SessileDrop_WithBasilisk.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# \"A\" sessile drop sitting on a superhydrophobic surface\n",
    "\n",
    "<img src=\"Schematic.png\" \n",
    "        alt=\"Picture\" \n",
    "        width=\"600\" \n",
    "        style=\"display: block; margin: 0 auto\" />\n",
    "\n",
    "Laplace equaiton for this problem gives a boundary value problem (see figure) where the two boundaries are the surface of the drop and the surface of the substrate. However, both boundaries are not known apriori. Therefore, we will solve the problem using the initial value problem (IVP) formulation.\n",
    "\n",
    "The set of ODE that we need to solve is the following:\n",
    "\n",
    "$$ \\frac{d\\phi}{ds} + \\frac{\\sin\\phi}{r} = \\kappa_T + Bo z $$\n",
    "\n",
    "where $r-z$ is the cylindrical coordinate system as shown in the figure. We have parameterized the equation for curvature using the length of arc $s$ and the tangent angle $\\phi$. See page 15-16 of [deserno2004notes](https://www.cmu.edu/biolphys/deserno/pdf/diff_geom.pdf) for more details. Consequently, two more ODEs are needed to solve the problem:\n",
    "\n",
    "$$ \\frac{dr}{ds} = \\cos\\phi $$\n",
    "$$ \\frac{dz}{ds} = \\sin\\phi $$\n",
    "\n",
    "### Initial conditions\n",
    "\n",
    "$$ \\phi(s = 0) = 0 $$\n",
    "$$ r(s = 0) = 0 $$ \n",
    "\n",
    "**Note:** Need to initialize with a very small (finite) valuen of $r(s = 0)$ to avoid division by zero.\n",
    "\n",
    "$$ z(s = 0) = 0 $$\n",
    "\n",
    "### References\n",
    "``` bib\n",
    "@misc{deserno2004notes,\n",
    "  title={Notes on differential geometry},\n",
    "  author={Deserno, M.},\n",
    "  year={2004},\n",
    "  publisher={Dover, New York. https://www.cmu.edu/biolphys/deserno/pdf/diff_geom.pdf}\n",
    "}\n",
    "```\n",
    "\n",
    "*Note* Initial guess of $\\kappa_T$: The initial guess for the curvature at the apex of the drop is taken from the database: [NormalizeBond.csv](NormalizeBond.csv). If such a file is absent, $\\kappa_T = 2$ is taken as the initial guess. "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Essential imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import *\n",
    "from scipy.integrate import solve_ivp\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.collections import LineCollection\n",
    "import os\n",
    "import pandas as pd\n",
    "import sys\n",
    "\n",
    "mpl.rcParams['text.usetex'] = True\n",
    "mpl.rcParams['font.family'] = 'serif'\n",
    "\n",
    "AxesLabel, TickLabel = [30, 30]\n",
    "plt.rcParams.update({\n",
    "    'font.size' : TickLabel,                   # Set font size to 11pt\n",
    "    'axes.labelsize': AxesLabel,               # -> axis labels\n",
    "    'legend.fontsize': AxesLabel,              # -> legends\n",
    "    'xtick.labelsize': TickLabel,              # -> x-axis tick labels\n",
    "    'ytick.labelsize': TickLabel,              # -> y-axis tick labels\n",
    "})\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Essential functions"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Laplace equation for a sessile drop\n",
    "def LaplaceEqn(t, y, Bo, KappaT):\n",
    "    Phi = y[0]\n",
    "    r = y[1]\n",
    "    z = y[2]\n",
    "\n",
    "    f0 = Bo*z + KappaT - sin(Phi)/r\n",
    "    f1 = cos(Phi)\n",
    "    f2 = sin(Phi)\n",
    "\n",
    "    return array([f0, f1, f2])\n",
    "\n",
    "# stop integration when Phi = pi\n",
    "def event(t, y, Bo, KappaT):\n",
    "    return y[0] - 1.001*pi\n",
    "\n",
    "# calculate the volume of the drop given by (R, Z)\n",
    "def volume(R, Z):\n",
    "    return -pi*trapz(R**2, Z)\n",
    "\n",
    "# calculate the volume of the drop given by (R, Z)\n",
    "def surface(R, Z, S):\n",
    "    return 2*pi*trapz(R, S)\n",
    "\n",
    "# calculate the center of mass of the drop given by (R, Z)\n",
    "def centerOfMass(R, Z):\n",
    "    return trapz((R**2)*Z, Z)/trapz(R**2, Z)\n",
    "\n",
    "# main funtion to get the drop shape\n",
    "def getDrop(Bo, KappaT):\n",
    "  # Initial conditions\n",
    "  Phi0, r0, z0 = 0.0, 1e-50, 0.0\n",
    "  y0 = array([Phi0, r0, z0])\n",
    "  y0.reshape(3,)\n",
    "\n",
    "  # parameterizatio is done using the arc length s\n",
    "  s0, sMax, ds = 0.0, 5*pi, 1e-6\n",
    "  \n",
    "  event.terminal = True\n",
    "  return solve_ivp(LaplaceEqn, [s0, sMax], y0, args=(Bo, KappaT), t_eval=arange(s0, sMax, ds), events=event, rtol=1e-10, atol=1e-16)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gradient descent algorithm to get the drop profile!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def CorrectDrop(Bo, CountMax, lr, KappaT):\n",
    "      Error, VolError = [], 1.0\n",
    "      count = 0\n",
    "      while (abs(VolError) > 1.0e-10 and count < CountMax):\n",
    "        print('------------------------------------')\n",
    "        count += 1\n",
    "        sol = getDrop(Bo, KappaT)\n",
    "        S, Phi, r, z = sol.t, sol.y[0], sol.y[1], sol.y[2]\n",
    "        # coordinate transformation to have drop straight up\n",
    "        Z = -z+z[-1]\n",
    "        R = r\n",
    "        # join a straight line from the last point to the origin\n",
    "        Z = append(Z, 0.0)\n",
    "        R = append(R, 0.0)\n",
    "        S = append(S, S[-1]+r[-1])\n",
    "        r = append(r, 0.0)\n",
    "        z = append(z, z[-1])\n",
    "        Phi = append(Phi, pi)\n",
    "\n",
    "        Vol = volume(R, Z)\n",
    "        VolError = Vol - (4.0/3.0)*pi\n",
    "        print('Volume = %4.3e and VolError = %4.3e' % (Vol, VolError))\n",
    "\n",
    "        # use gradient descent to find the updated KappaT\n",
    "        if KappaT < 1:\n",
    "          KappaT = KappaT*(1.0 + lr*VolError)\n",
    "        else:\n",
    "          KappaT = KappaT + lr*VolError\n",
    "        \n",
    "        print('Done: Iteration = %d, Next KappaT = %5.4e' % (count, KappaT))\n",
    "        Error.append(VolError)\n",
    "        KappaTNew = KappaT\n",
    "\n",
    "      print('------------------------------------')\n",
    "\n",
    "      # if the volume did not converge, stop the code\n",
    "      if abs(VolError) > 1.0e-6:\n",
    "          print('Volume did not converge after %d iterations for Bond = %.15e. Stopping code. VolError = %4.3e' % (count, Bo, VolError))\n",
    "          sys.exit(1)\n",
    "      \n",
    "      return R, Z, S, Phi, r, z, KappaTNew, Error"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Function to run Basilisk to check the initial condition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gettingFacets(L0, InitConditionFile):\n",
    "    import subprocess as sp\n",
    "    exe = [\"./InitialCondition\", str(L0), InitConditionFile]\n",
    "    p = sp.Popen(exe, stdout=sp.PIPE, stderr=sp.PIPE)\n",
    "    stdout, stderr = p.communicate()\n",
    "    temp1 = stderr.decode(\"utf-8\")\n",
    "    temp2 = temp1.split(\"\\n\")\n",
    "    segs = []\n",
    "    skip = False\n",
    "    if (len(temp2) > 1e2):\n",
    "        for n1 in range(len(temp2)):\n",
    "            temp3 = temp2[n1].split(\" \")\n",
    "            if temp3 == ['']:\n",
    "                skip = False\n",
    "                pass\n",
    "            else:\n",
    "                if not skip:\n",
    "                    temp4 = temp2[n1+1].split(\" \")\n",
    "                    r1, z1 = array([float(temp3[1]), float(temp3[0])])\n",
    "                    r2, z2 = array([float(temp4[1]), float(temp4[0])])\n",
    "                    segs.append(((r1, z1),(r2,z2)))\n",
    "                    skip = True\n",
    "    return segs"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Plotting(R, Z, S, Phi, r, z, filename, Bo, KappaT, Zcm, InterfaceBas, TestWithBasilisk):\n",
    "    S = S/pi\n",
    "\n",
    "    fig, AX = plt.subplots(2, 2)\n",
    "    fig.patch.set_facecolor('white')\n",
    "    fig.set_size_inches(20, 15)\n",
    "    ax1, ax2, ax3, ax4 = AX.flatten()\n",
    "\n",
    "    \n",
    "    ax1.plot(R, Z, 'r-', linewidth=4.0)\n",
    "    ax1.plot(-R, Z, 'r-', linewidth=4.0)\n",
    "    if TestWithBasilisk:\n",
    "        line_segments = LineCollection(InterfaceBas, linewidths=4, colors='#1a9641', linestyle='solid')\n",
    "        ax1.add_collection(line_segments)\n",
    "\n",
    "    ax1.plot(0, Zcm, 'bo', markersize=15.0)\n",
    "    ax1.set_xlabel(r'$\\mathcal{R}/R_0$')\n",
    "    ax1.set_ylabel(r'$\\mathcal{Z}/R_0$')\n",
    "    if Bo<125:\n",
    "        ax1.set_aspect('equal')\n",
    "    else:\n",
    "        ax1.set_box_aspect(1)\n",
    "    ax1.set_xlim(-1.1*R.max(), 1.1*R.max())\n",
    "    ax1.set_ylim(0.0, 1.05*Z.max())\n",
    "\n",
    "    ax2.plot(S, Phi/pi, 'b-', linewidth=4.0)\n",
    "    ax2.set_xlabel(r'$s/\\left(\\pi R_0\\right)$')\n",
    "    ax2.set_ylabel(r'$\\phi/\\pi$')\n",
    "    ax2.set_box_aspect(1)\n",
    "    ax2.set_xlim(0.0, S.max())\n",
    "    ax2.set_ylim(0.0, 1.05)\n",
    "\n",
    "    ax3.plot(S, r, 'k-')\n",
    "    ax3.set_xlabel(r'$s/\\left(\\pi R_0\\right)$')\n",
    "    ax3.set_ylabel(r'$r/R_0$')\n",
    "    ax3.set_box_aspect(1)\n",
    "    ax3.set_xlim(0.0, S.max())\n",
    "    ax3.set_ylim(0.0, 1.05*r.max())\n",
    "\n",
    "    ax4.plot(S, z, 'k-')\n",
    "    ax4.set_xlabel(r'$s/\\left(\\pi R_0\\right)$')\n",
    "    ax4.set_ylabel(r'$z/R_0$')\n",
    "    ax4.set_box_aspect(1)\n",
    "    ax4.set_xlim(0.0, S.max())\n",
