300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0043163303 |             f\n",
      "   244 |    24400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0109460048 |         ideal\n",
      "   245 |    24500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   246 |    24600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   247 |    24700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   248 |    24800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   249 |    24900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   250 |    25000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0077894709 |         ideal\n",
      "   251 |    25100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0004113037 |             f\n",
      "   252 |    25200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0053359201 |         ideal\n",
      "   253 |    25300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   254 |    25400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0076871889 |             f\n",
      "   255 |    25500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   256 |    25600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   257 |    25700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   258 |    25800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   259 |    25900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0144863853 |         ideal\n",
      "   260 |    26000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0044223016 |         ideal\n",
      "   261 |    26100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   262 |    26200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   263 |    26300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   264 |    26400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   265 |    26500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   266 |    26600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   267 |    26700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   268 |    26800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   269 |    26900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   270 |    27000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   271 |    27100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002384338 |             f\n",
      "   272 |    27200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002384338 |             f\n",
      "   273 |    27300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0153979951 |         ideal\n",
      "   274 |    27400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0168100656 |         ideal\n",
      "   275 |    27500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001045946 |             f\n",
      "   276 |    27600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001045946 |             f\n",
      "   277 |    27700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001045946 |             f\n",
      "   278 |    27800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001045946 |             f\n",
      "   279 |    27900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0052701877 |             f\n",
      "   280 |    28000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0053943300 |             f\n",
      "   281 |    28100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   282 |    28200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0003405346 |             f\n",
      "   283 |    28300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0003405346 |             f\n",
      "   284 |    28400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0003405346 |             f\n",
      "   285 |    28500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0003405346 |             f\n",
      "   286 |    28600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0003405346 |             f\n",
      "   287 |    28700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0004344629 |             f\n",
      "   288 |    28800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0004344629 |             f\n",
      "   289 |    28900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0025004294 |         nadir\n",
      "   290 |    29000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0031579365 |         nadir\n",
      "   291 |    29100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0075966151 |         ideal\n",
      "   292 |    29200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0068256605 |         ideal\n",
      "   293 |    29300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0043452186 |         ideal\n",
      "   294 |    29400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   295 |    29500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   296 |    29600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   297 |    29700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   298 |    29800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   299 |    29900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   300 |    30000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   301 |    30100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0005934311 |             f\n",
      "   302 |    30200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0068012442 |         nadir\n",
      "   303 |    30300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   304 |    30400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001028064 |             f\n",
      "   305 |    30500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001660554 |             f\n",
      "   306 |    30600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0001660554 |             f\n",
      "   307 |    30700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0005200998 |             f\n",
      "   308 |    30800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0013147820 |             f\n",
      "   309 |    30900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0068443183 |             f\n",
      "   310 |    31000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0009227284 |             f\n",
      "   311 |    31100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0087783066 |         ideal\n",
      "   312 |    31200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   313 |    31300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0003346588 |             f\n",
      "   314 |    31400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0055919482 |         ideal\n",
      "   315 |    31500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   316 |    31600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   317 |    31700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0070540311 |         ideal\n",
      "   318 |    31800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0000960777 |             f\n",
      "   319 |    31900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0007559796 |             f\n",
      "   320 |    32000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0007559796 |             f\n",
      "   321 |    32100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0072674878 |         nadir\n",
      "   322 |    32200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   323 |    32300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   324 |    32400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002238900 |             f\n",
      "   325 |    32500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002238900 |             f\n",
      "   326 |    32600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002238900 |             f\n",
      "   327 |    32700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002238900 |             f\n",
      "   328 |    32800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002238900 |             f\n",
      "   329 |    32900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002238900 |             f\n",
      "   330 |    33000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002272461 |             f\n",
      "   331 |    33100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0002272461 |             f\n",
      "   332 |    33200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0019942038 |             f\n",
      "   333 |    33300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0019942038 |             f\n",
      "   334 |    33400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0019942038 |             f\n",
      "   335 |    33500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0040651784 |             f\n",
      "   336 |    33600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   337 |    33700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   338 |    33800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   339 |    33900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   340 |    34000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0038585440 |         ideal\n",
      "   341 |    34100 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   342 |    34200 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   343 |    34300 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0032157585 |             f\n",
      "   344 |    34400 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   345 |    34500 |      3 |  0.000000E+00 |  0.000000E+00 |  0.0027984235 |         nadir\n",
      "   346 |    34600 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   347 |    34700 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   348 |    34800 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   349 |    34900 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "   350 |    35000 |      3 |  0.000000E+00 |  0.000000E+00 |  0.000000E+00 |             f\n",
      "Solver time : 117.58\n"
     ]
    }
   ],
   "source": [
    "start = time.perf_counter()\n",
    "res2 = minimize(problem2,\n",
    "               algorithm,\n",
    "               termination,\n",
    "               seed=1,\n",
    "               save_history=True,\n",
    "               verbose=True)\n",
    "print('Solver time : {:.2F}'.format(time.perf_counter() - start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ae44ca79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'x01': 47, 'x02': 0.0006028439732116314, 'x03': 0.0002622106010612949, 'x04': 0.0002523763935911835, 'x05': 0.0006506766180058812, 'x06': 3.150134863868282e-05, 'x07': 0.0006764639323048898, 'x08': 0.0001643647229564307, 'x09': 0.00020073998857107663, 'x10': 0.0007289545506162272, 'x11': 6.438716068262682e-06, 'x12': 0.0006283751279582885, 'x13': 3.538916742238892e-05, 'x14': 1.934660340601024e-06, 'x15': 0.0005354418612876122, 'x16': 6.466635189965837e-05, 'x17': 0.0003809020651663772, 'x18': 1.4491764637197803e-06, 'x19': 2.2349664652889427e-05, 'x20': 0.0006513280103668162, 'x21': 0.00016036581819692662, 'x22': 0.0003814029120061315, 'x23': 0.0003654812346650533, 'x24': 0.00020253608696083902, 'x25': 0.0003509883699680166, 'x26': 0.00016409622231073435, 'x27': 0.0002869738634020082, 'x28': 0.00029660392744951865, 'x29': 0.0002565627357357406, 'x30': 0.0004275694331023017, 'x31': 0.00048544376565768955, 'x32': 0.0004258458776595507, 'x33': 0.00029558918626329105, 'x34': 3.1115969138602664e-05, 'x35': 8.338370807192658e-05, 'x36': 3.4584593806669674e-05, 'x37': 0.0004350426261932494, 'x38': 0.0005108073542952403, 'x39': 0.0005933096084771562, 'x40': 0.00013441681385596225, 'x41': 3.905424427075329e-06, 'x42': 9.71230157467626e-06, 'x43': 0.0005059416503455968, 'x44': 0.00040051184964015396, 'x45': 0.0003147756927065134, 'x46': 0.0004223793592763217, 'x47': 0.0004445660069088209, 'x48': 0.00023065383057012894}\n",
      " {'x01': 12, 'x02': 0.0003781305419338658, 'x03': 0.00010890554600087562, 'x04': 0.0001543732884510194, 'x05': 0.00032740077103232776, 'x06': 5.902491846212817e-06, 'x07': 0.000342132172666425, 'x08': 2.861057984578597e-05, 'x09': 3.878171320876342e-05, 'x10': 0.0004019664073299416, 'x11': 9.203821464006497e-07, 'x12': 0.0003475964168748459, 'x13': 6.70027838164297e-07, 'x14': 3.854445958761781e-07, 'x15': 0.00034243310552546543, 'x16': 5.4572571838497126e-05, 'x17': 0.00024560714102452936, 'x18': 1.521500858500984e-07, 'x19': 1.0128224412093904e-06, 'x20': 0.00023540011452796432, 'x21': 0.000160248218757905, 'x22': 0.0001762976911671738, 'x23': 0.00013084792956124277, 'x24': 0.00013510551947236, 'x25': 0.00023318923640707417, 'x26': 4.152414691091128e-05, 'x27': 0.00016103516467146423, 'x28': 0.00020759079572042953, 'x29': 0.00019287556270615417, 'x30': 0.00021298041213898075, 'x31': 0.0002614387496625685, 'x32': 0.0003110588086640517, 'x33': 2.2516092702502988e-05, 'x34': 1.620609690127184e-05, 'x35': 5.990865824961475e-06, 'x36': 1.564645192486376e-05, 'x37': 0.00026921687840378235, 'x38': 0.00028645134422292584, 'x39': 4.829121549281374e-05, 'x40': 1.7732237648354187e-05, 'x41': 4.779024950631828e-07, 'x42': 1.5593649613890684e-06, 'x43': 0.000308359972732382, 'x44': 0.00016972620107053347, 'x45': 0.00013167603025617615, 'x46': 0.00022378608219380993, 'x47': 0.00018195621301300626, 'x48': 0.00020560368269434743}\n",