    "    ax4.set_ylim(0.0, 1.05*z.max())\n",
    "    # set figure title\n",
    "    l1, b1, w1, h1 = ax1.get_position().bounds\n",
    "    l2, b2, w2, h2 = ax2.get_position().bounds\n",
    "\n",
    "    L = max(b1+h1, b2+h2)\n",
    "    # set title position\n",
    "    fig.text(0.5, L+0.025, r'$Bo = %5.4e$, $\\kappa_TR_0 = %5.4e$' % (Bo, KappaT), fontsize=AxesLabel, ha='center')\n",
    "\n",
    "    plt.savefig(filename, bbox_inches='tight')\n",
    "    plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Main code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  2.0006880225931503\n",
      "------------------------------------\n",
      "Volume = 4.180e+00 and VolError = -8.496e-03\n",
      "Done: Iteration = 1, Next KappaT = 1.9986e+00\n",
      "------------------------------------\n",
      "Volume = 4.194e+00 and VolError = 4.837e-03\n",
      "Done: Iteration = 2, Next KappaT = 1.9998e+00\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -2.761e-03\n",
      "Done: Iteration = 3, Next KappaT = 1.9991e+00\n",
      "------------------------------------\n",
      "Volume = 4.190e+00 and VolError = 1.574e-03\n",
      "Done: Iteration = 4, Next KappaT = 1.9995e+00\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -8.977e-04\n",
      "Done: Iteration = 5, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.119e-04\n",
      "Done: Iteration = 6, Next KappaT = 1.9994e+00\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -2.919e-04\n",
      "Done: Iteration = 7, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.665e-04\n",
      "Done: Iteration = 8, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.494e-05\n",
      "Done: Iteration = 9, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.414e-05\n",
      "Done: Iteration = 10, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.087e-05\n",
      "Done: Iteration = 11, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.761e-05\n",
      "Done: Iteration = 12, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.004e-05\n",
      "Done: Iteration = 13, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.726e-06\n",
      "Done: Iteration = 14, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.265e-06\n",
      "Done: Iteration = 15, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.862e-06\n",
      "Done: Iteration = 16, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.062e-06\n",
      "Done: Iteration = 17, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 6.056e-07\n",
      "Done: Iteration = 18, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.454e-07\n",
      "Done: Iteration = 19, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.969e-07\n",
      "Done: Iteration = 20, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.123e-07\n",
      "Done: Iteration = 21, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 6.405e-08\n",
      "Done: Iteration = 22, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.653e-08\n",
      "Done: Iteration = 23, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.083e-08\n",
      "Done: Iteration = 24, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.188e-08\n",
      "Done: Iteration = 25, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 6.774e-09\n",
      "Done: Iteration = 26, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.863e-09\n",
      "Done: Iteration = 27, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.203e-09\n",
      "Done: Iteration = 28, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.256e-09\n",
      "Done: Iteration = 29, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 7.165e-10\n",
      "Done: Iteration = 30, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.086e-10\n",
      "Done: Iteration = 31, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.330e-10\n",
      "Done: Iteration = 32, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.329e-10\n",
      "Done: Iteration = 33, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 7.578e-11\n",
      "Done: Iteration = 34, Next KappaT = 1.9993e+00\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 3.1411e+00\n",
      "Surface Area = 1.2566e+01\n",
      "KappaT = 1.9993e+00, Bo = 1.0000e-03, H = 1.997, Zcm = 0.997, W = 1.000, Rw = 0.024\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e-03\n",
      "Done with Basilisk for Bo = 1.0000e-03\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  1.9947031285889003\n",
      "------------------------------------\n",
      "Volume = 4.180e+00 and VolError = -8.430e-03\n",
      "Done: Iteration = 1, Next KappaT = 1.9926e+00\n",
      "------------------------------------\n",
      "Volume = 4.194e+00 and VolError = 4.760e-03\n",
      "Done: Iteration = 2, Next KappaT = 1.9938e+00\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -2.695e-03\n",
      "Done: Iteration = 3, Next KappaT = 1.9931e+00\n",
      "------------------------------------\n",
      "Volume = 4.190e+00 and VolError = 1.524e-03\n",
      "Done: Iteration = 4, Next KappaT = 1.9935e+00\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -8.621e-04\n",
      "Done: Iteration = 5, Next KappaT = 1.9933e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.875e-04\n",
      "Done: Iteration = 6, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.758e-04\n",
      "Done: Iteration = 7, Next KappaT = 1.9933e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.560e-04\n",
      "Done: Iteration = 8, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.823e-05\n",
      "Done: Iteration = 9, Next KappaT = 1.9933e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.991e-05\n",
      "Done: Iteration = 10, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.823e-05\n",
      "Done: Iteration = 11, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.597e-05\n",
      "Done: Iteration = 12, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.031e-06\n",
      "Done: Iteration = 13, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.108e-06\n",
      "Done: Iteration = 14, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.889e-06\n",
      "Done: Iteration = 15, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.634e-06\n",
      "Done: Iteration = 16, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.245e-07\n",
      "Done: Iteration = 17, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.229e-07\n",
      "Done: Iteration = 18, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.958e-07\n",
      "Done: Iteration = 19, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.673e-07\n",
      "Done: Iteration = 20, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.464e-08\n",
      "Done: Iteration = 21, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.353e-08\n",
      "Done: Iteration = 22, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.028e-08\n",
      "Done: Iteration = 23, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.713e-08\n",
      "Done: Iteration = 24, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.689e-09\n",
      "Done: Iteration = 25, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.481e-09\n",
      "Done: Iteration = 26, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.100e-09\n",
      "Done: Iteration = 27, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.754e-09\n",
      "Done: Iteration = 28, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.919e-10\n",
      "Done: Iteration = 29, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.611e-10\n",
      "Done: Iteration = 30, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.174e-10\n",
      "Done: Iteration = 31, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.795e-10\n",
      "Done: Iteration = 32, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.016e-10\n",
      "Done: Iteration = 33, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.745e-11\n",
      "Done: Iteration = 34, Next KappaT = 1.9934e+00\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 3.1371e+00\n",
      "Surface Area = 1.2567e+01\n",
      "KappaT = 1.9934e+00, Bo = 1.0000e-02, H = 1.979, Zcm = 0.982, W = 1.002, Rw = 0.080\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e-02\n",
      "Done with Basilisk for Bo = 1.0000e-02\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  1.937283687145742\n",
      "------------------------------------\n",
      "Volume = 4.177e+00 and VolError = -1.176e-02\n",
      "Done: Iteration = 1, Next KappaT = 1.9343e+00\n",
      "------------------------------------\n",
      "Volume = 4.195e+00 and VolError = 6.149e-03\n",
      "Done: Iteration = 2, Next KappaT = 1.9359e+00\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -3.229e-03\n",
      "Done: Iteration = 3, Next KappaT = 1.9351e+00\n",
      "------------------------------------\n",
      "Volume = 4.190e+00 and VolError = 1.692e-03\n",
      "Done: Iteration = 4, Next KappaT = 1.9355e+00\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -8.875e-04\n",
      "Done: Iteration = 5, Next KappaT = 1.9353e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.653e-04\n",
      "Done: Iteration = 6, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.440e-04\n",
      "Done: Iteration = 7, Next KappaT = 1.9353e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.279e-04\n",
      "Done: Iteration = 8, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.709e-05\n",
      "Done: Iteration = 9, Next KappaT = 1.9353e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 3.518e-05\n",
      "Done: Iteration = 10, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.845e-05\n",
      "Done: Iteration = 11, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 9.673e-06\n",
      "Done: Iteration = 12, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.072e-06\n",
      "Done: Iteration = 13, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.659e-06\n",
      "Done: Iteration = 14, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.394e-06\n",
      "Done: Iteration = 15, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 7.308e-07\n",
      "Done: Iteration = 16, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.828e-07\n",
      "Done: Iteration = 17, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.008e-07\n",
      "Done: Iteration = 18, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.053e-07\n",
      "Done: Iteration = 19, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.525e-08\n",
      "Done: Iteration = 20, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.898e-08\n",
      "Done: Iteration = 21, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.520e-08\n",
      "Done: Iteration = 22, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.974e-09\n",
      "Done: Iteration = 23, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.183e-09\n",
      "Done: Iteration = 24, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.194e-09\n",
      "Done: Iteration = 25, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.151e-09\n",
      "Done: Iteration = 26, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.038e-10\n",
      "Done: Iteration = 27, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 3.167e-10\n",
      "Done: Iteration = 28, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.661e-10\n",
      "Done: Iteration = 29, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 8.715e-11\n",
      "Done: Iteration = 30, Next KappaT = 1.9354e+00\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 3.1097e+00\n",
      "Surface Area = 1.2585e+01\n",
      "KappaT = 1.9354e+00, Bo = 1.0000e-01, H = 1.869, Zcm = 0.895, W = 1.016, Rw = 0.249\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e-01\n",
      "Done with Basilisk for Bo = 1.0000e-01\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  1.4738400842449897\n",
      "------------------------------------\n",
      "Volume = 4.171e+00 and VolError = -1.779e-02\n",
      "Done: Iteration = 1, Next KappaT = 1.4694e+00\n",
      "------------------------------------\n",
      "Volume = 4.195e+00 and VolError = 6.116e-03\n",
      "Done: Iteration = 2, Next KappaT = 1.4709e+00\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -2.122e-03\n",
      "Done: Iteration = 3, Next KappaT = 1.4704e+00\n",
      "------------------------------------\n",
      "Volume = 4.190e+00 and VolError = 7.340e-04\n",
      "Done: Iteration = 4, Next KappaT = 1.4706e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.542e-04\n",
      "Done: Iteration = 5, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 8.798e-05\n",
      "Done: Iteration = 6, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.045e-05\n",
      "Done: Iteration = 7, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.054e-05\n",
      "Done: Iteration = 8, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.650e-06\n",
      "Done: Iteration = 9, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.262e-06\n",
      "Done: Iteration = 10, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.336e-07\n",
      "Done: Iteration = 11, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.460e-07\n",
      "Done: Iteration = 12, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.067e-08\n",
      "Done: Iteration = 13, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.759e-08\n",
      "Done: Iteration = 14, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.098e-09\n",
      "Done: Iteration = 15, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.110e-09\n",
      "Done: Iteration = 16, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.336e-10\n",
      "Done: Iteration = 17, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.591e-10\n",
      "Done: Iteration = 18, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.660e-11\n",
      "Done: Iteration = 19, Next KappaT = 1.4705e+00\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 3.0493e+00\n",
      "Surface Area = 1.3078e+01\n",
      "KappaT = 1.4705e+00, Bo = 1.0000e+00, H = 1.447, Zcm = 0.627, W = 1.124, Rw = 0.675\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e+00\n",
      "Done with Basilisk for Bo = 1.0000e+00\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  0.1232047737479391\n",
      "------------------------------------\n",
      "Volume = 4.196e+00 and VolError = 7.323e-03\n",
      "Done: Iteration = 1, Next KappaT = 1.2343e-01\n",
      "------------------------------------\n",
      "Volume = 4.192e+00 and VolError = 3.691e-03\n",
      "Done: Iteration = 2, Next KappaT = 1.2354e-01\n",
      "------------------------------------\n",
      "Volume = 4.191e+00 and VolError = 1.860e-03\n",
      "Done: Iteration = 3, Next KappaT = 1.2360e-01\n",
      "------------------------------------\n",
      "Volume = 4.190e+00 and VolError = 9.371e-04\n",
      "Done: Iteration = 4, Next KappaT = 1.2363e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.722e-04\n",
      "Done: Iteration = 5, Next KappaT = 1.2365e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.379e-04\n",
      "Done: Iteration = 6, Next KappaT = 1.2365e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.199e-04\n",
      "Done: Iteration = 7, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 6.041e-05\n",
      "Done: Iteration = 8, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 3.043e-05\n",
      "Done: Iteration = 9, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.532e-05\n",
      "Done: Iteration = 10, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 7.734e-06\n",
      "Done: Iteration = 11, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 3.884e-06\n",
      "Done: Iteration = 12, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.970e-06\n",
      "Done: Iteration = 13, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 9.892e-07\n",
      "Done: Iteration = 14, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.968e-07\n",
      "Done: Iteration = 15, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.495e-07\n",
      "Done: Iteration = 16, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.253e-07\n",
      "Done: Iteration = 17, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 6.291e-08\n",
      "Done: Iteration = 18, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 3.160e-08\n",
      "Done: Iteration = 19, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.587e-08\n",
      "Done: Iteration = 20, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 7.968e-09\n",
      "Done: Iteration = 21, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 4.002e-09\n",
      "Done: Iteration = 22, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.009e-09\n",
      "Done: Iteration = 23, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.009e-09\n",
      "Done: Iteration = 24, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 5.075e-10\n",
      "Done: Iteration = 25, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 2.545e-10\n",
      "Done: Iteration = 26, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 1.275e-10\n",
      "Done: Iteration = 27, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = 6.379e-11\n",
      "Done: Iteration = 28, Next KappaT = 1.2366e-01\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 3.4458e+00\n",
      "Surface Area = 1.8377e+01\n",
      "KappaT = 1.2366e-01, Bo = 1.0000e+01, H = 0.666, Zcm = 0.290, W = 1.567, Rw = 1.401\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e+01\n",
      "Done with Basilisk for Bo = 1.0000e+01\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  1.0357494187207507e-09\n",
      "------------------------------------\n",
      "Volume = 3.957e+00 and VolError = -2.322e-01\n",
      "Done: Iteration = 1, Next KappaT = 9.7562e-10\n",
      "------------------------------------\n",
      "Volume = 3.976e+00 and VolError = -2.130e-01\n",
      "Done: Iteration = 2, Next KappaT = 9.2367e-10\n",
      "------------------------------------\n",
      "Volume = 3.993e+00 and VolError = -1.953e-01\n",
      "Done: Iteration = 3, Next KappaT = 8.7857e-10\n",
      "------------------------------------\n",
      "Volume = 4.010e+00 and VolError = -1.791e-01\n",
      "Done: Iteration = 4, Next KappaT = 8.3923e-10\n",
      "------------------------------------\n",
      "Volume = 4.024e+00 and VolError = -1.643e-01\n",
      "Done: Iteration = 5, Next KappaT = 8.0476e-10\n",
      "------------------------------------\n",
      "Volume = 4.038e+00 and VolError = -1.507e-01\n",
      "Done: Iteration = 6, Next KappaT = 7.7444e-10\n",
      "------------------------------------\n",
      "Volume = 4.051e+00 and VolError = -1.382e-01\n",
      "Done: Iteration = 7, Next KappaT = 7.4768e-10\n",
      "------------------------------------\n",
      "Volume = 4.062e+00 and VolError = -1.268e-01\n",
      "Done: Iteration = 8, Next KappaT = 7.2399e-10\n",
      "------------------------------------\n",
      "Volume = 4.073e+00 and VolError = -1.163e-01\n",
      "Done: Iteration = 9, Next KappaT = 7.0294e-10\n",
      "------------------------------------\n",