      " {'x01': 14, 'x02': 0.0003771339556337345, 'x03': 0.00011361895541847275, 'x04': 0.00016947948529050239, 'x05': 0.0003727563848156051, 'x06': 6.550358439319795e-06, 'x07': 0.0003645176337074167, 'x08': 2.973473457420421e-05, 'x09': 3.297604959322221e-05, 'x10': 0.0004008135057197896, 'x11': 9.61966947313631e-07, 'x12': 0.000347552734124836, 'x13': 6.641918932751157e-07, 'x14': 2.656403922164266e-07, 'x15': 0.0003418433374500965, 'x16': 4.824314959774508e-05, 'x17': 0.00024115444208164182, 'x18': 3.013126472196695e-07, 'x19': 4.091062322694051e-06, 'x20': 0.00023552914309592695, 'x21': 0.00015697058009957353, 'x22': 0.00017755111048219972, 'x23': 0.0001311207702952006, 'x24': 0.00012113634649195286, 'x25': 0.00019694485008104676, 'x26': 4.1580820249260534e-05, 'x27': 0.00015196082383919587, 'x28': 0.00021039618617201334, 'x29': 0.00019063420028751993, 'x30': 0.00021278501616967224, 'x31': 0.0002615971583460213, 'x32': 0.0003113798649883251, 'x33': 1.930353965950921e-05, 'x34': 6.319816532821756e-06, 'x35': 2.821803210380282e-06, 'x36': 2.004535389576695e-05, 'x37': 0.000268020747730177, 'x38': 0.00028740954918455566, 'x39': 1.4845080169989692e-05, 'x40': 1.8346639469266097e-05, 'x41': 3.184931468414705e-07, 'x42': 1.951102600063735e-06, 'x43': 0.0002879262065530007, 'x44': 0.00014395621392054373, 'x45': 0.00013681087112450978, 'x46': 0.00019409825822856562, 'x47': 0.00018045316240477408, 'x48': 0.00012312980609109774}\n",
      " {'x01': 9, 'x02': 0.0003747043853034819, 'x03': 0.00022371880129531613, 'x04': 0.00016965062167348475, 'x05': 0.00032459401795146317, 'x06': 7.855172256524893e-06, 'x07': 0.0004132589424373491, 'x08': 2.6755807838615674e-05, 'x09': 2.1542620963577106e-05, 'x10': 0.000400355903035435, 'x11': 1.0781420109855235e-06, 'x12': 0.00033899252806617893, 'x13': 6.306898472942803e-07, 'x14': 2.7006467956694144e-07, 'x15': 0.00034235529532402763, 'x16': 6.209954215128821e-05, 'x17': 0.00024402955369461654, 'x18': 1.5230158092304134e-07, 'x19': 1.3925305262039954e-06, 'x20': 0.0002333595565897344, 'x21': 0.00016036943831961647, 'x22': 0.00017714759184265423, 'x23': 0.00013141210729629793, 'x24': 0.00013450792247474602, 'x25': 0.00016434240184427462, 'x26': 8.576798218534816e-05, 'x27': 0.0001533038868026774, 'x28': 0.00020655877417945673, 'x29': 0.00021039168793767038, 'x30': 0.0002157322037734604, 'x31': 0.0002621462504886377, 'x32': 0.00031115199527198073, 'x33': 4.9079505369302974e-05, 'x34': 8.722934361399282e-06, 'x35': 5.6339770416912185e-06, 'x36': 2.0871421680885038e-05, 'x37': 0.0002725454771954126, 'x38': 0.0002864154599617121, 'x39': 0.0002413132578000466, 'x40': 2.5016566288899066e-05, 'x41': 3.396418404275525e-07, 'x42': 1.5554258245663767e-06, 'x43': 0.0003083922627302164, 'x44': 0.00015225184626780781, 'x45': 0.0001483868987481541, 'x46': 0.00022396156565668887, 'x47': 0.00019808167686673298, 'x48': 0.0002094902020867095}\n",
      " {'x01': 5, 'x02': 0.0006045602014179762, 'x03': 0.00021820620289151308, 'x04': 0.00017044393293596779, 'x05': 0.0005982629417929222, 'x06': 5.881300796244287e-06, 'x07': 0.0004173740428029993, 'x08': 0.00016051872655814222, 'x09': 0.0002132571850802912, 'x10': 0.0004762329828743746, 'x11': 5.636172511396791e-07, 'x12': 0.0005142453567768864, 'x13': 3.403206933456143e-05, 'x14': 4.965721465598639e-07, 'x15': 0.00046008197355341024, 'x16': 6.229803211532923e-05, 'x17': 0.0003148915336430855, 'x18': 1.2062205157658205e-06, 'x19': 5.720589497136353e-06, 'x20': 0.00037520379080698257, 'x21': 0.00017061129349508155, 'x22': 0.0003595453730755853, 'x23': 0.0001593628995273196, 'x24': 0.0001406760678955947, 'x25': 0.00023515272086059046, 'x26': 5.432596751648571e-05, 'x27': 0.000266982720373258, 'x28': 0.00029307859542253664, 'x29': 0.00022136677161799424, 'x30': 0.0002593618173467408, 'x31': 0.0003250741770255484, 'x32': 0.0004204990383305327, 'x33': 4.7711236389612696e-05, 'x34': 7.320837472087367e-05, 'x35': 5.037928564169418e-05, 'x36': 2.1196602208992314e-05, 'x37': 0.00040422368963516744, 'x38': 0.000410454885717036, 'x39': 0.0002274164461270493, 'x40': 3.0361765202100586e-05, 'x41': 1.7010374905762545e-06, 'x42': 2.2137010580043507e-06, 'x43': 0.00046794329973530484, 'x44': 0.00024759984702030354, 'x45': 0.0002020811782469221, 'x46': 0.0003180167775878184, 'x47': 0.0005589504727115843, 'x48': 0.0001301866053872087}]\n"
     ]
    }
   ],
   "source": [
    "X2 = res2.X\n",
    "F2 = res2.F\n",
    "G2 = res2.G\n",
    "Z_res2 = [[d['x01']] for d in X2]\n",
    "\n",
    "\n",
    "names = []\n",
    "types = []\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "legend_dict = {}\n",
    "\n",
    "for xData in Z_res2:\n",
    "    matname = dataIdentifier['name'][int(xData[0])]\n",
    "    mattype = dataIdentifier['className'][int(xData[0])]\n",
    "    names.append(matname)\n",
    "    types.append(mattype)\n",
    "    \n",
    "unique_labels = list(set(types))\n",
    "\n",
    "# Define specific colors for each material type\n",
    "mat_colors = {\n",
    "    'Steel': 'slategrey',\n",
    "    'Aluminium Alloys': 'violet',\n",
    "    'Plastics': 'lawngreen',\n",
    "    'Titanium Alloys': 'indigo',\n",
    "    'Copper Alloys': 'chocolate',\n",
    "    'Composites': 'gold',\n",
    "    # Add more material types and corresponding colors as needed\n",
    "}\n",
    "\n",
    "\n",
    "for i, mattype in enumerate(types):\n",
    "    if mattype not in mat_colors:\n",
    "        mat_colors[mattype] = plt.cm.get_cmap('jet')(i / len(set(types)))\n",
    "        \n",
    "\n",
    "\n",
    "# add scatter plot for each unique label\n",
    "for i, (x, y) in enumerate(F2):\n",
    "    #if i == 3:  # Exclude the third value (index 2)\n",
    "        #continue\n",
    "    material = names[i]\n",
    "    mattype = types[i]\n",
    "    color = mat_colors[mattype]\n",
    "    label = mattype\n",
    "    ax.scatter(x, y, color=color, label=label)\n",
    "    ax.text(x + 0.1, y + 0.1, material)\n",
    "    if mattype not in legend_dict:\n",
    "        legend_dict[mattype] = ax.scatter(x, y, color=color, label=label)\n",
    "\n",
    "\n",
    "# set legend colors and remove duplicates\n",
    "handles, labels = [], []\n",
    "for label in legend_dict:\n",
    "    handles.append(legend_dict[label])\n",
    "    labels.append(label)\n",
    "    legend_dict[label].set_color(mat_colors[label])\n",
    "    \n",
    "ax.legend(handles, labels, loc=\"upper right\")\n",
    "\n",
    "\n",
    "# show plot\n",
    "plt.title(\"Objective Space\")\n",
    "entry_order = ['cost', 'mass', 'co2', 'water', 'energy', 'compliance']\n",
    "enabled_entries = [entry for entry in entry_order if objectives[entry]['isOn']]\n",
    "ax.set_xlabel(enabled_entries[0])\n",
    "ax.set_ylabel(enabled_entries[1])\n",
    "plt.savefig('./figures_Integer/Integer_cost_co2.png',bbox_inches='tight', dpi = 200)\n",
    "plt.show()\n",
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "580824a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "objectives3 = {'cost': {'isOn':False},\\\n",
    "              'mass': {'isOn':True}, \\\n",
    "              'co2': {'isOn':False},\\\n",
    "              'water': {'isOn':False},\\\n",
    "              'energy': {'isOn':False},\\\n",
    "              'compliance': {'isOn': True}}\n",
    "               \n",
    "# count the number of entries with 'isOn' set to True\n",
    "no = sum(1 for v in objectives.values() if v['isOn'])\n",
    "nc = sum(1 for v in constraints.values() if v['isOn'])\n",
    "\n",
    "# print an error message in red if there are 3 or more entries with 'isOn' set to True\n",
    "if no >= 3:\n",
    "    print('Error: Three or more entries have isOn=True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "26b2dd9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "class MixedVarsZDT1(ElementwiseProblem):\n",
    "\n",
    "    def __init__(self, truss, trainInfo , constraints, objectives3, nc, no, nmat, **kwargs):\n",
    "\n",
    "        variables = dict()\n",
    "\n",
    "        variables[f\"x01\"] = Integer(bounds=(0, nmat-1))\n",
    "\n",
    "        for k in range(2, 49):\n",
    "            variables[f\"x{k:02}\"] = Real(bounds=(2e-8, 2e-3))\n",
    "\n",
    "        super().__init__(vars=variables, n_obj=no, n_ieq_constr=nc, **kwargs)\n",
    "        \n",
    "        self.truss=truss\n",
    "        self.trainInfo=trainInfo\n",
    "        self.constraints=constraints\n",
    "        self.objectives=objectives3\n",
    "        \n",
    "    def _evaluate(self, x, out, *args, **kwargs):\n",
    "        x = np.array([x[f\"x{k:02}\"] for k in range(1, 49)])\n",
    "        \n",
    "        matprop=trainInfo[int(x[0]),:]  \n",
    "        \n",
    "        x_tensor = torch.from_numpy(x[1:])\n",
    "        area = x_tensor * torch.ones((connectivity.shape[0]))   \n",
    "        u, _, _, _, internalForce = truss.solveFE(E = torch.tensor([matprop[0]]).float(), A=area)\n",
    "        compliance = truss.computeCompliance(u)\n",
    "        volume = truss.getVolume(area)\n",
    "        mass = matprop[2]*volume\n",
    "        cost = mass*matprop[1]\n",
    "        co2 = mass*matprop[4]\n",
    "        energy = mass*matprop[5]        \n",
    "        water = mass*matprop[6] \n",
    "        \n",
    "        \n",
    "        \n",
    "        con_values = []\n",
    "        \n",
    "        if(constraints['massCons']['isOn']):\n",
    "            constraints['massCons']['value'] = (mass/constraints['massCons']['maxMass']) - 1.\n",
    "            con_values.append(constraints['massCons']['value'])\n",
    "\n",
    "        if(constraints['costCons']['isOn']):\n",
    "            constraints['costCons']['value'] = (cost/constraints['costCons']['maxCost']) - 1.\n",
    "            con_values.append(constraints['costCons']['value'])\n",
    "\n",
    "        if(constraints['tensionCons']['isOn']):\n",
    "            tensileForce = 0.001+torch.relu(internalForce)\n",
    "            tensileStress = tensileForce/area\n",
    "            maxTensileStressExperienced = torch.pow(torch.sum(tensileStress**6), 1./6)*constraints['tensionCons']['FOS']\n",
    "            constraints['tensionCons']['value'] = (maxTensileStressExperienced/matprop[3]) - 1.\n",
    "            con_values.append(constraints['tensionCons']['value'])\n",
    "\n",
    "        if(constraints['complianceCons']['isOn']):\n",
    "            constraints['complianceCons']['value'] = (compliance/constraints['complianceCons']['maxJ']) - 1.\n",
    "            con_values.append(constraints['complianceCons']['value'])\n",
    "\n",
    "        if(constraints['compressionCons']['isOn']):\n",
    "            compressiveForce = 0.001+torch.relu(-internalForce)\n",
    "            k = 4. # used in geom factor... see buckling theory\n",
    "            geomFactor = k*(self.truss.barLength/(np.pi*area))**2\n",
    "            compressiveStress = compressiveForce*geomFactor\n",
    "            maxCompressiveStressExperienced = torch.pow(torch.sum(compressiveStress**6), 1./6)*constraints['compressionCons']['FOS']\n",
    "            constraints['compressionCons']['value'] = (maxCompressiveStressExperienced/matprop[0]) - 1.\n",
    "            con_values.append(constraints['compressionCons']['value'])\n",
    "\n",
    "        if(constraints['co2Cons']['isOn']):\n",
    "            constraints['co2Cons']['value'] = (co2/constraints['co2Cons']['maxco2']) - 1.\n",
    "            con_values.append(constraints['co2Cons']['value'])\n",
    "\n",
    "        if(constraints['energyCons']['isOn']):\n",
    "            constraints['energyCons']['value'] = (energy/constraints['energyCons']['maxenergy']) - 1.\n",
    "            con_values.append(constraints['energyCons']['value'])\n",
    "\n",
    "        if(constraints['waterCons']['isOn']):\n",
    "            constraints['waterCons']['value'] = (water/constraints['waterCons']['maxwater']) - 1.\n",
    "            con_values.append(constraints['waterCons']['value'])\n",
    "            \n",
    "        \n",
    "        \n",
    "        obj_values = []\n",
    "        \n",
    "        if(objectives3['cost']['isOn']):\n",
    "            obj_values.append(cost)\n",
    "            \n",
    "        if(objectives3['mass']['isOn']):\n",
    "            obj_values.append(mass)\n",
    "            \n",
    "        if(objectives3['co2']['isOn']):\n",
    "            obj_values.append(co2)\n",
    "            \n",
    "        if(objectives3['water']['isOn']):\n",
    "            obj_values.append(water)\n",
    "            \n",
    "        if(objectives3['energy']['isOn']):\n",
    "            obj_values.append(energy)\n",
    "            \n",
    "        if(objectives3['compliance']['isOn']):\n",
    "            obj_values.append(compliance)\n",
    "            \n",
    "  \n",
    "\n",
    "        out[\"F\"] = np.array(obj_values)\n",
    "        out[\"G\"] = np.array(con_values)\n",
    "        \n",
    "  \n",
    "problem3 = MixedVarsZDT1(truss,trainInfo , constraints, objectives3, nc, no, nmat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "816fa962",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================================================\n",
      "n_gen  |  n_eval  | n_nds  |     cv_min    |     cv_avg    |      eps      |   indicator  \n",
      "==========================================================================================\n",
      "     1 |      100 |      1 |  0.2129996812 |  3.700016E+04 |             - |             -\n",
      "     2 |      200 |      2 |  0.000000E+00 |  8.8249697052 |             - |             -\n",