      "Volume = 4.082e+00 and VolError = -1.066e-01\n",
      "Done: Iteration = 10, Next KappaT = 6.8420e-10\n",
      "------------------------------------\n",
      "Volume = 4.091e+00 and VolError = -9.782e-02\n",
      "Done: Iteration = 11, Next KappaT = 6.6747e-10\n",
      "------------------------------------\n",
      "Volume = 4.099e+00 and VolError = -8.972e-02\n",
      "Done: Iteration = 12, Next KappaT = 6.5250e-10\n",
      "------------------------------------\n",
      "Volume = 4.106e+00 and VolError = -8.230e-02\n",
      "Done: Iteration = 13, Next KappaT = 6.3907e-10\n",
      "------------------------------------\n",
      "Volume = 4.113e+00 and VolError = -7.549e-02\n",
      "Done: Iteration = 14, Next KappaT = 6.2701e-10\n",
      "------------------------------------\n",
      "Volume = 4.120e+00 and VolError = -6.925e-02\n",
      "Done: Iteration = 15, Next KappaT = 6.1616e-10\n",
      "------------------------------------\n",
      "Volume = 4.125e+00 and VolError = -6.352e-02\n",
      "Done: Iteration = 16, Next KappaT = 6.0637e-10\n",
      "------------------------------------\n",
      "Volume = 4.131e+00 and VolError = -5.826e-02\n",
      "Done: Iteration = 17, Next KappaT = 5.9754e-10\n",
      "------------------------------------\n",
      "Volume = 4.135e+00 and VolError = -5.344e-02\n",
      "Done: Iteration = 18, Next KappaT = 5.8956e-10\n",
      "------------------------------------\n",
      "Volume = 4.140e+00 and VolError = -4.902e-02\n",
      "Done: Iteration = 19, Next KappaT = 5.8233e-10\n",
      "------------------------------------\n",
      "Volume = 4.144e+00 and VolError = -4.497e-02\n",
      "Done: Iteration = 20, Next KappaT = 5.7578e-10\n",
      "------------------------------------\n",
      "Volume = 4.148e+00 and VolError = -4.125e-02\n",
      "Done: Iteration = 21, Next KappaT = 5.6985e-10\n",
      "------------------------------------\n",
      "Volume = 4.151e+00 and VolError = -3.784e-02\n",
      "Done: Iteration = 22, Next KappaT = 5.6446e-10\n",
      "------------------------------------\n",
      "Volume = 4.154e+00 and VolError = -3.471e-02\n",
      "Done: Iteration = 23, Next KappaT = 5.5956e-10\n",
      "------------------------------------\n",
      "Volume = 4.157e+00 and VolError = -3.184e-02\n",
      "Done: Iteration = 24, Next KappaT = 5.5510e-10\n",
      "------------------------------------\n",
      "Volume = 4.160e+00 and VolError = -2.921e-02\n",
      "Done: Iteration = 25, Next KappaT = 5.5105e-10\n",
      "------------------------------------\n",
      "Volume = 4.162e+00 and VolError = -2.679e-02\n",
      "Done: Iteration = 26, Next KappaT = 5.4736e-10\n",
      "------------------------------------\n",
      "Volume = 4.164e+00 and VolError = -2.458e-02\n",
      "Done: Iteration = 27, Next KappaT = 5.4400e-10\n",
      "------------------------------------\n",
      "Volume = 4.166e+00 and VolError = -2.254e-02\n",
      "Done: Iteration = 28, Next KappaT = 5.4093e-10\n",
      "------------------------------------\n",
      "Volume = 4.168e+00 and VolError = -2.068e-02\n",
      "Done: Iteration = 29, Next KappaT = 5.3813e-10\n",
      "------------------------------------\n",
      "Volume = 4.170e+00 and VolError = -1.897e-02\n",
      "Done: Iteration = 30, Next KappaT = 5.3558e-10\n",
      "------------------------------------\n",
      "Volume = 4.171e+00 and VolError = -1.740e-02\n",
      "Done: Iteration = 31, Next KappaT = 5.3325e-10\n",
      "------------------------------------\n",
      "Volume = 4.173e+00 and VolError = -1.596e-02\n",
      "Done: Iteration = 32, Next KappaT = 5.3112e-10\n",
      "------------------------------------\n",
      "Volume = 4.174e+00 and VolError = -1.464e-02\n",
      "Done: Iteration = 33, Next KappaT = 5.2918e-10\n",
      "------------------------------------\n",
      "Volume = 4.175e+00 and VolError = -1.343e-02\n",
      "Done: Iteration = 34, Next KappaT = 5.2740e-10\n",
      "------------------------------------\n",
      "Volume = 4.176e+00 and VolError = -1.232e-02\n",
      "Done: Iteration = 35, Next KappaT = 5.2578e-10\n",
      "------------------------------------\n",
      "Volume = 4.177e+00 and VolError = -1.130e-02\n",
      "Done: Iteration = 36, Next KappaT = 5.2429e-10\n",
      "------------------------------------\n",
      "Volume = 4.178e+00 and VolError = -1.037e-02\n",
      "Done: Iteration = 37, Next KappaT = 5.2293e-10\n",
      "------------------------------------\n",
      "Volume = 4.179e+00 and VolError = -9.513e-03\n",
      "Done: Iteration = 38, Next KappaT = 5.2169e-10\n",
      "------------------------------------\n",
      "Volume = 4.180e+00 and VolError = -8.726e-03\n",
      "Done: Iteration = 39, Next KappaT = 5.2055e-10\n",
      "------------------------------------\n",
      "Volume = 4.181e+00 and VolError = -8.005e-03\n",
      "Done: Iteration = 40, Next KappaT = 5.1951e-10\n",
      "------------------------------------\n",
      "Volume = 4.181e+00 and VolError = -7.343e-03\n",
      "Done: Iteration = 41, Next KappaT = 5.1855e-10\n",
      "------------------------------------\n",
      "Volume = 4.182e+00 and VolError = -6.736e-03\n",
      "Done: Iteration = 42, Next KappaT = 5.1768e-10\n",
      "------------------------------------\n",
      "Volume = 4.183e+00 and VolError = -6.179e-03\n",
      "Done: Iteration = 43, Next KappaT = 5.1688e-10\n",
      "------------------------------------\n",
      "Volume = 4.183e+00 and VolError = -5.669e-03\n",
      "Done: Iteration = 44, Next KappaT = 5.1615e-10\n",
      "------------------------------------\n",
      "Volume = 4.184e+00 and VolError = -5.200e-03\n",
      "Done: Iteration = 45, Next KappaT = 5.1548e-10\n",
      "------------------------------------\n",
      "Volume = 4.184e+00 and VolError = -4.770e-03\n",
      "Done: Iteration = 46, Next KappaT = 5.1486e-10\n",
      "------------------------------------\n",
      "Volume = 4.184e+00 and VolError = -4.376e-03\n",
      "Done: Iteration = 47, Next KappaT = 5.1430e-10\n",
      "------------------------------------\n",
      "Volume = 4.185e+00 and VolError = -4.014e-03\n",
      "Done: Iteration = 48, Next KappaT = 5.1378e-10\n",
      "------------------------------------\n",
      "Volume = 4.185e+00 and VolError = -3.682e-03\n",
      "Done: Iteration = 49, Next KappaT = 5.1331e-10\n",
      "------------------------------------\n",
      "Volume = 4.185e+00 and VolError = -3.378e-03\n",
      "Done: Iteration = 50, Next KappaT = 5.1288e-10\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -3.099e-03\n",
      "Done: Iteration = 51, Next KappaT = 5.1248e-10\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -2.843e-03\n",
      "Done: Iteration = 52, Next KappaT = 5.1211e-10\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -2.608e-03\n",
      "Done: Iteration = 53, Next KappaT = 5.1178e-10\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -2.392e-03\n",
      "Done: Iteration = 54, Next KappaT = 5.1147e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -2.194e-03\n",
      "Done: Iteration = 55, Next KappaT = 5.1119e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -2.013e-03\n",
      "Done: Iteration = 56, Next KappaT = 5.1094e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.847e-03\n",
      "Done: Iteration = 57, Next KappaT = 5.1070e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.694e-03\n",
      "Done: Iteration = 58, Next KappaT = 5.1048e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.554e-03\n",
      "Done: Iteration = 59, Next KappaT = 5.1029e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.426e-03\n",
      "Done: Iteration = 60, Next KappaT = 5.1010e-10\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.308e-03\n",
      "Done: Iteration = 61, Next KappaT = 5.0994e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -1.200e-03\n",
      "Done: Iteration = 62, Next KappaT = 5.0979e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -1.100e-03\n",
      "Done: Iteration = 63, Next KappaT = 5.0964e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -1.010e-03\n",
      "Done: Iteration = 64, Next KappaT = 5.0952e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -9.261e-04\n",
      "Done: Iteration = 65, Next KappaT = 5.0940e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -8.496e-04\n",
      "Done: Iteration = 66, Next KappaT = 5.0929e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -7.793e-04\n",
      "Done: Iteration = 67, Next KappaT = 5.0919e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -7.149e-04\n",
      "Done: Iteration = 68, Next KappaT = 5.0910e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -6.558e-04\n",
      "Done: Iteration = 69, Next KappaT = 5.0902e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -6.016e-04\n",
      "Done: Iteration = 70, Next KappaT = 5.0894e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -5.519e-04\n",
      "Done: Iteration = 71, Next KappaT = 5.0887e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -5.063e-04\n",
      "Done: Iteration = 72, Next KappaT = 5.0881e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -4.644e-04\n",
      "Done: Iteration = 73, Next KappaT = 5.0875e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -4.260e-04\n",
      "Done: Iteration = 74, Next KappaT = 5.0869e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -3.908e-04\n",
      "Done: Iteration = 75, Next KappaT = 5.0864e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -3.585e-04\n",