      "     3 |      300 |      5 |  0.000000E+00 |  2.4676914670 |  0.0586419053 |         ideal\n",
      "     4 |      400 |      5 |  0.000000E+00 |  0.7176305668 |  0.1735478681 |         ideal\n",
      "     5 |      500 |      7 |  0.000000E+00 |  0.1746583994 |  0.0062080345 |         ideal\n",
      "     6 |      600 |      8 |  0.000000E+00 |  0.0019769861 |  0.0612915416 |             f\n",
      "     7 |      700 |     10 |  0.000000E+00 |  0.000000E+00 |  0.0567514500 |             f\n",
      "     8 |      800 |     13 |  0.000000E+00 |  0.000000E+00 |  0.0336353646 |             f\n",
      "     9 |      900 |     15 |  0.000000E+00 |  0.000000E+00 |  0.0240507905 |             f\n",
      "    10 |     1000 |     19 |  0.000000E+00 |  0.000000E+00 |  0.0100576091 |         ideal\n",
      "    11 |     1100 |     25 |  0.000000E+00 |  0.000000E+00 |  0.0070896105 |         ideal\n",
      "    12 |     1200 |     33 |  0.000000E+00 |  0.000000E+00 |  0.0110435452 |         ideal\n",
      "    13 |     1300 |     32 |  0.000000E+00 |  0.000000E+00 |  0.0051425985 |         ideal\n",
      "    14 |     1400 |     44 |  0.000000E+00 |  0.000000E+00 |  0.0168870511 |         ideal\n",
      "    15 |     1500 |     52 |  0.000000E+00 |  0.000000E+00 |  0.0087337280 |         ideal\n",
      "    16 |     1600 |     43 |  0.000000E+00 |  0.000000E+00 |  0.0027333715 |         ideal\n",
      "    17 |     1700 |     53 |  0.000000E+00 |  0.000000E+00 |  0.0089721116 |         ideal\n",
      "    18 |     1800 |     56 |  0.000000E+00 |  0.000000E+00 |  0.0033479652 |             f\n",
      "    19 |     1900 |     54 |  0.000000E+00 |  0.000000E+00 |  0.0042257279 |         ideal\n",
      "    20 |     2000 |     56 |  0.000000E+00 |  0.000000E+00 |  0.0040884266 |         ideal\n",
      "    21 |     2100 |     55 |  0.000000E+00 |  0.000000E+00 |  0.0051678223 |             f\n",
      "    22 |     2200 |     48 |  0.000000E+00 |  0.000000E+00 |  0.0032473491 |         ideal\n",
      "    23 |     2300 |     55 |  0.000000E+00 |  0.000000E+00 |  0.0033653763 |             f\n",
      "    24 |     2400 |     63 |  0.000000E+00 |  0.000000E+00 |  0.0021855988 |             f\n",
      "    25 |     2500 |     63 |  0.000000E+00 |  0.000000E+00 |  0.0049803371 |             f\n",
      "    26 |     2600 |     68 |  0.000000E+00 |  0.000000E+00 |  0.0064183673 |         ideal\n",
      "    27 |     2700 |     70 |  0.000000E+00 |  0.000000E+00 |  0.0155511149 |         nadir\n",
      "    28 |     2800 |     67 |  0.000000E+00 |  0.000000E+00 |  0.0019661312 |             f\n",
      "    29 |     2900 |     73 |  0.000000E+00 |  0.000000E+00 |  0.0411829884 |         nadir\n",
      "    30 |     3000 |     71 |  0.000000E+00 |  0.000000E+00 |  0.0049489624 |             f\n",
      "    31 |     3100 |     76 |  0.000000E+00 |  0.000000E+00 |  0.0040648364 |             f\n",
      "    32 |     3200 |     83 |  0.000000E+00 |  0.000000E+00 |  0.0533251441 |         nadir\n",
      "    33 |     3300 |     81 |  0.000000E+00 |  0.000000E+00 |  0.0037032935 |         ideal\n",
      "    34 |     3400 |     84 |  0.000000E+00 |  0.000000E+00 |  0.0109687744 |         nadir\n",
      "    35 |     3500 |     87 |  0.000000E+00 |  0.000000E+00 |  0.0031234553 |         ideal\n",
      "    36 |     3600 |     82 |  0.000000E+00 |  0.000000E+00 |  0.0024932929 |             f\n",
      "    37 |     3700 |     87 |  0.000000E+00 |  0.000000E+00 |  0.0033443203 |             f\n",
      "    38 |     3800 |     82 |  0.000000E+00 |  0.000000E+00 |  0.0416612320 |         nadir\n",
      "    39 |     3900 |     88 |  0.000000E+00 |  0.000000E+00 |  0.0034664255 |             f\n",
      "    40 |     4000 |     84 |  0.000000E+00 |  0.000000E+00 |  0.0069978705 |         nadir\n",
      "    41 |     4100 |     91 |  0.000000E+00 |  0.000000E+00 |  0.0010364783 |             f\n",
      "    42 |     4200 |     81 |  0.000000E+00 |  0.000000E+00 |  0.0021704114 |             f\n",
      "    43 |     4300 |     88 |  0.000000E+00 |  0.000000E+00 |  0.0030317301 |             f\n",
      "    44 |     4400 |     94 |  0.000000E+00 |  0.000000E+00 |  0.0016171572 |             f\n",
      "    45 |     4500 |     96 |  0.000000E+00 |  0.000000E+00 |  0.0034130445 |             f\n",
      "    46 |     4600 |     95 |  0.000000E+00 |  0.000000E+00 |  0.0014780517 |             f\n",
      "    47 |     4700 |     95 |  0.000000E+00 |  0.000000E+00 |  0.0128026674 |         nadir\n",
      "    48 |     4800 |     96 |  0.000000E+00 |  0.000000E+00 |  0.0008045917 |             f\n",
      "    49 |     4900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021140379 |             f\n",
      "    50 |     5000 |     94 |  0.000000E+00 |  0.000000E+00 |  0.0029789917 |             f\n",
      "    51 |     5100 |     95 |  0.000000E+00 |  0.000000E+00 |  0.0163441596 |         nadir\n",
      "    52 |     5200 |     91 |  0.000000E+00 |  0.000000E+00 |  0.0010507735 |             f\n",
      "    53 |     5300 |     94 |  0.000000E+00 |  0.000000E+00 |  0.0019051845 |             f\n",
      "    54 |     5400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024747635 |             f\n",
      "    55 |     5500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0034028895 |             f\n",
      "    56 |     5600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012384360 |             f\n",
      "    57 |     5700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021037392 |             f\n",
      "    58 |     5800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0028809954 |             f\n",
      "    59 |     5900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012099946 |             f\n",
      "    60 |     6000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022258861 |             f\n",
      "    61 |     6100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0033569502 |             f\n",
      "    62 |     6200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006651010 |             f\n",
      "    63 |     6300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020783953 |             f\n",
      "    64 |     6400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0350137183 |         nadir\n",
      "    65 |     6500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007268298 |             f\n",
      "    66 |     6600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014621655 |             f\n",
      "    67 |     6700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022814832 |             f\n",
      "    68 |     6800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0112655830 |         nadir\n",
      "    69 |     6900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.1654262846 |         nadir\n",
      "    70 |     7000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009358443 |             f\n",
      "    71 |     7100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011699939 |             f\n",
      "    72 |     7200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0029039566 |             f\n",
      "    73 |     7300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006528201 |             f\n",
      "    74 |     7400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010433076 |             f\n",
      "    75 |     7500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0285181214 |         nadir\n",
      "    76 |     7600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006004010 |             f\n",
      "    77 |     7700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019117058 |             f\n",
      "    78 |     7800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026268362 |             f\n",
      "    79 |     7900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0231895673 |         nadir\n",
      "    80 |     8000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0206213123 |         nadir\n",
      "    81 |     8100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012965978 |             f\n",
      "    82 |     8200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025800671 |             f\n",
      "    83 |     8300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0259314094 |         nadir\n",
      "    84 |     8400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0077103899 |         nadir\n",
      "    85 |     8500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0061952884 |         nadir\n",
      "    86 |     8600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005619418 |             f\n",
      "    87 |     8700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015275051 |             f\n",
      "    88 |     8800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020438851 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    89 |     8900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027945310 |             f\n",
      "    90 |     9000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009774134 |             f\n",
      "    91 |     9100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018301015 |             f\n",
      "    92 |     9200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022033389 |             f\n",
      "    93 |     9300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0029001136 |             f\n",
      "    94 |     9400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006548432 |             f\n",
      "    95 |     9500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021123807 |             f\n",
      "    96 |     9600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0030005360 |             f\n",
      "    97 |     9700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005324065 |             f\n",
      "    98 |     9800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011587666 |             f\n",
      "    99 |     9900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018864022 |             f\n",
      "   100 |    10000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024035578 |             f\n",
      "   101 |    10100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0028937710 |             f\n",
      "   102 |    10200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006172340 |             f\n",
      "   103 |    10300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012747403 |             f\n",
      "   104 |    10400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017446590 |             f\n",
      "   105 |    10500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024861975 |             f\n",
      "   106 |    10600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0760073903 |         nadir\n",
      "   107 |    10700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009461849 |             f\n",
      "   108 |    10800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012615392 |             f\n",
      "   109 |    10900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021787301 |             f\n",
      "   110 |    11000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0042336719 |         nadir\n",
      "   111 |    11100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008484490 |             f\n",
      "   112 |    11200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014378598 |             f\n",
      "   113 |    11300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026186901 |             f\n",
      "   114 |    11400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006605801 |             f\n",
      "   115 |    11500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018530665 |             f\n",
      "   116 |    11600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027078997 |             f\n",
      "   117 |    11700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004924278 |             f\n",
      "   118 |    11800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014634958 |             f\n",
      "   119 |    11900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021501664 |             f\n",
      "   120 |    12000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025285241 |             f\n",
      "   121 |    12100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0298176262 |         nadir\n",
      "   122 |    12200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.1726401882 |         nadir\n",
      "   123 |    12300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008661254 |             f\n",
      "   124 |    12400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013644352 |             f\n",
      "   125 |    12500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017432792 |             f\n",
      "   126 |    12600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0764887332 |         nadir\n",
      "   127 |    12700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0041783670 |         nadir\n",
      "   128 |    12800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003263651 |             f\n",
      "   129 |    12900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010113123 |             f\n",
      "   130 |    13000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013785021 |             f\n",
      "   131 |    13100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022740705 |             f\n",