      "Done: Iteration = 76, Next KappaT = 5.0860e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -3.289e-04\n",
      "Done: Iteration = 77, Next KappaT = 5.0855e-10\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -3.017e-04\n",
      "Done: Iteration = 78, Next KappaT = 5.0852e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.768e-04\n",
      "Done: Iteration = 79, Next KappaT = 5.0848e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.539e-04\n",
      "Done: Iteration = 80, Next KappaT = 5.0845e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.329e-04\n",
      "Done: Iteration = 81, Next KappaT = 5.0842e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.137e-04\n",
      "Done: Iteration = 82, Next KappaT = 5.0839e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.960e-04\n",
      "Done: Iteration = 83, Next KappaT = 5.0837e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.798e-04\n",
      "Done: Iteration = 84, Next KappaT = 5.0834e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.650e-04\n",
      "Done: Iteration = 85, Next KappaT = 5.0832e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.513e-04\n",
      "Done: Iteration = 86, Next KappaT = 5.0830e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.388e-04\n",
      "Done: Iteration = 87, Next KappaT = 5.0829e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.273e-04\n",
      "Done: Iteration = 88, Next KappaT = 5.0827e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.168e-04\n",
      "Done: Iteration = 89, Next KappaT = 5.0826e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.071e-04\n",
      "Done: Iteration = 90, Next KappaT = 5.0824e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.828e-05\n",
      "Done: Iteration = 91, Next KappaT = 5.0823e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.019e-05\n",
      "Done: Iteration = 92, Next KappaT = 5.0822e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.272e-05\n",
      "Done: Iteration = 93, Next KappaT = 5.0821e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.587e-05\n",
      "Done: Iteration = 94, Next KappaT = 5.0820e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.961e-05\n",
      "Done: Iteration = 95, Next KappaT = 5.0819e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.387e-05\n",
      "Done: Iteration = 96, Next KappaT = 5.0818e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.855e-05\n",
      "Done: Iteration = 97, Next KappaT = 5.0817e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.374e-05\n",
      "Done: Iteration = 98, Next KappaT = 5.0817e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.928e-05\n",
      "Done: Iteration = 99, Next KappaT = 5.0816e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.525e-05\n",
      "Done: Iteration = 100, Next KappaT = 5.0815e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.150e-05\n",
      "Done: Iteration = 101, Next KappaT = 5.0815e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.807e-05\n",
      "Done: Iteration = 102, Next KappaT = 5.0814e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.492e-05\n",
      "Done: Iteration = 103, Next KappaT = 5.0814e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.204e-05\n",
      "Done: Iteration = 104, Next KappaT = 5.0814e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.934e-05\n",
      "Done: Iteration = 105, Next KappaT = 5.0813e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.693e-05\n",
      "Done: Iteration = 106, Next KappaT = 5.0813e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.473e-05\n",
      "Done: Iteration = 107, Next KappaT = 5.0813e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.271e-05\n",
      "Done: Iteration = 108, Next KappaT = 5.0812e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.079e-05\n",
      "Done: Iteration = 109, Next KappaT = 5.0812e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.911e-05\n",
      "Done: Iteration = 110, Next KappaT = 5.0812e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.749e-05\n",
      "Done: Iteration = 111, Next KappaT = 5.0812e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.608e-05\n",
      "Done: Iteration = 112, Next KappaT = 5.0811e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.473e-05\n",
      "Done: Iteration = 113, Next KappaT = 5.0811e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.349e-05\n",
      "Done: Iteration = 114, Next KappaT = 5.0811e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.241e-05\n",
      "Done: Iteration = 115, Next KappaT = 5.0811e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.137e-05\n",
      "Done: Iteration = 116, Next KappaT = 5.0811e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.041e-05\n",
      "Done: Iteration = 117, Next KappaT = 5.0811e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.597e-06\n",
      "Done: Iteration = 118, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.788e-06\n",
      "Done: Iteration = 119, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.047e-06\n",
      "Done: Iteration = 120, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.369e-06\n",
      "Done: Iteration = 121, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.748e-06\n",
      "Done: Iteration = 122, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.243e-06\n",
      "Done: Iteration = 123, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.717e-06\n",
      "Done: Iteration = 124, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.235e-06\n",
      "Done: Iteration = 125, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.794e-06\n",
      "Done: Iteration = 126, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.390e-06\n",
      "Done: Iteration = 127, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.020e-06\n",
      "Done: Iteration = 128, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.681e-06\n",
      "Done: Iteration = 129, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.370e-06\n",
      "Done: Iteration = 130, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.151e-06\n",
      "Done: Iteration = 131, Next KappaT = 5.0810e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.885e-06\n",
      "Done: Iteration = 132, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.642e-06\n",
      "Done: Iteration = 133, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.419e-06\n",
      "Done: Iteration = 134, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.215e-06\n",
      "Done: Iteration = 135, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.029e-06\n",
      "Done: Iteration = 136, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.858e-06\n",
      "Done: Iteration = 137, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.701e-06\n",
      "Done: Iteration = 138, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.558e-06\n",
      "Done: Iteration = 139, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.426e-06\n",
      "Done: Iteration = 140, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.306e-06\n",
      "Done: Iteration = 141, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.196e-06\n",
      "Done: Iteration = 142, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.095e-06\n",
      "Done: Iteration = 143, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.003e-06\n",
      "Done: Iteration = 144, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.183e-07\n",
      "Done: Iteration = 145, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.409e-07\n",
      "Done: Iteration = 146, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.700e-07\n",
      "Done: Iteration = 147, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.051e-07\n",
      "Done: Iteration = 148, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.457e-07\n",
      "Done: Iteration = 149, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.912e-07\n",
      "Done: Iteration = 150, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.414e-07\n",
      "Done: Iteration = 151, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.958e-07\n",
      "Done: Iteration = 152, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.540e-07\n",
      "Done: Iteration = 153, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.157e-07\n",
      "Done: Iteration = 154, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.807e-07\n",
      "Done: Iteration = 155, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.486e-07\n",
      "Done: Iteration = 156, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.192e-07\n",
      "Done: Iteration = 157, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.923e-07\n",
      "Done: Iteration = 158, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.676e-07\n",
      "Done: Iteration = 159, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.451e-07\n",
      "Done: Iteration = 160, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.244e-07\n",
      "Done: Iteration = 161, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.055e-07\n",
      "Done: Iteration = 162, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.882e-07\n",
      "Done: Iteration = 163, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.723e-07\n",
      "Done: Iteration = 164, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.578e-07\n",
      "Done: Iteration = 165, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.445e-07\n",