      "   132 |    13200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026028226 |             f\n",
      "   133 |    13300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006407197 |             f\n",
      "   134 |    13400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019869032 |             f\n",
      "   135 |    13500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025556336 |             f\n",
      "   136 |    13600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0041574928 |         nadir\n",
      "   137 |    13700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007389355 |             f\n",
      "   138 |    13800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0131123808 |         nadir\n",
      "   139 |    13900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006333414 |             f\n",
      "   140 |    14000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011128083 |             f\n",
      "   141 |    14100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017834135 |             f\n",
      "   142 |    14200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023540474 |             f\n",
      "   143 |    14300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027074078 |             f\n",
      "   144 |    14400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0389590686 |         nadir\n",
      "   145 |    14500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007286779 |             f\n",
      "   146 |    14600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012008165 |             f\n",
      "   147 |    14700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014831717 |             f\n",
      "   148 |    14800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019361546 |             f\n",
      "   149 |    14900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022259106 |             f\n",
      "   150 |    15000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027865808 |             f\n",
      "   151 |    15100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0029928006 |         nadir\n",
      "   152 |    15200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003279725 |             f\n",
      "   153 |    15300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009349197 |             f\n",
      "   154 |    15400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016011959 |             f\n",
      "   155 |    15500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023251043 |             f\n",
      "   156 |    15600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025565066 |             f\n",
      "   157 |    15700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004007724 |             f\n",
      "   158 |    15800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011681413 |             f\n",
      "   159 |    15900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021170491 |             f\n",
      "   160 |    16000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026252191 |             f\n",
      "   161 |    16100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007348513 |             f\n",
      "   162 |    16200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009501067 |             f\n",
      "   163 |    16300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012604087 |             f\n",
      "   164 |    16400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017483182 |             f\n",
      "   165 |    16500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023812770 |             f\n",
      "   166 |    16600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027157702 |             f\n",
      "   167 |    16700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010690489 |             f\n",
      "   168 |    16800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017177655 |             f\n",
      "   169 |    16900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021711549 |             f\n",
      "   170 |    17000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022754099 |             f\n",
      "   171 |    17100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0036449458 |         ideal\n",
      "   172 |    17200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004519377 |             f\n",
      "   173 |    17300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006629522 |             f\n",
      "   174 |    17400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009395141 |             f\n",
      "   175 |    17500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015045236 |             f\n",
      "   176 |    17600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019620403 |             f\n",
      "   177 |    17700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023325323 |             f\n",
      "   178 |    17800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026455480 |             f\n",
      "   179 |    17900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007857329 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   180 |    18000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012277670 |             f\n",
      "   181 |    18100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018764771 |             f\n",
      "   182 |    18200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025505099 |             f\n",
      "   183 |    18300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004332263 |             f\n",
      "   184 |    18400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011939111 |             f\n",
      "   185 |    18500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021363802 |             f\n",
      "   186 |    18600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022964568 |             f\n",
      "   187 |    18700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024591871 |             f\n",
      "   188 |    18800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0066193605 |         nadir\n",
      "   189 |    18900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005307034 |             f\n",
      "   190 |    19000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012356697 |             f\n",
      "   191 |    19100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017125487 |             f\n",
      "   192 |    19200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023289956 |             f\n",
      "   193 |    19300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024448100 |             f\n",
      "   194 |    19400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027899628 |             f\n",
      "   195 |    19500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005223663 |             f\n",
      "   196 |    19600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007789707 |             f\n",
      "   197 |    19700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009761511 |             f\n",
      "   198 |    19800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013108718 |             f\n",
      "   199 |    19900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022883177 |             f\n",
      "   200 |    20000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025607850 |             f\n",
      "   201 |    20100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005175467 |             f\n",
      "   202 |    20200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010473711 |             f\n",
      "   203 |    20300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013663030 |             f\n",
      "   204 |    20400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016421257 |             f\n",
      "   205 |    20500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0059643679 |         nadir\n",
      "   206 |    20600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003523821 |             f\n",
      "   207 |    20700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011765714 |             f\n",
      "   208 |    20800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016315579 |             f\n",
      "   209 |    20900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0072204953 |         nadir\n",
      "   210 |    21000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003073764 |             f\n",
      "   211 |    21100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006715912 |             f\n",
      "   212 |    21200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015321070 |             f\n",
      "   213 |    21300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017141667 |             f\n",
      "   214 |    21400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024750266 |             f\n",
      "   215 |    21500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0237655229 |         nadir\n",
      "   216 |    21600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006660499 |             f\n",
      "   217 |    21700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010886940 |             f\n",
      "   218 |    21800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014273170 |             f\n",
      "   219 |    21900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021932713 |             f\n",
      "   220 |    22000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0065941391 |         nadir\n",
      "   221 |    22100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003480473 |             f\n",
      "   222 |    22200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009431956 |             f\n",
      "   223 |    22300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011685608 |             f\n",
      "   224 |    22400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014156968 |             f\n",
      "   225 |    22500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015437004 |             f\n",
      "   226 |    22600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018073407 |             f\n",
      "   227 |    22700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026374554 |             f\n",
      "   228 |    22800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004468483 |             f\n",
      "   229 |    22900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010104392 |             f\n",
      "   230 |    23000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012104077 |             f\n",
      "   231 |    23100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019469463 |             f\n",
      "   232 |    23200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027806721 |         nadir\n",
      "   233 |    23300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008323031 |             f\n",
      "   234 |    23400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012858601 |             f\n",
      "   235 |    23500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016031103 |             f\n",
      "   236 |    23600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0169977019 |         nadir\n",
      "   237 |    23700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004177701 |             f\n",
      "   238 |    23800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007175377 |             f\n",
      "   239 |    23900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008444598 |             f\n",
      "   240 |    24000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013191994 |             f\n",
      "   241 |    24100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018255648 |             f\n",
      "   242 |    24200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022499423 |             f\n",
      "   243 |    24300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022060424 |             f\n",
      "   244 |    24400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025852366 |             f\n",
      "   245 |    24500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003682426 |             f\n",
      "   246 |    24600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010752539 |             f\n",
      "   247 |    24700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015505506 |             f\n",
      "   248 |    24800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017657447 |             f\n",
      "   249 |    24900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020274456 |             f\n",
      "   250 |    25000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024623398 |             f\n",
      "   251 |    25100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0028177191 |             f\n",
      "   252 |    25200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004567818 |             f\n",
      "   253 |    25300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011659355 |             f\n",
      "   254 |    25400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013013734 |             f\n",
      "   255 |    25500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016366892 |             f\n",
      "   256 |    25600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020197904 |             f\n",
      "   257 |    25700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021143219 |             f\n",
      "   258 |    25800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025955036 |             f\n",
      "   259 |    25900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004984108 |             f\n",
      "   260 |    26000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015108796 |             f\n",
      "   261 |    26100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017415480 |             f\n",
      "   262 |    26200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021252402 |             f\n",
      "   263 |    26300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026195132 |             f\n",
      "   264 |    26400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005239001 |             f\n",
      "   265 |    26500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0156664197 |         nadir\n",
      "   266 |    26600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010023442 |             f\n",
      "   267 |    26700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012791581 |             f\n",
      "   268 |    26800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0029956961 |         nadir\n",
      "   269 |    26900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003732806 |             f\n",
      "   270 |    27000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008811671 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   271 |    27100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012902865 |             f\n",
      "   272 |    27200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014905362 |             f\n",
      "   273 |    27300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0048399459 |         nadir\n",
      "   274 |    27400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007052678 |             f\n",
      "   275 |    27500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008194111 |             f\n",
      "   276 |    27600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0135231318 |         nadir\n",
      "   277 |    27700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002811004 |             f\n",
      "   278 |    27800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009128217 |             f\n",
      "   279 |    27900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016005467 |             f\n",
      "   280 |    28000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019117145 |             f\n",
      "   281 |    28100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023039264 |             f\n",
      "   282 |    28200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025042904 |             f\n",
      "   283 |    28300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002943910 |             f\n",
      "   284 |    28400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008599209 |             f\n",
      "   285 |    28500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014401368 |             f\n",
      "   286 |    28600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017776449 |             f\n",
      "   287 |    28700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0184470780 |         nadir\n",
      "   288 |    28800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008541488 |             f\n",
      "   289 |    28900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012377110 |             f\n",
      "   290 |    29000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018929781 |             f\n",
      "   291 |    29100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020272190 |             f\n",
      "   292 |    29200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024869403 |             f\n",
      "   293 |    29300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026670049 |             f\n",
      "   294 |    29400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002498386 |             f\n",
      "   295 |    29500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014760279 |             f\n",
      "   296 |    29600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017802452 |             f\n",
      "   297 |    29700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022809850 |             f\n",
      "   298 |    29800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024318351 |             f\n",
      "   299 |    29900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027503267 |             f\n",
      "   300 |    30000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003536992 |             f\n",
      "   301 |    30100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011282340 |             f\n",
      "   302 |    30200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016637146 |             f\n",
      "   303 |    30300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0035061841 |         nadir\n",
      "   304 |    30400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006846094 |             f\n",
      "   305 |    30500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011092392 |             f\n",
      "   306 |    30600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014022831 |             f\n",
      "   307 |    30700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019549465 |             f\n",
      "   308 |    30800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020342292 |             f\n",
      "   309 |    30900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0380911602 |         nadir\n",
      "   310 |    31000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003284718 |             f\n",
      "   311 |    31100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011003518 |             f\n",
      "   312 |    31200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016340605 |             f\n",
      "   313 |    31300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022150093 |             f\n",
      "   314 |    31400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025562810 |             f\n",
      "   315 |    31500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003907178 |             f\n",
      "   316 |    31600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009164182 |             f\n",
      "   317 |    31700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015073220 |             f\n",
      "   318 |    31800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017531771 |             f\n",
      "   319 |    31900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020969471 |             f\n",
      "   320 |    32000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0065785394 |         nadir\n",
      "   321 |    32100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0000885830 |             f\n",
      "   322 |    32200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005442984 |             f\n",
      "   323 |    32300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012777509 |             f\n",
      "   324 |    32400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0046198381 |         nadir\n",
      "   325 |    32500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007177656 |             f\n",
      "   326 |    32600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008906830 |             f\n",
      "   327 |    32700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010225371 |             f\n",
      "   328 |    32800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013656429 |             f\n",
      "   329 |    32900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019041488 |             f\n",
      "   330 |    33000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020787046 |             f\n",
      "   331 |    33100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024646668 |             f\n",
      "   332 |    33200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025807140 |             f\n",
      "   333 |    33300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003721849 |             f\n",
      "   334 |    33400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008794065 |             f\n",
      "   335 |    33500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016676501 |             f\n",
      "   336 |    33600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018943309 |             f\n",
      "   337 |    33700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025044139 |             f\n",
      "   338 |    33800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0056273745 |         nadir\n",
      "   339 |    33900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006538067 |             f\n",
      "   340 |    34000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007100961 |             f\n",
      "   341 |    34100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0077186261 |         nadir\n",
      "   342 |    34200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005135679 |             f\n",
      "   343 |    34300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010907702 |             f\n",
      "   344 |    34400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014677717 |             f\n",
      "   345 |    34500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020300296 |             f\n",
      "   346 |    34600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022281219 |             f\n",
      "   347 |    34700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024311268 |             f\n",
      "   348 |    34800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026498066 |             f\n",
      "   349 |    34900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004808249 |             f\n",
      "   350 |    35000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008477854 |             f\n",
      "   351 |    35100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013271869 |             f\n",
      "   352 |    35200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019791317 |             f\n",
      "   353 |    35300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0066122280 |         nadir\n",
      "   354 |    35400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005229664 |             f\n",
      "   355 |    35500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007893386 |             f\n",
      "   356 |    35600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0029547024 |         nadir\n",
      "   357 |    35700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002207041 |             f\n",
      "   358 |    35800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008556502 |             f\n",
      "   359 |    35900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0096220378 |         nadir\n",
      "   360 |    36000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002686269 |             f\n",
      "   361 |    36100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008580498 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   362 |    36200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012978266 |             f\n",
      "   363 |    36300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016906501 |             f\n",
      "   364 |    36400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019253538 |             f\n",
      "   365 |    36500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021219538 |             f\n",
      "   366 |    36600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023198951 |             f\n",
      "   367 |    36700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027066605 |             f\n",
      "   368 |    36800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007073505 |             f\n",
      "   369 |    36900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010262326 |             f\n",
      "   370 |    37000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016540523 |             f\n",
      "   371 |    37100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020698131 |             f\n",
      "   372 |    37200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022839685 |             f\n",
      "   373 |    37300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027381363 |             f\n",
      "   374 |    37400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007895890 |             f\n",
      "   375 |    37500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008529458 |             f\n",
      "   376 |    37600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0167879280 |         nadir\n",
      "   377 |    37700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003260239 |             f\n",
      "   378 |    37800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008500625 |             f\n",
      "   379 |    37900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011667720 |             f\n",
      "   380 |    38000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012804476 |             f\n",
      "   381 |    38100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015429680 |             f\n",
      "   382 |    38200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0054993579 |         nadir\n",
      "   383 |    38300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007201666 |             f\n",