      "Done: Iteration = 166, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.323e-07\n",
      "Done: Iteration = 167, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.212e-07\n",
      "Done: Iteration = 168, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.109e-07\n",
      "Done: Iteration = 169, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.016e-07\n",
      "Done: Iteration = 170, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.303e-08\n",
      "Done: Iteration = 171, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.518e-08\n",
      "Done: Iteration = 172, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.800e-08\n",
      "Done: Iteration = 173, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.143e-08\n",
      "Done: Iteration = 174, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.541e-08\n",
      "Done: Iteration = 175, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.989e-08\n",
      "Done: Iteration = 176, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.484e-08\n",
      "Done: Iteration = 177, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.022e-08\n",
      "Done: Iteration = 178, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.599e-08\n",
      "Done: Iteration = 179, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.211e-08\n",
      "Done: Iteration = 180, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.856e-08\n",
      "Done: Iteration = 181, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.531e-08\n",
      "Done: Iteration = 182, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.233e-08\n",
      "Done: Iteration = 183, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.961e-08\n",
      "Done: Iteration = 184, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.711e-08\n",
      "Done: Iteration = 185, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.483e-08\n",
      "Done: Iteration = 186, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.273e-08\n",
      "Done: Iteration = 187, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.082e-08\n",
      "Done: Iteration = 188, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.906e-08\n",
      "Done: Iteration = 189, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.746e-08\n",
      "Done: Iteration = 190, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.598e-08\n",
      "Done: Iteration = 191, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.464e-08\n",
      "Done: Iteration = 192, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.340e-08\n",
      "Done: Iteration = 193, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.227e-08\n",
      "Done: Iteration = 194, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.124e-08\n",
      "Done: Iteration = 195, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.029e-08\n",
      "Done: Iteration = 196, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.424e-09\n",
      "Done: Iteration = 197, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.629e-09\n",
      "Done: Iteration = 198, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.902e-09\n",
      "Done: Iteration = 199, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.236e-09\n",
      "Done: Iteration = 200, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.626e-09\n",
      "Done: Iteration = 201, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.067e-09\n",
      "Done: Iteration = 202, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.556e-09\n",
      "Done: Iteration = 203, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.088e-09\n",
      "Done: Iteration = 204, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.659e-09\n",
      "Done: Iteration = 205, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.266e-09\n",
      "Done: Iteration = 206, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.906e-09\n",
      "Done: Iteration = 207, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.577e-09\n",
      "Done: Iteration = 208, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.276e-09\n",
      "Done: Iteration = 209, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.999e-09\n",
      "Done: Iteration = 210, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.747e-09\n",
      "Done: Iteration = 211, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.515e-09\n",
      "Done: Iteration = 212, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.303e-09\n",
      "Done: Iteration = 213, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.109e-09\n",
      "Done: Iteration = 214, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.931e-09\n",
      "Done: Iteration = 215, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.768e-09\n",
      "Done: Iteration = 216, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.619e-09\n",
      "Done: Iteration = 217, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.483e-09\n",
      "Done: Iteration = 218, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.358e-09\n",
      "Done: Iteration = 219, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.243e-09\n",
      "Done: Iteration = 220, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.139e-09\n",
      "Done: Iteration = 221, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.043e-09\n",
      "Done: Iteration = 222, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.547e-10\n",
      "Done: Iteration = 223, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.742e-10\n",
      "Done: Iteration = 224, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.005e-10\n",
      "Done: Iteration = 225, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.330e-10\n",
      "Done: Iteration = 226, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.712e-10\n",
      "Done: Iteration = 227, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.146e-10\n",
      "Done: Iteration = 228, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.628e-10\n",
      "Done: Iteration = 229, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.154e-10\n",
      "Done: Iteration = 230, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.719e-10\n",
      "Done: Iteration = 231, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.321e-10\n",
      "Done: Iteration = 232, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.957e-10\n",
      "Done: Iteration = 233, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.624e-10\n",
      "Done: Iteration = 234, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.318e-10\n",
      "Done: Iteration = 235, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.039e-10\n",
      "Done: Iteration = 236, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.782e-10\n",
      "Done: Iteration = 237, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.548e-10\n",
      "Done: Iteration = 238, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.333e-10\n",
      "Done: Iteration = 239, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.136e-10\n",
      "Done: Iteration = 240, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.956e-10\n",
      "Done: Iteration = 241, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.791e-10\n",
      "Done: Iteration = 242, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.640e-10\n",
      "Done: Iteration = 243, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.502e-10\n",
      "Done: Iteration = 244, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.376e-10\n",
      "Done: Iteration = 245, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.260e-10\n",
      "Done: Iteration = 246, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.153e-10\n",
      "Done: Iteration = 247, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.056e-10\n",
      "Done: Iteration = 248, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.671e-11\n",
      "Done: Iteration = 249, Next KappaT = 5.0809e-10\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 5.3317e+00\n",
      "Surface Area = 4.4629e+01\n",
      "KappaT = 5.0809e-10, Bo = 1.0000e+02, H = 0.203, Zcm = 0.099, W = 2.619, Rw = 2.565\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e+02\n",
      "Done with Basilisk for Bo = 1.0000e+02\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial guess for KappaT =  3.1928041543835893e-23\n",
      "------------------------------------\n",
      "Volume = 1.102e+00 and VolError = -3.087e+00\n",
      "Done: Iteration = 1, Next KappaT = 7.2869e-24\n",
      "------------------------------------\n",
      "Volume = 1.152e+00 and VolError = -3.037e+00\n",
      "Done: Iteration = 2, Next KappaT = 1.7544e-24\n",
      "------------------------------------\n",
      "Volume = 1.204e+00 and VolError = -2.985e+00\n",
      "Done: Iteration = 3, Next KappaT = 4.4534e-25\n",
      "------------------------------------\n",
      "Volume = 1.259e+00 and VolError = -2.929e+00\n",
      "Done: Iteration = 4, Next KappaT = 1.1920e-25\n",
      "------------------------------------\n",
      "Volume = 1.318e+00 and VolError = -2.870e+00\n",
      "Done: Iteration = 5, Next KappaT = 3.3665e-26\n",
      "------------------------------------\n",
      "Volume = 1.382e+00 and VolError = -2.807e+00\n",
      "Done: Iteration = 6, Next KappaT = 1.0044e-26\n",
      "------------------------------------\n",
      "Volume = 1.451e+00 and VolError = -2.738e+00\n",
      "Done: Iteration = 7, Next KappaT = 3.1695e-27\n",
      "------------------------------------\n",
      "Volume = 1.543e+00 and VolError = -2.645e+00\n",
      "Done: Iteration = 8, Next KappaT = 1.0733e-27\n",