      "   384 |    38400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0090244724 |         nadir\n",
      "   385 |    38500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006667778 |             f\n",
      "   386 |    38600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015084966 |             f\n",
      "   387 |    38700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0031660017 |         nadir\n",
      "   388 |    38800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002262125 |             f\n",
      "   389 |    38900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008400498 |             f\n",
      "   390 |    39000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012131359 |             f\n",
      "   391 |    39100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0044641031 |         nadir\n",
      "   392 |    39200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003913602 |             f\n",
      "   393 |    39300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006456090 |             f\n",
      "   394 |    39400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013121700 |             f\n",
      "   395 |    39500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017479520 |             f\n",
      "   396 |    39600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019029110 |             f\n",
      "   397 |    39700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024480837 |             f\n",
      "   398 |    39800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027060514 |             f\n",
      "   399 |    39900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003881348 |             f\n",
      "   400 |    40000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009100232 |             f\n",
      "   401 |    40100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013438897 |             f\n",
      "   402 |    40200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017915339 |             f\n",
      "   403 |    40300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0020565214 |             f\n",
      "   404 |    40400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024045631 |             f\n",
      "   405 |    40500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024413507 |             f\n",
      "   406 |    40600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0024845671 |             f\n",
      "   407 |    40700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025636101 |             f\n",
      "   408 |    40800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003947522 |             f\n",
      "   409 |    40900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007697564 |             f\n",
      "   410 |    41000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010517934 |             f\n",
      "   411 |    41100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011873228 |             f\n",
      "   412 |    41200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016890472 |             f\n",
      "   413 |    41300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017524227 |             f\n",
      "   414 |    41400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019781063 |             f\n",
      "   415 |    41500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019481392 |             f\n",
      "   416 |    41600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022551341 |             f\n",
      "   417 |    41700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022028936 |             f\n",
      "   418 |    41800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025226327 |             f\n",
      "   419 |    41900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003336694 |             f\n",
      "   420 |    42000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008622168 |             f\n",
      "   421 |    42100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0055944940 |         nadir\n",
      "   422 |    42200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026182018 |         nadir\n",
      "   423 |    42300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005301990 |             f\n",
      "   424 |    42400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009449304 |             f\n",
      "   425 |    42500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013973086 |             f\n",
      "   426 |    42600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015697586 |             f\n",
      "   427 |    42700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018417108 |             f\n",
      "   428 |    42800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019579723 |             f\n",
      "   429 |    42900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023424130 |             f\n",
      "   430 |    43000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0026346467 |             f\n",
      "   431 |    43100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005094735 |             f\n",
      "   432 |    43200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007827005 |             f\n",
      "   433 |    43300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012475345 |             f\n",
      "   434 |    43400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0016985880 |             f\n",
      "   435 |    43500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018443499 |             f\n",
      "   436 |    43600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0023877838 |             f\n",
      "   437 |    43700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0027580084 |             f\n",
      "   438 |    43800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004882613 |             f\n",
      "   439 |    43900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010070937 |             f\n",
      "   440 |    44000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015122362 |             f\n",
      "   441 |    44100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017785235 |             f\n",
      "   442 |    44200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018492735 |             f\n",
      "   443 |    44300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021013983 |             f\n",
      "   444 |    44400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021695201 |             f\n",
      "   445 |    44500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025114644 |             f\n",
      "   446 |    44600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005658160 |             f\n",
      "   447 |    44700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007201578 |             f\n",
      "   448 |    44800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012345061 |             f\n",
      "   449 |    44900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012637131 |             f\n",
      "   450 |    45000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015713178 |             f\n",
      "   451 |    45100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0689755497 |         nadir\n",
      "   452 |    45200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005046057 |             f\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   453 |    45300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008576901 |             f\n",
      "   454 |    45400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012806716 |             f\n",
      "   455 |    45500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015075666 |             f\n",
      "   456 |    45600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0538185416 |         nadir\n",
      "   457 |    45700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0494096831 |         nadir\n",
      "   458 |    45800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0002929701 |             f\n",
      "   459 |    45900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0005876879 |             f\n",
      "   460 |    46000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008663587 |             f\n",
      "   461 |    46100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010449233 |             f\n",
      "   462 |    46200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013155586 |             f\n",
      "   463 |    46300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0474435677 |         nadir\n",
      "   464 |    46400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004856661 |             f\n",
      "   465 |    46500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008264830 |             f\n",
      "   466 |    46600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011384982 |             f\n",
      "   467 |    46700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014885092 |             f\n",
      "   468 |    46800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0019620751 |             f\n",
      "   469 |    46900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022598213 |             f\n",
      "   470 |    47000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0028356102 |             f\n",
      "   471 |    47100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004831429 |             f\n",
      "   472 |    47200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008041350 |             f\n",
      "   473 |    47300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0012565046 |             f\n",
      "   474 |    47400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015939662 |             f\n",
      "   475 |    47500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018817882 |             f\n",
      "   476 |    47600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021202073 |             f\n",
      "   477 |    47700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022987202 |             f\n",
      "   478 |    47800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0025026687 |             f\n",
      "   479 |    47900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004181771 |             f\n",
      "   480 |    48000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0007429475 |             f\n",
      "   481 |    48100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0009768796 |             f\n",
      "   482 |    48200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0015392168 |             f\n",
      "   483 |    48300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0018581467 |             f\n",
      "   484 |    48400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0021177257 |             f\n",
      "   485 |    48500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0209577550 |         nadir\n",
      "   486 |    48600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0004586070 |             f\n",
      "   487 |    48700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0008107689 |             f\n",
      "   488 |    48800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0011555378 |             f\n",
      "   489 |    48900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013517213 |             f\n",
      "   490 |    49000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017711998 |             f\n",
      "   491 |    49100 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0770171037 |         nadir\n",
      "   492 |    49200 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0006679751 |             f\n",
      "   493 |    49300 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0010511434 |             f\n",
      "   494 |    49400 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0013710772 |             f\n",
      "   495 |    49500 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0014681496 |             f\n",
      "   496 |    49600 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0017724084 |             f\n",
      "   497 |    49700 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022230795 |             f\n",
      "   498 |    49800 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0022852829 |             f\n",
      "   499 |    49900 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0068916964 |         nadir\n",
      "   500 |    50000 |    100 |  0.000000E+00 |  0.000000E+00 |  0.0003765989 |             f\n",
      "Solver time : 175.54\n"
     ]
    }
   ],
   "source": [
    "start = time.perf_counter()\n",
    "res3 = minimize(problem3,\n",
    "               algorithm,\n",
    "               termination,\n",
    "               seed=1,\n",
    "               save_history=True,\n",
    "               verbose=True)\n",