      "------------------------------------\n",
      "Volume = 1.665e+00 and VolError = -2.524e+00\n",
      "Done: Iteration = 9, Next KappaT = 3.9615e-28\n",
      "------------------------------------\n",
      "Volume = 1.812e+00 and VolError = -2.377e+00\n",
      "Done: Iteration = 10, Next KappaT = 1.6075e-28\n",
      "------------------------------------\n",
      "Volume = 1.984e+00 and VolError = -2.205e+00\n",
      "Done: Iteration = 11, Next KappaT = 7.2129e-29\n",
      "------------------------------------\n",
      "Volume = 2.177e+00 and VolError = -2.012e+00\n",
      "Done: Iteration = 12, Next KappaT = 3.5847e-29\n",
      "------------------------------------\n",
      "Volume = 2.362e+00 and VolError = -1.827e+00\n",
      "Done: Iteration = 13, Next KappaT = 1.9473e-29\n",
      "------------------------------------\n",
      "Volume = 2.561e+00 and VolError = -1.627e+00\n",
      "Done: Iteration = 14, Next KappaT = 1.1550e-29\n",
      "------------------------------------\n",
      "Volume = 2.762e+00 and VolError = -1.427e+00\n",
      "Done: Iteration = 15, Next KappaT = 7.4307e-30\n",
      "------------------------------------\n",
      "Volume = 2.957e+00 and VolError = -1.232e+00\n",
      "Done: Iteration = 16, Next KappaT = 5.1421e-30\n",
      "------------------------------------\n",
      "Volume = 3.139e+00 and VolError = -1.049e+00\n",
      "Done: Iteration = 17, Next KappaT = 3.7930e-30\n",
      "------------------------------------\n",
      "Volume = 3.306e+00 and VolError = -8.831e-01\n",
      "Done: Iteration = 18, Next KappaT = 2.9556e-30\n",
      "------------------------------------\n",
      "Volume = 3.616e+00 and VolError = -5.726e-01\n",
      "Done: Iteration = 19, Next KappaT = 2.5325e-30\n",
      "------------------------------------\n",
      "Volume = 3.626e+00 and VolError = -5.632e-01\n",
      "Done: Iteration = 20, Next KappaT = 2.1760e-30\n",
      "------------------------------------\n",
      "Volume = 3.634e+00 and VolError = -5.547e-01\n",
      "Done: Iteration = 21, Next KappaT = 1.8742e-30\n",
      "------------------------------------\n",
      "Volume = 3.642e+00 and VolError = -5.470e-01\n",
      "Done: Iteration = 22, Next KappaT = 1.6179e-30\n",
      "------------------------------------\n",
      "Volume = 3.650e+00 and VolError = -5.385e-01\n",
      "Done: Iteration = 23, Next KappaT = 1.4001e-30\n",
      "------------------------------------\n",
      "Volume = 3.659e+00 and VolError = -5.302e-01\n",
      "Done: Iteration = 24, Next KappaT = 1.2145e-30\n",
      "------------------------------------\n",
      "Volume = 3.667e+00 and VolError = -5.219e-01\n",
      "Done: Iteration = 25, Next KappaT = 1.0561e-30\n",
      "------------------------------------\n",
      "Volume = 3.675e+00 and VolError = -5.137e-01\n",
      "Done: Iteration = 26, Next KappaT = 9.2045e-31\n",
      "------------------------------------\n",
      "Volume = 3.683e+00 and VolError = -5.056e-01\n",
      "Done: Iteration = 27, Next KappaT = 8.0410e-31\n",
      "------------------------------------\n",
      "Volume = 3.691e+00 and VolError = -4.976e-01\n",
      "Done: Iteration = 28, Next KappaT = 7.0407e-31\n",
      "------------------------------------\n",
      "Volume = 3.699e+00 and VolError = -4.897e-01\n",
      "Done: Iteration = 29, Next KappaT = 6.1788e-31\n",
      "------------------------------------\n",
      "Volume = 3.707e+00 and VolError = -4.818e-01\n",
      "Done: Iteration = 30, Next KappaT = 5.4346e-31\n",
      "------------------------------------\n",
      "Volume = 3.715e+00 and VolError = -4.740e-01\n",
      "Done: Iteration = 31, Next KappaT = 4.7906e-31\n",
      "------------------------------------\n",
      "Volume = 3.723e+00 and VolError = -4.663e-01\n",
      "Done: Iteration = 32, Next KappaT = 4.2322e-31\n",
      "------------------------------------\n",
      "Volume = 3.730e+00 and VolError = -4.586e-01\n",
      "Done: Iteration = 33, Next KappaT = 3.7469e-31\n",
      "------------------------------------\n",
      "Volume = 3.738e+00 and VolError = -4.510e-01\n",
      "Done: Iteration = 34, Next KappaT = 3.3244e-31\n",
      "------------------------------------\n",
      "Volume = 3.745e+00 and VolError = -4.435e-01\n",
      "Done: Iteration = 35, Next KappaT = 2.9558e-31\n",
      "------------------------------------\n",
      "Volume = 3.753e+00 and VolError = -4.360e-01\n",
      "Done: Iteration = 36, Next KappaT = 2.6336e-31\n",
      "------------------------------------\n",
      "Volume = 3.760e+00 and VolError = -4.286e-01\n",
      "Done: Iteration = 37, Next KappaT = 2.3514e-31\n",
      "------------------------------------\n",
      "Volume = 3.768e+00 and VolError = -4.213e-01\n",
      "Done: Iteration = 38, Next KappaT = 2.1037e-31\n",
      "------------------------------------\n",
      "Volume = 3.775e+00 and VolError = -4.140e-01\n",
      "Done: Iteration = 39, Next KappaT = 1.8860e-31\n",
      "------------------------------------\n",
      "Volume = 3.782e+00 and VolError = -4.067e-01\n",
      "Done: Iteration = 40, Next KappaT = 1.6943e-31\n",
      "------------------------------------\n",
      "Volume = 3.789e+00 and VolError = -3.995e-01\n",
      "Done: Iteration = 41, Next KappaT = 1.5251e-31\n",
      "------------------------------------\n",
      "Volume = 3.796e+00 and VolError = -3.923e-01\n",
      "Done: Iteration = 42, Next KappaT = 1.3755e-31\n",
      "------------------------------------\n",
      "Volume = 3.804e+00 and VolError = -3.852e-01\n",
      "Done: Iteration = 43, Next KappaT = 1.2430e-31\n",
      "------------------------------------\n",
      "Volume = 3.811e+00 and VolError = -3.781e-01\n",
      "Done: Iteration = 44, Next KappaT = 1.1255e-31\n",
      "------------------------------------\n",
      "Volume = 3.818e+00 and VolError = -3.711e-01\n",
      "Done: Iteration = 45, Next KappaT = 1.0211e-31\n",
      "------------------------------------\n",
      "Volume = 3.825e+00 and VolError = -3.640e-01\n",
      "Done: Iteration = 46, Next KappaT = 9.2821e-32\n",
      "------------------------------------\n",
      "Volume = 3.832e+00 and VolError = -3.571e-01\n",
      "Done: Iteration = 47, Next KappaT = 8.4535e-32\n",
      "------------------------------------\n",
      "Volume = 3.839e+00 and VolError = -3.502e-01\n",
      "Done: Iteration = 48, Next KappaT = 7.7135e-32\n",
      "------------------------------------\n",
      "Volume = 3.855e+00 and VolError = -3.336e-01\n",
      "Done: Iteration = 49, Next KappaT = 7.0702e-32\n",
      "------------------------------------\n",
      "Volume = 3.915e+00 and VolError = -2.739e-01\n",
      "Done: Iteration = 50, Next KappaT = 6.5861e-32\n",
      "------------------------------------\n",
      "Volume = 3.965e+00 and VolError = -2.240e-01\n",
      "Done: Iteration = 51, Next KappaT = 6.2173e-32\n",
      "------------------------------------\n",
      "Volume = 4.006e+00 and VolError = -1.827e-01\n",
      "Done: Iteration = 52, Next KappaT = 5.9333e-32\n",
      "------------------------------------\n",
      "Volume = 4.040e+00 and VolError = -1.487e-01\n",
      "Done: Iteration = 53, Next KappaT = 5.7128e-32\n",
      "------------------------------------\n",
      "Volume = 4.068e+00 and VolError = -1.207e-01\n",
      "Done: Iteration = 54, Next KappaT = 5.5404e-32\n",
      "------------------------------------\n",
      "Volume = 4.091e+00 and VolError = -9.786e-02\n",
      "Done: Iteration = 55, Next KappaT = 5.4048e-32\n",
      "------------------------------------\n",
      "Volume = 4.110e+00 and VolError = -7.923e-02\n",
      "Done: Iteration = 56, Next KappaT = 5.2978e-32\n",
      "------------------------------------\n",
      "Volume = 4.125e+00 and VolError = -6.408e-02\n",
      "Done: Iteration = 57, Next KappaT = 5.2129e-32\n",
      "------------------------------------\n",
      "Volume = 4.137e+00 and VolError = -5.178e-02\n",
      "Done: Iteration = 58, Next KappaT = 5.1454e-32\n",
      "------------------------------------\n",
      "Volume = 4.147e+00 and VolError = -4.181e-02\n",
      "Done: Iteration = 59, Next KappaT = 5.0917e-32\n",
      "------------------------------------\n",
      "Volume = 4.155e+00 and VolError = -3.374e-02\n",
      "Done: Iteration = 60, Next KappaT = 5.0487e-32\n",
      "------------------------------------\n",
      "Volume = 4.162e+00 and VolError = -2.722e-02\n",
      "Done: Iteration = 61, Next KappaT = 5.0143e-32\n",
      "------------------------------------\n",
      "Volume = 4.167e+00 and VolError = -2.195e-02\n",
      "Done: Iteration = 62, Next KappaT = 4.9868e-32\n",
      "------------------------------------\n",
      "Volume = 4.171e+00 and VolError = -1.769e-02\n",
      "Done: Iteration = 63, Next KappaT = 4.9648e-32\n",
      "------------------------------------\n",
      "Volume = 4.175e+00 and VolError = -1.426e-02\n",
      "Done: Iteration = 64, Next KappaT = 4.9471e-32\n",
      "------------------------------------\n",
      "Volume = 4.177e+00 and VolError = -1.149e-02\n",
      "Done: Iteration = 65, Next KappaT = 4.9329e-32\n",
      "------------------------------------\n",
      "Volume = 4.180e+00 and VolError = -9.257e-03\n",
      "Done: Iteration = 66, Next KappaT = 4.9214e-32\n",
      "------------------------------------\n",
      "Volume = 4.181e+00 and VolError = -7.457e-03\n",
      "Done: Iteration = 67, Next KappaT = 4.9123e-32\n",