    "print('Solver time : {:.2F}'.format(time.perf_counter() - start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "50a09536",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solution not limited by the areas\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CQgI0Gg0mTJiAjRs3om3btnZdu0mTJujQoUOt61hSUoLBgwcjPj4eBw8ehEpl/FG7fft2PPzww7hx4waSk5NrdY+1a9fKFmTOnj2LkSNHYvfu3Rg8eDAA4NKlS7jnnnuQkJCATp06AYAUZB588EGX14ktM/YwlAE337Je5uZbxnJERPWEwWBAeuYlHDt5FumZl2RZs6Z///6IiYnB1q1bHb6GVqvFxo0ba12XefPmobS0FEuWLJGCDACMGTMGTz31VK2vL7d9+/YhICBACjIA0Lp1a8yYMQONGzeWpU4MM/a49R4AfQ2F9L+XIyKq+06cTseC5Wvx7vqt2LAtBe+u34oFy9fixOl0t9flzp07VmdmJScno3fv3tBqtejduzc++OAD6dyBAweqdE09/vjjCA0NxWOPPYYXX3wRCQkJ6NixI/bt21ftPcrLy7FmzRo8/PDDFge3Pvfcc0hKSpLK/vWvf5Xq1LdvX+zcuVMqu2XLFsTGxkKhUGDPnj24//77ERYWZtbSYTAY8MILL0Cr1SIyMhJLl5r3HJw/fx733XcfevXqhW7duuGZZ57B7du3q1x/9+7deOCBBxAdHY2//vWv1X/IMM5+y83NxU8//WR2/KWXXsKYMWMAAC+88AJSUlKQkpICrVaL0aNHW71mrYk6Lj8/XwAQ+fn5tb9YzjNCnEbNXznP1P5eREQuVlJSIk6dOiVKSkocev/Pp86LWcnLqv36+dR5J9f4DwDE2rVrpdefffaZUCgU4r///a8QQoiMjAwBQGRkZEhlIiMjxaVLl4QQQly9elW0bNlSHDp0SDpv6T2TJk0SwcHB4vTp00IIIZYvXy7atGlTbb1OnjwpAIgdO3bU+D0UFBSIiIgIodPphBBCnD17Vmg0GnH+/B+f28GDBwUAMW/ePCGEEOnp6WLixIlS3QIDA8V3330nhBDi9OnTws/PT+zatUsIIcTt27dF27ZtxWuvvSaEEKK0tFQkJCSI6dOnV7n+kiVLpM/F19dXHDhwoNp6X716VTRt2lT4+fmJyZMni3379omysrIq5SZNmiQmTZpk9TOw9nfQnp/fsrbM7NixA4mJiRg6dCgGDBiAXr16YdOmTWZlJk+ejL59+0Kr1UpfTz75pDwVbtDeueWIiLyUwWDAtpRDVstsTznk0i6nxYsXSy0a//73v/H5559j6NCh1Zbfv38/WrVqBQBo0aIFEhISsHfv3hrvExcXJ40D0Wq1uHjxIm7dumWxbH5+PgAgICCgxuv6+/sjNTUVgYGBAIAOHTqgc+fO2L9/f5WyU6ZMAQC0b98eH3/8sXS8R48euPvuuwEAnTp1wn333YcVK1YAAD755BNcvnwZs2bNAmBsUZk1axY+/PBDXL161ez6EydOBGD8XLp06YLjx49XW+8WLVrg6NGjeOSRR7Bp0yYMHz4crVq1wqJFi2TbFkPWAcDvv/8+Jk6ciMceewwAsGvXLjz44IPo3LkzunXrJpXbuHEjIiMjZaplBcFPA9fnwHpXk4+xHBFRHXbh4mXk6wqtlsnTFeLCxcuIimztkjpUHABsi1OnTuGpp55CUVERVCoVzpw5g/vuu6/G91Vcat8UPHQ6HYKDg6uUNR0rKiqq8bpKpRKHDh3C1KlTcefOHfj4+OD06dO4cuVKlbKtW1v+DCMiIsxet2/fXhr388svv6Bly5Zm41iioqJgMBhw6tQphISEVPs96nQ6q3WPiIjAv//9b7z77rvYu3cv3n//fbz88su4ffs25s+fX+P37myytswsXLhQSoOAMfEaDAakp7u/r9UmyoZAQKL1MgGJXG+GiOo8XUHNP6ztKedq3333HUaPHo3p06fj66+/RmpqKkaMGAEhRI3vrbjMvmkcTHXv69ixI4KCgnD69Okar7t582Y8/vjjWLhwIQ4fPozU1FTExsZavHZ1S/1XLiuEqLGOFb8PS9dXKBRW31tYWIjCQmOQbdSoEZKSkvDFF18gMTERO3bsqPZ9riRrmOnVq5c00vvOnTtYunQpunTpYrWZUFZCD9w+ar3M7WPGckREdZg60LZZK7aWc7Wvv/4aCoUCY8eOlY6VlTl/5qmPjw+efvppfPbZZxYDQWJiIubMmQPAuB5OmzZtcM899zhcp4sXL5q9vnDhgtQl1q1bN+Tk5Ji1EqWnp8PHxwedO3e26z4VbdmyBe+8806V4x06dDDrXqu4cWlxcbG0fYYreMRsphkzZqB58+bYv3+/NOWrokWLFkGr1WLAgAGYMWNGlb6+ikpLS6HT6cy+nKb4MFB+yXqZ8ixjOSKiOqxdmzBo1NbHhQSpA9CuTZibamRd165dodfrkZqaCgDIzc3FoUPWx/w46tVXX4W/vz9efPFFlJeXAzC2kqxcuRKnTp3C888/L9UpKysLZ8+eBQD89ttv+Pnnn+261w8//IAff/wRgHH9l7179+Jvf/sbAOM4mLCwMCxbtgyAMSgtW7YM06ZNM+ticsQHH3yA7Oxs6XVWVha2bt2Khx9+WDrWvHlzaWzRuHHjzBbUczaPCDPvvvsucnNzMWTIEPTv3x85OTnSuQ4dOmDgwIE4cOAADhw4gNLSUvTt21dq4qps0aJF0Gg00ld4eLjzKqrPqbmMPeWIiLyUUqlE0ogEq2XGjEgw++3cGUwrAAPGAcCWxrwcOnQIEyZMAABMmDABX3/9Ne677z4kJydj8uTJGDJkCGbOnIlOnTohJSUFzz33HA4cOFDlPbNmzZKmF7/wwgs4e/asWZmTJ09arKOvry+++OILBAQEICEhAVqtFv369cPPP/+MQ4cOSUFi+vTpePzxxzF06FCMGDECixcvRlRUFNatW4elS5ciJSVFGryr1WqxZcsW6R5TpkxBSkoKkpKS8O9//xsDBw7EsGHDMH/+fCQmJkr12LdvHw4fPoxevXohLi4OXbt2lcJN5evfvHkTU6ZMwfHjx6U6WJKQkID7778fDz74ILRaLQYOHIgxY8bgueeewzPPPGNWxwsXLiA+Ph5NmzZF165da3q8DlMIWzoM3cRgMCAyMhIPP/xwtR+iadDVqlWrMH369CrnS0tLUVpaalY+PDwc+fn5UKvVtatgUSqQNajmcuEHgcba2t2LiMjFbt++jYyMDLRt2xZ+fn4OXePE6XRsSzlkNhg4SB2AMSMS0L1zlLOqSnWUtb+DOp0OGo3Gpp/fss5mKisrM1vgSKlUIjo6GqdOnar2PWq1Gs2bN8dvv/1m8byvry98fX2dXlcAgH88oGoNlGcDsJQBFcbz/vGuuT8RkYfp3jkKMR3b4cLFy9AVFEEd2Bjt2oQ5vUWGyBpZ/7ZZ2tArJycHYWF/9LHOnDnT7HxpaSlyc3Od231kK4UPELLc9KLySeMfIcuM5YiI6gmlUomoyNaI69YRUZGtGWTI7WT9G3fq1Cns2bNHev1///d/OHv2LCZNmiQdW7VqFdLS0qTXr732GjQaDR566CG31lUSmAS02gKoWpkfV7UyHg9MkqdeRERE9ZSs3UzLly/HwoULsXjxYuj1eigUCuzcuRMDBgyQyrzxxhuYPXs2VCoViouL0axZMxw8eBAtWrSQseYAKg818pyhR0RERPWKRw0AdgV7BhDZpGAbkD0OVcfM/N7NxNYZIvISzhgATFQbzhoAzI5Newg9cHUmLA/+/f3Y1VlcNI+IiMiNGGbsUeOieYKL5hEREbkZw4w9uGgeERGRx2GYsYdPy5rL2FOOiIiIak3W2Uxeh4vmERF5jJKSEixduhRffPEFVCoVSktL4e/vjwcffBDjx4/HqlWr8Mknn+Ds2bNISDDfeiEvLw+xsbFYs2YNhg0bhuPHj8PPzw+dOnWCwWDA9evXER0djRUrViAyMhIAsGDBgirXu3XrFkJCQvDGG2+ge/fu7v4I6HcMM/YwLZqXPQ7G2UuVA43gonlERG5QUlKCwYMHIz4+HgcPHoRKZfxxtn37djz88MO4ceMGkpOT0aZNG0yZMkXaYNIkNTUV69atQ8OGDZGamgqtVovIyEisW7cOgHGB1mHDhmHixIk4cuQIAOMGkpWvJ4TAjBkzMHz4cJw+fRpBQUFu+gSoInYz2cu0aJ6ySdVzyqburw8RkdyE3rh3ne5T459umNE5b948lJaWYsmSJVKQAYAxY8bgqaeeqvH93bp1w+zZs6s97+vri7Fjx+Lbb7+FTqertpxCocATTzyBK1eu4JtvvrHvmyCnYcuMoww3LR/LHse1Zoio/ijYZlyyouJMT1VrYyu2i/4dLC8vx5o1azB37lwoFJW3lgGee+455OXlVfv+5ORkREZGYvLkyTXeB0CN2zPcuXMHAMz2GiT3YsuMvbjWDBGRkWkR0cpLVpRnG48XbHPJbc+cOYP8/Hx07tzZ4vk2bdrUevxKbm4uPvroIzz66KMICAiotlxJSQkWL16M6Oho9O/fv1b3JMexZcZe9qw101jrrloREblXjb/YKYy/2AWMdvo4wvz8fACwGjIq02q10n9nZmYiOTm5SpmUlBRotVrk5eXh7NmzWLRoEf72t79ZvV5xcTFiY2Nx8OBB+Pv721wfci6GGXtxrRkiIll/sQsODgYAFBUV2fyeigOALQUZABgxYgTWrVsHg8GAGTNm4M0338Tjjz9uMTRVHlBM8mI3k7241gwRkay/2HXs2BFBQUE4ffq0Q+9PTk62Ol5GqVRi8eLF0Ol0WLNmjYO1JHdimLGXaa0Za1ThXGuGiOo2GX+x8/HxwdNPP43PPvsMlvZKTkxMxJw5c2p1D41Gg8cffxzLly+XBgKT52KYsZfCB1A/Yr2MegLXmiGiuk36xa7qbCIjhUt/sXv11Vfh7++PF198UQobQgisXLkSp06dwvPPP1/re/ztb39DdnY2Nm/eXOtrkWsxzNhL6I1rKVij28jZTERUt5kWETW+qHzS+IcLFxH19fXFF198gYCAACQkJECr1aJfv374+eefcejQIYSEhGDBggVYvHgxAOOA3YULF1a5TllZGbRaLY4fPy4NAC4sLAQAREREYOzYsZg9ezZGjx5d5XrLly+vcj2Sh0JYaqOrQ3Q6HTQaDfLz86FWq2t/waJUIGtQzeXCD3I2ExF5tNu3byMjIwNt27aFn5+fYxexuM5MuDHIcL0tqoG1v4P2/PzmbCZ7cTYTEdEfApOM06+LDxv/3fNpaexaYlc7uRHDjL04m4mIyJzChy3RJCuOmbFXjYPeYNyjibOZiIiI3IJhxl7SoDcrQ40MuUDhDrdViYiIqD5jmHFEwOiad8jm/kxE5CXq+DwQ8mDO+rvHMOOI4sPG1hdrTMt4ExF5KB8f4yDdsrIymWtC9VVxcTEAoEGDBrW6DgcAO6I827nliIhkoFKp4O/vj+vXr6NBgwZQKvn7LbmHEALFxcW4du0agoKCpGDtKIYZR5Rfd245IiIZKBQKtGzZEhkZGfjf//4nd3WoHgoKCkJoaGitr8Mw4whVc+eWIyKSScOGDREdHc2uJnK7Bg0a1LpFxoRhxhGqVs4tR0QkI6VS6fgKwEQegB2kjuDO2URERB6DYcYRZhusVcOFG6wRERHRHxhmiIiIyKsxzDhC6IGcJ6yXufIEF80jIiJyA4YZRxSn1rxonj7XWI6IiIhcimHGEUWpzi1HREREDmOYcYSVDbMdKkdEREQOY5hxRCOtc8sRERGRwxhmHNFYW/Ou2cqmxnJERETkUgwzjlD4AC3XWC/Tcg3XmSEiInIDhhlHBSYBrbYCPpW2LPBpZTwemCRPvYiIiOoZhhkiIiLyagwzjirYBmSPA/TZ5sf1l43HC7bJUy8iIqJ6hmHGEUIPXJ0JQFg6afzj6iyuAExEROQGDDOOKD4MlF+yUkAA5VnGckRERORSDDOO0Oc4txwRERE5jGHGET4tbStXet619SAiIiKGGYf4x1edkm1J/r84boaIiMjFGGYcofABgp+ouVz5JY6bISIicjGGGUc1jLatHMfNEBERuRTDjKNsHTdjazkiIiJyiKxhZseOHUhMTMTQoUMxYMAA9OrVC5s2bapSbvXq1YiLi0P//v0xatQoZGdnW7iam/nHA6rWABTVFFAAqnBjOSIiInIZWcPM+++/j/Hjx+OLL77A119/jeTkZDzyyCM4efKkVGbbtm2YN28eUlJS8M033+Duu+9GYmIiDAaDjDWHcdxMyHLTi8onjX+ELONmk0RERC4ma5hZuHAhJk6cKL3WarUwGAxIT083KzNp0iS0aNECADBz5kz88ssv+Pzzz91e3yoCk4Amc1D1Y1Qaj3OzSSIiIpeTNcz06tULKpUKAHDnzh0sXboUXbp0wdChQwEAt27dwrFjx9C7d2/pPRqNBh06dMCXX34pS53NFGwDbr4BoPL0a73xOPdnIiIicjmPGAA8Y8YMNG/eHPv378e+ffsQEBAAALhw4QIAIDQ01Kx8aGiodE42Vvdn+h33ZyIiInI5jwgz7777LnJzczFkyBD0798fOTnG6czFxcUAAF9fX7Pyvr6+0rnKSktLodPpzL5cgvszEREReQSPCDMA4OPjg+TkZAgh8NZbbwEA/P39ARgDSkWlpaXSucoWLVoEjUYjfYWHh7umwtyfiYiIyCPIGmbKysrMXiuVSkRHR+PUqVMAgHbt2gEArly5YlbuypUr0rnK5s6di/z8fOkrKyvLBTUH15khIiLyELKGmbi4uCrHcnJyEBYWBgAIDg5Gz549kZaWJp3X6XQ4d+4c7r33XovX9PX1hVqtNvtyiRrXmQHXmSEiInIDWcPMqVOnsGfPHun1//3f/+Hs2bOYNGmSdOyVV17B+vXrcf36dQDAihUrEBMTg5EjR7q9vmbM1pmphnoC15khIiJyMZWcN1++fDkWLlyIxYsXQ6/XQ6FQYOfOnRgwYIBUJikpCdeuXcPw4cPh5+eH4OBg7Nq1C0qlBwz3Ma0zc3Op5fM33wAa9eV6M0RERC6kEEJYmVvs/XQ6HTQaDfLz853f5ST0wG+RVmY1KYxdUe0z2EJDRERkB3t+fntA84YX4/RsIiIi2THM1AanZxMREcmOYaY2OD2biIhIdgwztVHj9GwFp2cTERG5GMNMbUjTs6sbQy2AkGUc/EtERORCDDNERETk1RhmakPogZwnrJe58gR3ziYiInIhhpnaKE4FDLnWy+hzjeWIiIjIJRhmaqMo1bnliIiIyG4MM7VhZY9Jh8oRERGR3RhmaqOR1rnliIiIyG4MM7XRWAsom1ovo2xqLEdEREQuwTBTGwofoOUa62WCpnKdGSIiIhdimKmtwCSgyfPVn7/5BlCwzX31ISIiqmcYZmpL6AHdp9bLXJ3FtWaIiIhchGGmtooPA+WXrBQQQHmWsRwRERE5HcNMbelznFuOiIiI7MIwU1s+LZ1bjoiIiOzCMFNb/vG2Tc/2j3dPfYiIiOoZhhl34ArARERELsMwU1vFh23cbJIDgImIiFyBYaa2OACYiIhIVgwztcUBwERERLJimKkt/3hA1RrVD4xRAKpwDgAmIiJyEYaZ2lL4ACHLTS8slwlZxv2ZiIiIXIRhxhkCk4BWWwBlk6rnLB0jIiIip2GYcSZLs5oMN4HscdxskoiIyEUYZpxB6IGrM6s7afyDm00SERG5BMOMM3CzSSIiItkwzDgD15ohIiKSDcOMM3CtGSIiItkwzDgD15ohIiKSDcOMM1hda+b311xrhoiIyCUYZpzFtNaMT5j5cZ9WxuOBSfLUi4iIqI5jmHE2RaWWmep6noiIiMgpGGacpWCbcXG8ylO0y7O5aB4REZELMcw4g7RonrB00vgHF80jIiJyCYYZZ+CieURERLJhmHEGLppHREQkG4YZZ+CieURERLJhmHEGLppHREQkG4YZZ+CieURERLJhmHEW06J5qlbmx1WtuWgeERGRC6nkrkCdEpgENE4Ebr0H3PkNaNAeCH4aUDaUu2ZERER1FsOMMxVsM643U3Ga9q03jV1QbJkhIiJyCXYzOQtXACYiIpIFw4wzcAVgIiIi2TDMOANXACYiIpKNrGNmNm3ahA8++AB6vR46nQ5t2rTB0qVL0a5dOwDA5MmTcebMGfj5+Unv6dixI1avXi1XlS3jCsBERESykTXMPProo9i9ezeGDRsGg8GAqVOnYsSIEThx4oQUYDZu3IjIyEg5q1kzrgBMREQkG1m7mUaPHo1hw4YZK6JU4plnnsH58+dx7NgxOatlP64ATEREJBtZw8zmzZvNXptaY8rKyuSojuOsrgD8O64ATERE5BIeNQD422+/RVhYGPr37y8dW7RoEbRaLQYMGIAZM2bg6tWrMtbQCtMKwMomVc9ZOkZERERO4TFhprS0FEuXLsWKFSvQoEEDAECHDh0wcOBAHDhwAAcOHEBpaSn69u2LwsJCq9fR6XRmX25lyLVw7CbXmiEiInIRhRDC0uIobjd58mSEhYXh9ddfr7aMTqdDcHAwVq1ahenTp1ssk5ycjPnz51c5np+fD7Va7bT6ViH0wG+RVqZoK4zjatpnsLuJiIioBjqdDhqNxqaf3x7RMvPSSy9BpVJh4cKFVsup1Wo0b94cv/32W7Vl5s6di/z8fOkrKyvL2dW1jGvNEBERyUL2MLNkyRJkZmZizZo1UCgUOHr0KI4ePQoAmDlzplnZ0tJS5ObmIjw8vNrr+fr6Qq1Wm325BdeaISIikoWsYWbVqlXYsGEDZs6ciWPHjiEtLQ27du3CyZMnpfNpaWlS+ddeew0ajQYPPfSQXFWuHteaISIikoVsi+YVFBRgxowZMBgM6Nevn9m5tWvXAgDeeOMNzJ49GyqVCsXFxWjWrBkOHjyIFi1ayFFl60xrzZRnw/IeTQCUTbnWDBERkZN5zABgV7FnAFGtFWwDssdaL9Nqq3EaNxEREVXL6wYA1xkBo42tL9VScPdsIiIiJ2OYcabiw5bXmZFwRhMREZGzMcw4E2c0ERERuR3DjDNxRhMREZHbMcw4k7R7dg30N1xfFyIionqCYcaZFD5Ai7dqLnftWQ4CJiIichKGGWfzaV5zGQ4CJiIichqGGWfjIGAiIiK3YphxNg4CJiIiciuGGWeTBgErqimgAFTh3NaAiIjISRhmnE3hA4Qst1JAAOoJxnJERERUawwzrhCYBDSZU/35m28Y93EiIiKiWmOYcQWhB3SfWi/DPZqIiIicgmHGFYoPA+WXrBTgHk1ERETOwjDjCpyeTURE5DYMM67A6dlERERuwzDjCpyeTURE5DYMM65gNj27cqD5/XXIMk7PJiIicgKGGVcJTAJabQF8wsyP+7QyHg9MkqdeREREdQzDjKspKrXMVNfzRERERA5xWpi5deuWsy5VNxRsA7LHVZ2iXZ5tPM5F84iIiJzCoTDz8ccfY/Dgwfj+++8BABMnTkSzZs0QGhqKH374wakV9EpCD1ydCUBYOmn8g4vmEREROYXKkTetXr0a8+bNQ58+fbBnzx5s27YNu3btQnl5OV544QWkpqY6uZpexp5F8xpr3VUrIiKiOsmhlhmVSoUhQ4ZAoVDgo48+wsMPP4yRI0figQcegKLyGJH6iIvmERERuY1DLTOFhYUwGAy4fv06du/ejd27d0vnysvLnVY5r8VF84iIiNzGoTAzZMgQdOrUCUVFRejcuTMGDRqErKwsvP/++9BoNM6uo/cxLZpXng3L42YAKJty0TwiIiIncCjMLFq0CD179sTly5fx6KOPAgCuXLkCX19fzJs3z6kV9EqmRfOyx1ZfxpALFO7gejNERES1pBBCVNN0UDfodDpoNBrk5+dDrVa778ZCD5wPMYYWixTG1pv2GVwJmIiIqBJ7fn47NAA4JSUFU6dOxcmTJwEAL7/8MjQaDfr06YNz5845csm6p/iwlSADmM1oIiIiIoc5FGaWLl2KAQMGICoqCl999RWWLFmCRYsW4dFHH8XMmTOdXUfvxBlNREREbuHQmBkhBKZOnQoAWLduHR588EE8/fTTAIBt27iyLQDbZyqVnndtPYiIiOo4h1pmbt++DQAoKCjA9u3bMWnSJOkc15n5nX+8cVPJmuT/iysBExER1YJDYSYmJgaDBg3CwIED0axZMyQmJiIvLw9r1qxhmDFR+ADBT9RcrvwSx80QERHVgkNhZuXKlRg5ciQSEhKwd+9eKJVKHDt2DN9++y1efPFFZ9fRezWMtq0cx80QERE5zKExM76+vnj++efNjg0ePBiDBw/Gr7/+6pSK1Qk+LZxbjoiIiKpwKMyYlJaW4tq1a6i4VM306dNx5MiRWlesTrB1BZ86vdIPERGRazkUZrKzs/HYY4/h0KFDqONr7tWO4ZpzyxEREVEVDoWZv/3tbxg0aBDee+89TJ48GRs3bkRpaSm2bt0KnU7n7Dp6L244SURE5HIOhZlr167hlVdeAQD4+fkhIiICADB37lyMGTPGebXzdtKGk5eqL6MK54aTREREteDQbCal8o+33blzB8XFxQAAvV6Ps2fPOqdmdYHCB1A/Yr2MegL3ZiIiIqoFh8JMQEAA5syZg8LCQvTp0wdDhw7FwoULMWLECDRv3tzZdfReQg/oPrVeRreRi+YRERHVgkNh5vXXX0fbtm1RVlaGV155BUFBQVi8eDEKCgqwatUqZ9fRexUftt7FBHCzSSIiolpyaMxMjx490KNHD+n1nj17pP+eOHEiPvnkk9rXrC7gZpNEREQu51CYyc/Px4oVK/DTTz8hPz/fbHr28ePHnVU378fZTERERC7nUJh5+OGHUVhYiH79+qFx48bScSEEMjMznVU37yfNZspGtSvj+TTlbCYiIqJacCjMXL9+HUePHrV4TqPR1KpCdYrCBwhZDmSPrb6MPhco3AEEJrmvXkRERHWIQwOAe/bsidu3b1s817Ilu0zMBIwGlE2tFFAAV2dxRhMREZGDFMKB/Qh0Oh1eeeUVhIaGomXLlvDx+WOdlMWLF+PUqVNOrWRt6HQ6aDQa5OfnQ61Wu78CRalA1qCay4UfBBprXV0bIiIir2DPz2+HupneeecdvPvuu2jWrBn8/f3Nzl29etXm62zatAkffPAB9Ho9dDod2rRpg6VLl6Jdu3ZSmdWrV2P16tVo1KgRgoKCsGbNGrRq1cqRasuDM5qIiIhcyqEw8+GHH+LMmTOIjo6ucm748OE2X+fRRx/F7t27MWzYMBgMBkydOhUjRozAiRMn4Ofnh23btmHevHk4ceIEWrRogQULFiAxMRFHjx41W4XYo3FGExERkUs5lAi6du1qMcgAwGeffWbzdUaPHo1hw4YZK6JU4plnnsH58+dx7NgxAMDChQsxadIktGjRAgAwc+ZM/PLLL/j8888dqbY8TDOaoKimgIL7MxEREdWCQ2HmiSeewLJly3D58mVUHnKTlGT7rJzNmzebvfbz8wMAlJWV4datWzh27Bh69+4tnddoNOjQoQO+/PJLR6otD9OMJuOLyieNf4Qs4/5MREREDnKom+mBBx4AADz33HNOrcy3336LsLAw9O/fHydOnAAAhIaGmpUJDQ3FhQsXnHpflwtMAlptAa7ONN/eQBkMNJlpnPFEREREDnF4O4Nly5ZVOS6EwOzZsx2qSGlpKZYuXYoVK1agQYMG0k7cvr6+ZuV8fX2lc9Vdp7S0VHqt0+kcqo/TBSYZQ8uNhcCt5YDhpvHrxjwg71/G1huuNUNERGQ3h8LMK6+8goSEBIvnFi9e7FBFnnzySYwbNw5jxxoXmDPNkqoYTEyvK646XNmiRYswf/58h+rgcoU7gNxkVFkNuDwbyB5nbL1hoCEiIrKLQ2NmTIHDEntmM5m89NJLUKlUWLhwoXTMND37ypUrZmWvXLliNnW7srlz5yI/P1/6ysrKsrs+LiH0xm4mi9sa/H6Mi+cRERHZTfb5zUuWLEFmZibWrFkDhUKBo0eP4ujRowgODkbPnj2RlpYmldXpdDh37hzuvffeaq/n6+sLtVpt9uURig+bj5epQgDlWcZyREREZDNZw8yqVauwYcMGzJw5E8eOHUNaWhp27dqFkydPAjB2Z61fvx7Xr18HAKxYsQIxMTEYOXKknNV2jK2L4hXucG09iIiI6hiHxsw4Q0FBAWbMmAGDwYB+/fqZnVu7di0A4zTva9euYfjw4fDz80NwcDB27drlPQvmVWTroni3lhnXnOHYGSIiIps4tDeTN5F9byYToQd+izQO9rU4bqYCVTjQPoNrzxARUb1lz89vL2zi8FLS4nk2ZEeOnSEiIrIZw4w7BSYBwbNsK8uNJ4mIiGzCMONutq72y40niYiIbMIw427ceJKIiMipGGbczerGkwAguPEkERGRHRhm5GDaeFLZpOo5hZqrABMREdmBYUZOhptVjwkdcHk8cO0F99eHiIjICzHMyMHqPk2/u7kU0G1xW5WIiIi8FcOMHGrcp+l3V59mlxMREVENGGbkYOsaMvrrXDyPiIioBgwzcrBnDRkunkdERGQVw4wc/OMBZTPbynLxPCIiIqsYZuSg8AFC36u5nE9TLp5HRERUA4YZuagfApo8b72MPhco3OGe+hAREXkphhk5NV9keeE8iQK4OoszmoiIiKxgmJFT8WHLC+dJBFCexRlNREREVjDMyMnmKdqc0URERFQdhhk5KVs4txwREVE9xDAjJ0ubZtemHBERUT3EMCMn/TXnliMiIqqHGGbkZOuCeFw4j4iIqFoMM3LyjwdUrWG9H0kJlLNlhoiIqDoMM3JS+AAhy2soZAByHgauveCWKhEREXkbhhm5BSYBYZ8B8LFe7uZSQLfZLVUiIiLyJgwznsCnOQAbVvm9MoOrARMREVXCMOMJbF0Uz3CdqwETERFVwjDjCeyZrcTVgImIiMwwzHgC//jfu5pswGnaREREZhhmPIHCBwh5r+ZyqnBj8CEiIiIJw4ynUI8DmjxvvYxfnDH4EBERkYRhxpO0+CfQ+IHqzxfu4HozRERElTDMeBJDGVC0x3qZm28ZyxEREREAhhnPcus91LzejP73ckRERAQwzHiWO785txwREVE9wDDjSRq0d245IiKieoBhxpMEP40a92gCAJ8Ql1eFiIjIWzDMeBJlQ6DJszWXuzKRs5qIiIh+xzDjaVr8EwieU3O5m0sB3RbX14eIiMjDMcx4ooBRtpW7+jR30SYionqPYcYT2bqZpP46UJzq0qoQERF5OoYZT2TPZpLZ44GCba6rCxERkYdjmPFE/vGAspltZQ03gexxDDRERFRvMcx4IoUPEGrnKr9XZ3H8DBER1UsMM55K/VDNu2hLBFCeBRSlurJGREREHolhxpO1+CcQthlQBtpW/jLHzxARUf3DMOPp1OOAsO22leX4GSIiqocYZrxBYy2gag1AYVt5jp8hIqJ6hGHGGyh8gJDlNhb+ffzMzZUMNEREVC/IHmbKysowd+5cqFQqZGZmmp2bPHky+vbtC61WK309+eST8lRUboFJQKstgLKJbeWvzwZ+i2SXExER1XkqOW+emZmJRx55BB06dIBeb7kVYePGjYiMjHRvxTxVYBKg1ABZ99pWvjzbOIam1Rbje4mIiOogWVtmCgsLsWHDBkyZMkXOangXf60d42eE8Q+OoSEiojpM1jATExODqKgoOavgfczGz9gYaExjaHSfGteiYbAhIqI6RNZuJlssWrQIZ8+eRXl5OXr06IFXX30VISEhcldLXqbxM1dnAuWXbHvP9dl//LeymXGFYfVDrqkfERGRG8k+ANiaDh06YODAgThw4AAOHDiA0tJS9O3bF4WFhdW+p7S0FDqdzuyrTgpMAtpnAs3ftv+9hhvGBfauvfDHMaE3ttqw9YaIiLyMQggh5K5EamoqBg0ahIyMDKuDfXU6HYKDg7Fq1SpMnz7dYpnk5GTMnz+/yvH8/Hyo1WpnVdlzCL1x1lJ5NqQxMvYI2wwolFVbeVStjd1ZgUnGexQfBvQ5xh29/eON3V1EREQuotPpoNFobPr57fHdTBWp1Wo0b94cv/32W7Vl5s6di2effVZ6rdPpEB4e7o7qycM0hiZ7HIxjaOwMNFemAQYLrVemmVBN5hhbayoHHc10wDea4YaIiGTn0d1MM2fONHtdWlqK3Nxcq+HE19cXarXa7KvOM42hUbWy/72WggwAYygSwM2lVcfllF8CcucBlycCWYPM17NhdxUREbmZR4eZVatWIS0tTXr92muvQaPR4KGHOHC1CtMYmvCDQNgnjo2lcZSpFefaC8ZgkzXIctAhIiJyAVm7mcrKyjBs2DDk5eUBACZMmIDw8HBs3rwZAPDGG29g9uzZUKlUKC4uRrNmzXDw4EG0aNFCxlp7MIWPcR8nwNgikrvQONjX5X7v2rq5tOqp8ktA9lig1VYu3EdERC7hEQOAXcmeAUR1jm6zcdaSJ/BpCkRd5dgaIiKyiT0/vz26m4lqSf0Q0OR5KwUUgLIpbN6Nuzb0uUBxquvvQ0RE9Q7DTF3X4p/G6dc+zc2Pq8KNg4Zbrvn9gBsCTVGq6+/hAIPBgPTMSzh28izSMy/BYDDIXSUiIrKDV03NJgepxwGBY6pfK8bSasKqcEA9Abj5xu8HnNAb6Ya8ZK8Tp9OxLeUQ8nV/LMSoUQcgaUQCunfmVhtERN6AY2bIqLqF8Qq22bdtgjWtvwQChtT+Ok5y4nQ61m7aU+35KeNHMdAQEcmkzi6aRy5UcSZURYFJQMDoP4JO2Xng1hpAn/1HGVVrQJ8HiOq3mYCyqeXry8RgMGBbyiGrZbbtTUVMx3ZQKtkbS0TkyRhmqGaVg07T/1e1Fadwh3EKdnVarvGomUwXLl4261qyJL+gCF8c/hHDE+52U62IiMgR/JWT7GcKN+pHjH8qfH5fhXgr4FNpFWKf1h65xoyuoMimcimp3+HE6XQX14aIiGqDLTPkPJW7pDx43yZ1YGOby25POcTuJiIiD8YwQ85V3dgbD9OuTRg06oAau5oAIE9XiAsXLyMqsrUbakZERPbir5pULymVSiSNSLC5vK3dUkRE5H4MM1Rvde8chRHavjaVtadbioiI3Ithhuq1ofG9oQkMsFomSB2Adm3C3FQjIiKyF8MM1WtKpRJJ91nvbhozIgFKpZLbHhAReSgOAKZ6r3vnKEwZP6rKtgZB6gCM+X1bA257QETkubidAdHvDAYDLly8DF1BEdSBjdGuTRiUSiW3PSAikgG3MyBygFKprDL92pZtD7gODRGRvPivL5EVtmx7YFqHhoiI5MEwQ2SFrevLcB0aIiL5MMwQWWHr+jIFRcWc5UREJBOOmSGywpZtDxQKBf6z7yvpNWc5ERG5F1tmiKywZduDyhMC83WFWLtpD3fbJiJyE4YZohqY1qHRqM1XClYoFFbft2n3fpSXl7uyakREBK4zQ2SziuvQFBQVm3UtVaexfyOMTxzMLiciIjvZ8/ObLTNENjKtQxPXrSMCG/vb9J6i4hJ2ORERuRjDDJED7N1F+7NdX+LchYuc6URE5AKczUTkAFtmOVVUXFKK9zds50wnIiIXYMsMkQNsmeVkCWc6ERE5H8MMkYNMs5wa+/vZ/d7tKYfY5URE5CQMM0S10L1zFJJnT0Nj/0Z2vS9PV4j0zEsuqhURUf3CMENUSyqVCuMTB9v9vnVbPmd3ExGREzDMEDlBdQvrWVNSUsrxM0RETsDZTERO0r1zFGI6tkN6ZjbWb9mD4pJSm9732a798PP1RVRkKyiV/P2CiMhe/JeTyImUSiU6tAvHw/ffa/N7iktu4/0N27Bg+Vq20hAROYBhhsgFTN1O/o18bX4Pp20TETmGYYbIRbp3jsKkcaPsfh+nbRMR2YdhhsiFoiJb2TUoGDBN2852UY2IiOoehhkiF3J0peAPN+7CvkPfs4WGiMgGDDNELubItO2yO3eQkvod/v7GvziGhoioBgohhJC7Eq6k0+mg0WiQn58PtVotd3WoHjMYDEjPvIR1Wz5HiY3Ttk2mjB/FzSmJqF6x5+c3W2aI3MQ4bbsNJtgxbdvks137ce5CFrudiIgsYMsMkQxOnE7Hxl1f2t1Co1EHIGlEAltpiKjOY8sMkYfr3jkKk8eNtPt9XIuGiKgqbmdAJJOoyNbQqAOQryu0+72bdu9H2Z1yBKkD0K5NGLdBIKJ6jd1MRDI6cTodazftqdU12PVERHWRPT+/GWaIZHbidDo+27UfxSW3a3WdEdq+aN4kCOrAxmytISKvxzBTAcMMeQODwYAvDv+IQ9//ZPegYEvYWkNE3o5hpgKGGfImtVmLxpJJ40Yitmu0E2pGRORenM1E5KVqsxaNJR9t3Yvjv55zyrWIiDyV7GGmrKwMc+fOhUqlQmZmZpXzq1evRlxcHPr3749Ro0YhO5sb8FHd58gWCJYIIbB+y15O5SaiOk3WqdmZmZl45JFH0KFDB+j1+irnt23bhnnz5uHEiRNo0aIFFixYgMTERBw9epSDG6nO6945CjEd2+HCxcvI0xXiP/u+QlFxiUPX2rz7AKdyE1GdJeuYmV9++QV+fn64dOkSBg0ahIyMDERGRkrne/XqhXvvvRdLliwBAOTn56NZs2bYvn07EhMTbboHx8xQXeGMadwABwcTkXfwmjEzMTExiIqy/A/qrVu3cOzYMfTu3Vs6ptFo0KFDB3z55ZfuqiKRx3BW1xNXESaiusZjVwC+cOECACA0NNTseGhoqHTOktLSUpSW/jELRKfTuaaCRDKo2PWkKyjC9Zt5SEn9zqFrbU85BD9fXxQWFXNtGiLyah4bZoqLiwEAvr6+Zsd9fX2lc5YsWrQI8+fPd2ndiOSkVCoRFdlaeh3SrAk+2roX9vYY5+kK8f6GbdJrdj8Rkbfy2F/D/P39AcCslcX02nTOkrlz5yI/P1/6ysrKcmk9ieQW2zUaj40dUevrmLqf9h36HsdOnkV65iUYDAYn1JCIyLU8tmWmXbt2AIArV66YHb9y5QqGDh1a7ft8fX2rtOYQ1XWxXTtAqVRiW8ohhzaurKhitxVba4jIG3hsy0xwcDB69uyJtLQ06ZhOp8O5c+dw773OWVCMqC7p3jkKr86cghmTxuJPY4ajsb9fra/JwcJE5A08NswAwCuvvIL169fj+vXrAIAVK1YgJiYGI0eOlLlmRJ7JNJ7mru6dMD5xiNOuuz3lELuciMhjydrNVFZWhmHDhiEvLw8AMGHCBISHh2Pz5s0AgKSkJFy7dg3Dhw+Hn58fgoODsWvXLs64ILKBaSq3M7qe8nSFuHDxMqIiW8NgMEizqTgLiog8ATeaJKrjKoaPgMaN8PF//gtdQZHd1/lz0gioVD5VwlGjRr5IuLsnhsb3ZqghIqfhrtkVMMwQmXN0JeER2r5W17Txb+SHh0YNQkBjf7baEFGtMcxUwDBDVNWJ0+l2dT8FqQNgEMLuFh3OhiIiRzHMVMAwQ2RZxe6nmlYSrqlVpiZTxo9ioCEiu9jz89tj15khIteqvJJwyxZNq7TWBKkDMGZEAsrLq+5qb49te1PRsEEDXLiYDUCBqMhWiIpszS4oInIKtswQkaS6mUrpmZfw7vqtTr2XfyM/PHz/EKnFhrOkiKgitswQkUMqt9aYtGsTBo06oNZTvCsqLrmNtZv2YMr4UQBQpVVIExiAe3rFoHmTIIYbIrKKLTNEZBNHZ0HVxL+RH4pLbtdYjoOJieoXe35+89ccIrKJaRE+/0a13yahIluCDGB5awWDwYD0zEvcGJOonmM3ExHZrHvnKMR0bIcvDv+Ir77/CcUlpTW/ycm2pxxCTMd2+OXshapdU7+33sR0bMfxN0T1CLuZiMghlQfsFhaV4D///cqp42qqY8sCfhVbfDTqADw4bCACGjdiwCHyElxnpgKGGSL3Md86wR8fb98HXaH9WyfUpFEjX5TUslWosX8j3NWtI2I6tbcYbDi7ikheDDMVMMwQyceWQcO2DgB2pcqDiy2tkMwByETuxTBTAcMMkbxOnE7HZ7v2VwksjRv5Yfz9QwDArllSrgw/pmni1urD1YyJ3INhpgKGGSL5GWcdZSM9MwuWVgC2Z6+o2m6tYI0msDEABfILqq9HgH8jjB4+EEHqAHZPEbkQw0wFDDNE3qHyXlFHjp4029jStLVCTMd2WLB8rVsGGtfE0e6p6gIPgxDRHxhmKmCYIfJO1n6wu2oBP0fZ0z1VXeCJi+mAY7+cs2mcDkMP1QcMMxUwzBDVTZZCgVyDiYPUATAIYdaSZKnM6GHxWL9lr93XrzhOx5HBydbCT03ByLQwYXpmNgCBqMhwREW2qjE8MXBRbTHMVMAwQ1R3WfqBaWkxPVvZMmamNhr7N0JRcYnd7wtSB+DvM6fgl7MX7B6cbC38ABb2xKoQjKobvF15k9DK7Alc9oQeBqT6hWGmAoYZovqn6oJ+xfjPfw/XGHBs6S6Sy1N/HoNPdnxh9XswhR5ndMcN6heHg0eOWS1TXXiyNXDZE3oslW3s74dxIwcjtmu0WVnz9Y4aAVCgsKjYLQGIgct5uGs2EdVrlnb/7t45ChcuXsYvZ39D2okzKCr+o7XBNLjY9AN0yvhRDrfuuEp6ZnaN9cnTFeLCxcuIimwNg8GAbSmHHL5f6rc/1Vhm295UxHRsZ9ZlVdM9K25HYSn0mPbgqhx6LJUtKr6N9Vs+x8XLcXhgaLxU1tqzc+V6QY6uT+RNAahiXRv7+yHnWi5yb+WjWZMg9L+rG1QqeWIFwwwR1QumgBMV2RoPDI23+sPDtAfVhYuXkacrxH/2HTILP5XZMmamsb+f1WvUzLZGdFMdLly8XKswZkujfX5BkRSebL1nnq4Q6ZnZNoceADWWPXjkGNqEhUCpVNbYEmUpLDlDdYGrpvt50wKNNQXFHf89DO09PaVg6U6eGf2IiFzIFGziunU0W+/GUpm7unfC+MQhVq83ZkQCxt6ntVpm3MjB0KgDHKpvkDoAUZHhNpVVBzYGAKvBypkq3sfWe6ZnZtncymRrKNv6eSq27k216f6AMSw5a5d1W1ukKt/PFIAqf3+WdoiXW3V1rUgIgYNHjmHnF4fdWDMjhhkiohp07xyFKeNHVQkjQeoA6TfumsrEdo2WBt3aa8yIBERFtqoxDJkW8gP+CDWuVvE+tt9TYVMpXUGRzQGpsLjErgBnCkvOYGuLVMX7ORqA5GBvl2Xqtz+hvLzchTWqit1MREQ2qNj1ZEv3lKUypsBTuak+SB2AnhbWmak8lidpRILVbpQxIxKke7VrEwaNOsDhriaFQlFjV5Pm9+/PxJZ7GluZWsGWX95dHcic1Xpl63UqlrMnAFUe/+Vu9nZZCiHwTdpJJPTt6cJamWOYISKykaWBxfaWsRZ4Eof0rzEsVReGxlQaY6FUKmsMP9Zo7+lZ42ympPu0ZvWz5Z7GVqbWNoUeU1Cq/Xgjy5wVlmy9TsVyjgQguThShxs385xfESsYZoiI3Ky6wGNLWLKlhahiWWvhB6i6zkzFYBTZuqXd68zYGrjsaWUaN3Iw1m/53OrnYssg7MrlK7Yq1YatLVIV7+dIAJKLI3Vo1iTI+RWxgmGGiMjL2BJ6TGoKPzV1i8V0bGf3CsC2dsnZ2soU2zUaFy9bX/fGFM5sbYmqGJZqy9YWqYr3cyQAycXeLkuFQoH+d3Vzca0q3ZOL5hERkVzsWWPl+K/nsOXzVLNVlCuHn5qmD1sKS85i6d7W7mfPAoNys2cBxkH94pwyPZsrAFfAMENEVHfYEn68aQVgewOQnGoKigqFwqnrzDDMVMAwQ0REnowrAFvG7QyIiIi8hD1joORWua4d20fIWJs/eGb0IyIiIrIRwwwRERF5NYYZIiIi8moMM0REROTVGGaIiIjIqzHMEBERkVdjmCEiIiKvxjBDREREXo1hhoiIiLxanV8B2LRbg06nk7kmREREZCvTz21bdl2q82GmoKAAABAeHi5zTYiIiMheBQUF0Gg0VsvU+Y0mDQYDzp49iy5duiArK4ubTXoonU6H8PBwPiMPx+fk+fiMvAOfU82EECgoKEBYWM0bb9b5lhmlUolWrVoBANRqNf/SeDg+I+/A5+T5+Iy8A5+TdTW1yJhwADARERF5NYYZIiIi8mr1Isz4+vpi3rx58PX1lbsqVA0+I+/A5+T5+Iy8A5+Tc9X5AcBERERUt9WLlhkiIiKquxhmiIiIyKsxzBAREZFXqxdhZvv27bjrrrsQHx+PhIQE/Prrr3JXqV4pKyvD3LlzoVKpkJmZWeX86tWrERcXh/79+2PUqFHIzs42Oy+EwIIFCxAXF4c+ffrg0UcfRX5+vptqX/dt2rQJw4YNw5AhQ9C7d2+MHTsWFy5cMCvDZySvHTt2IDExEUOHDsWAAQPQq1cvbNq0qUo5PifPsXLlSigUCqSmppod5zNyEVHHff/99yIgIECcOXNGCCHE+vXrRatWrYROp5O5ZvVDRkaG6Nu3r3jssccEAJGRkWF2fuvWrSIkJERcvXpVCCHE/PnzRWxsrNDr9VKZN998U3Tt2lUUFRUJIYSYMmWKeOCBB9z2PdR1DRo0EPv27RNCCKHX68WkSZNEdHS0KCkpEULwGXmC4cOHi/Xr10uvd+7cKZRKpThx4oR0jM/Jc2RnZ4s2bdoIAOLgwYPScT4j16nzYSYpKUmMHz9eeq3X60VISIhYuXKljLWqP06ePCnOnz8vDh48aDHMxMXFiRdeeEF6nZeXJ1Qqldi1a5cQQojy8nLRvHlz8d5770llfv31VwFAnDx50i3fQ103btw4s9c//vijACC++eYbIQSfkSdIS0sTd+7ckV7rdDoBQGzbtk06xufkOZKSksT7779fJczwGblOne9m2r9/P3r37i29ViqV6NWrF7788ksZa1V/xMTEICoqyuK5W7du4dixY2bPR6PRoEOHDtLzOXHiBK5fv25WpnPnzmjcuDGfoZNs3rzZ7LWfnx8AY/cgn5Fn6NWrF1Qq4+4zd+7cwdKlS9GlSxcMHToUAP9f8iS7du1CgwYNMGLECLPjfEauVafDTG5uLvLz8xEaGmp2PDQ0tMqYAHI/0zOw9nwslVEoFAgJCeEzdJFvv/0WYWFh6N+/P5+Rh5kxYwaaN2+O/fv3Y9++fQgICADA/5c8RVFREf7f//t/ePvtt6uc4zNyrTodZoqLiwGgygqLvr6+0jmSjy3Ph8/QvUpLS7F06VKsWLECDRo04DPyMO+++y5yc3MxZMgQ9O/fHzk5OQD4/5Kn+Pvf/46//OUvaNmyZZVzfEauVafDjL+/PwDjP9AVlZaWSudIPrY8Hz5D93ryyScxbtw4jB07FgCfkSfy8fFBcnIyhBB46623APA5eYKffvoJ33//Pf7yl79YPM9n5Fp1Osw0bdoUGo0GV65cMTt+5coVtGvXTqZakYnpGVh7PpbKCCFw9epVPkMne+mll6BSqbBw4ULpGJ+RZygrKzN7rVQqER0djVOnTgHgc/IEu3fvRklJCQYPHgytVosJEyYAAGbNmgWtVguDwQCAz8hV6nSYAYDBgwcjLS1Nei2EwLFjx3DvvffKWCsCgODgYPTs2dPs+eh0Opw7d056Pt27d0fz5s3Nypw5cwZFRUV8hk60ZMkSZGZmYs2aNVAoFDh69CiOHj3KZ+Qh4uLiqhzLyclBWFgYAP6/5An+/ve/49ixY0hNTUVqaio2btwIAFi2bBlSU1PRu3dvPiNXknMqlTt8//33IjAwUJw9e1YIIcSGDRu4zowMqpuavXXrVhEaGiquXbsmhBDiH//4h8V1F2JiYqR1F6ZNmybuv/9+t9W9rnv//fdF165dxZEjR8SPP/4ofvzxRzFv3jyxdu1aIQSfkSdQKBRi9+7d0usNGzYIpVIpDh8+LB3jc/IsGRkZFteZ4TNyDZXcYcrV+vTpg/Xr12PixIlo1KgRlEol9u3bh8DAQLmrVi+UlZVh2LBhyMvLAwBMmDAB4eHh0nTgpKQkXLt2DcOHD4efnx+Cg4Oxa9cuKJV/NBrOnj0bhYWF6N+/Pxo0aIDo6Gh89NFHcnw7dU5BQQFmzJgBg8GAfv36mZ1bu3YtAD4jT7B8+XIsXLgQixcvhl6vh0KhwM6dOzFgwACpDJ+T55g1axa+++476b87deqEjRs38hm5kEIIIeSuBBEREZGj6vyYGSIiIqrbGGaIiIjIqzHMEBERkVdjmCEiIiKvxjBDREREXo1hhoiIiLwawwwRERF5NYYZIqrz8vLykJycLC3eSER1CxfNI6I6LzMzE23btkVGRgYiIyPlrg4RORlbZoiIiMirMcwQkccoLy/HSy+9hJiYGAwcOBC9e/fGsmXLAACFhYV44okn0K1bN8TFxeH+++9HZmam9N5jx44hISEBWq0W99xzD6ZOnYorV67g1KlTmDBhAgDj3mBarRbbt2+X4bsjIldhNxMReYyXX34ZKSkp+OqrrxAQEIDDhw9j9OjRuHnzJiZOnIi8vDzs3LkTKpUKL7/8Mnbs2IGff/4ZKpUKXbp0wZw5czB16lSUl5fj3nvvRXJyMrRaLbuZiOo4tswQkUcoKSnB22+/jRkzZiAgIAAAEB8fjxkzZuDChQv49NNP8eyzz0KlUgEA5syZg9OnT0utLNnZ2cjKygIAqFQqrFq1Ct26dZPnmyEit2KYISKPkJ6ejtu3byMqKsrs+D/+8Q/8+uuvAIDo6GjpeJMmTdCkSRP88ssvAIBFixbh9ddfR6dOnbBgwQKo1Wo0bdrUfd8AEcmGYYaIPIK1Hm9r5xQKBQDg6aefxsWLFzF9+nR8+umn6NSpE3788Uen15OIPA/DDBF5hOjoaPj5+SE9Pd3s+BtvvIGoqCgoFAqcP39eOn7z5k3cvHkTMTExAIAtW7YgJCQEzz33HE6ePImuXbvio48+AgAolX/8U2cwGFBUVOSG74iI3IVhhog8QqNGjTB79my89957UthISUnB9u3b0aVLF0yYMAFvvfUWysvLARhDTufOnfHggw8CAKZPn46rV68CMLbW6PV6dOzYEQDQtGlTKJVK3Lp1C2lpaZg8ebLbvz8ich2V3BUgIjJZsGAB9Ho9+vTpg2bNmkGj0WDjxo0AgDVr1uDZZ59Fz5490aBBA4SFhWHPnj3SgOCnnnoKo0aNQmBgIIqKihAfH4+nnnoKANC4cWPMmTMHf/7znxEQEIA333xTtu+RiJyPU7OJiIjIq7GbiYiIiLwawwwRERF5NYYZIiIi8moMM0REROTVGGaIiIjIqzHMEBERkVdjmCEiIiKvxjBDREREXo1hhoiIiLwawwwRERF5NYYZIiIi8moMM0REROTV/j8P0rS87X+7ugAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "from pymoo.visualization.pcp import PCP\n",
    "X3 = res3.X\n",
    "F3 = res3.F\n",
    "G3 = res3.G\n",
    "Z_res3 = [[d['x01']] for d in X3]\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "labels = list(res3.opt[0].X.keys())\n",
    "labels_x = ['matID'] + [f'A{i}' for i in range(1, 48)]\n",
    "bounds = np.array([problem.vars[name].bounds for name in labels]).T\n",
    "\n",
    "\n",
    "X3 = np.array([[sol.X[name] for name in labels] for sol in res3.opt])\n",
    "\n",
    "plot1 = PCP(labels=labels_x, bounds=bounds)\n",
    "plot1.set_axis_style(color=\"grey\", alpha=1)\n",
    "plot1.add(X3)\n",
    "\n",
    "plot1.show()\n",
    "plt.savefig('./figures_Integer/PCP.png',bbox_inches='tight', dpi = 200)\n",
    "\n",
    "\n",
    "# Maybe the solution is limited by the limits in areas. Example, you want to minimize the compliance but\n",
    "# you have a maximum area, so you can't reduce the compliance further\n",
    "\n",
    "upper_bounds = bounds[1, 1:]*0.999\n",
    "lower_bounds = bounds[0, 1:]*1.001\n",
    "\n",
    "\n",
    "\n",
    "# Check if each row of X is within the limits\n",
    "is_within_limits = np.logical_and(np.all(X3[:,1:] >= lower_bounds, axis=1), np.all(X3[:,1:] <= upper_bounds, axis=1))\n",
    "\n",
    "# Print the results\n",
    "if np.all(is_within_limits):\n",
    "    print(\"Solution not limited by the areas\")\n",
    "else:\n",
    "    print(\"Solution limited by the areas\")\n",
    "\n",
    "\n",
    "\n",
    "    \n",
    "\n",
    "names = []\n",
    "types = []\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "legend_dict = {}\n",
    "material_name_dict = {}  # Dictionary to map material types to material names\n",
    "\n",
    "for xData in Z_res3:\n",
    "    matname = dataIdentifier['name'][int(xData[0])]\n",
    "    mattype = dataIdentifier['className'][int(xData[0])]\n",
    "    names.append(matname)\n",
    "    types.append(mattype)\n",
    "    material_name_dict[mattype] = matname  # Populate the material name dictionary\n",
    "\n",
    "unique_labels = list(set(types))\n",
    "\n",
    "# Define specific colors for each material type\n",
    "mat_colors = {\n",
    "    'Steel': 'slategrey',\n",
    "    'Aluminium Alloys': 'violet',\n",
    "    'Plastics': 'lawngreen',\n",
    "    'Titanium Alloys': 'indigo',\n",
    "    'Copper Alloys': 'chocolate',\n",
    "    'Composites': 'gold',\n",
    "    # Add more material types and corresponding colors as needed\n",
    "}\n",
    "\n",
    "for i, mattype in enumerate(types):\n",
    "    if mattype not in mat_colors:\n",
    "        mat_colors[mattype] = plt.cm.get_cmap('jet')(i / len(set(types)))\n",
    "\n",
    "# add scatter plot for each unique label\n",
    "for i, (x, y) in enumerate(F3):\n",
    "    material = names[i]\n",
    "    mattype = types[i]\n",
    "    color = mat_colors[mattype]\n",
    "    label = material_name_dict[mattype]  # Use material name as the label\n",
    "    ax.scatter(x, y, color=color, label=label)\n",
    "    if mattype not in legend_dict:\n",
    "        legend_dict[mattype] = ax.scatter(x, y, color=color, label=label)\n",
    "\n",
    "# set legend colors and remove duplicates\n",
    "handles, labels = [], []\n",
    "for label in legend_dict:\n",
    "    handles.append(legend_dict[label])\n",
    "    labels.append(material_name_dict[label])  # Use material name as the label\n",
    "    legend_dict[label].set_color(mat_colors[label])\n",
    "\n",
    "ax.legend(handles, labels, loc=\"upper right\")\n",
    "\n",
    "# show plot\n",
    "plt.title(\"Objective Space\")\n",
    "entry_order = ['cost', 'mass', 'co2', 'water', 'energy', 'compliance']\n",
    "enabled_entries = [entry for entry in entry_order if objectives[entry]['isOn']]\n",
    "ax.set_xlabel(enabled_entries[0])\n",
    "ax.set_ylabel(enabled_entries[1])\n",
    "plt.savefig('./figures_Integer/Integer_compliance_mass.png', bbox_inches='tight', dpi=200)\n",
    "plt.show()\n",
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18e911a8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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