      "------------------------------------\n",
      "Volume = 4.183e+00 and VolError = -6.007e-03\n",
      "Done: Iteration = 68, Next KappaT = 4.9049e-32\n",
      "------------------------------------\n",
      "Volume = 4.184e+00 and VolError = -4.838e-03\n",
      "Done: Iteration = 69, Next KappaT = 4.8990e-32\n",
      "------------------------------------\n",
      "Volume = 4.185e+00 and VolError = -3.896e-03\n",
      "Done: Iteration = 70, Next KappaT = 4.8942e-32\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -3.138e-03\n",
      "Done: Iteration = 71, Next KappaT = 4.8904e-32\n",
      "------------------------------------\n",
      "Volume = 4.186e+00 and VolError = -2.527e-03\n",
      "Done: Iteration = 72, Next KappaT = 4.8873e-32\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -2.035e-03\n",
      "Done: Iteration = 73, Next KappaT = 4.8848e-32\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.638e-03\n",
      "Done: Iteration = 74, Next KappaT = 4.8828e-32\n",
      "------------------------------------\n",
      "Volume = 4.187e+00 and VolError = -1.319e-03\n",
      "Done: Iteration = 75, Next KappaT = 4.8812e-32\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -1.062e-03\n",
      "Done: Iteration = 76, Next KappaT = 4.8799e-32\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -8.552e-04\n",
      "Done: Iteration = 77, Next KappaT = 4.8788e-32\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -6.886e-04\n",
      "Done: Iteration = 78, Next KappaT = 4.8780e-32\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -5.545e-04\n",
      "Done: Iteration = 79, Next KappaT = 4.8773e-32\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -4.464e-04\n",
      "Done: Iteration = 80, Next KappaT = 4.8768e-32\n",
      "------------------------------------\n",
      "Volume = 4.188e+00 and VolError = -3.595e-04\n",
      "Done: Iteration = 81, Next KappaT = 4.8763e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.894e-04\n",
      "Done: Iteration = 82, Next KappaT = 4.8760e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.330e-04\n",
      "Done: Iteration = 83, Next KappaT = 4.8757e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.876e-04\n",
      "Done: Iteration = 84, Next KappaT = 4.8755e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.511e-04\n",
      "Done: Iteration = 85, Next KappaT = 4.8753e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.216e-04\n",
      "Done: Iteration = 86, Next KappaT = 4.8751e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.791e-05\n",
      "Done: Iteration = 87, Next KappaT = 4.8750e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.894e-05\n",
      "Done: Iteration = 88, Next KappaT = 4.8749e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.347e-05\n",
      "Done: Iteration = 89, Next KappaT = 4.8748e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.115e-05\n",
      "Done: Iteration = 90, Next KappaT = 4.8748e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.109e-05\n",
      "Done: Iteration = 91, Next KappaT = 4.8747e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.321e-05\n",
      "Done: Iteration = 92, Next KappaT = 4.8747e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.662e-05\n",
      "Done: Iteration = 93, Next KappaT = 4.8747e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.147e-05\n",
      "Done: Iteration = 94, Next KappaT = 4.8746e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.723e-05\n",
      "Done: Iteration = 95, Next KappaT = 4.8746e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.390e-05\n",
      "Done: Iteration = 96, Next KappaT = 4.8746e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.130e-05\n",
      "Done: Iteration = 97, Next KappaT = 4.8746e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.055e-06\n",
      "Done: Iteration = 98, Next KappaT = 4.8746e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.297e-06\n",
      "Done: Iteration = 99, Next KappaT = 4.8746e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.921e-06\n",
      "Done: Iteration = 100, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.637e-06\n",
      "Done: Iteration = 101, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.837e-06\n",
      "Done: Iteration = 102, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.005e-06\n",
      "Done: Iteration = 103, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.559e-06\n",
      "Done: Iteration = 104, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.004e-06\n",
      "Done: Iteration = 105, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.570e-06\n",
      "Done: Iteration = 106, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.229e-06\n",
      "Done: Iteration = 107, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.630e-07\n",
      "Done: Iteration = 108, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.544e-07\n",
      "Done: Iteration = 109, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.964e-07\n",
      "Done: Iteration = 110, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.236e-07\n",
      "Done: Iteration = 111, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.883e-07\n",
      "Done: Iteration = 112, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.823e-07\n",
      "Done: Iteration = 113, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.994e-07\n",
      "Done: Iteration = 114, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.345e-07\n",
      "Done: Iteration = 115, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.836e-07\n",
      "Done: Iteration = 116, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.438e-07\n",
      "Done: Iteration = 117, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.126e-07\n",
      "Done: Iteration = 118, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.819e-08\n",
      "Done: Iteration = 119, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.907e-08\n",
      "Done: Iteration = 120, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.409e-08\n",
      "Done: Iteration = 121, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.236e-08\n",
      "Done: Iteration = 122, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.317e-08\n",
      "Done: Iteration = 123, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.598e-08\n",
      "Done: Iteration = 124, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.035e-08\n",
      "Done: Iteration = 125, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.593e-08\n",
      "Done: Iteration = 126, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.248e-08\n",
      "Done: Iteration = 127, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.773e-09\n",
      "Done: Iteration = 128, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -7.654e-09\n",
      "Done: Iteration = 129, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.994e-09\n",
      "Done: Iteration = 130, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.695e-09\n",
      "Done: Iteration = 131, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.677e-09\n",
      "Done: Iteration = 132, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.879e-09\n",
      "Done: Iteration = 133, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.255e-09\n",
      "Done: Iteration = 134, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.766e-09\n",
      "Done: Iteration = 135, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.383e-09\n",
      "Done: Iteration = 136, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.083e-09\n",
      "Done: Iteration = 137, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -8.483e-10\n",
      "Done: Iteration = 138, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -6.644e-10\n",
      "Done: Iteration = 139, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -5.203e-10\n",
      "Done: Iteration = 140, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -4.075e-10\n",
      "Done: Iteration = 141, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -3.191e-10\n",
      "Done: Iteration = 142, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -2.499e-10\n",
      "Done: Iteration = 143, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.957e-10\n",
      "Done: Iteration = 144, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.533e-10\n",
      "Done: Iteration = 145, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -1.201e-10\n",
      "Done: Iteration = 146, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n",
      "Volume = 4.189e+00 and VolError = -9.402e-11\n",
      "Done: Iteration = 147, Next KappaT = 4.8745e-32\n",
      "------------------------------------\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------\n",
      "(3V)(4pi)^{-1} = 1.0000e+00\n",
      "Perimeter = 9.2358e+00\n",
      "Surface Area = 1.3399e+02\n",
      "KappaT = 4.8745e-32, Bo = 1.0000e+03, H = 0.063, Zcm = 0.032, W = 4.603, Rw = 4.586\n",
      "<------------------------------------>\n",
      "Doing Basilisk now for Bo = 1.0000e+03\n",
      "Done with Basilisk for Bo = 1.0000e+03\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1080 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Learning rate for the gradient descent algorithm and the maximum number of iterations, whether to plot the results, whether to plot error decay from the gradient descent, and the domain length for Basilisk code\n",
    "lr, CountMax, Plot, PlotError, L0, TestWithBasilisk = 0.25, 500, True, True, 8.0, True\n",
    "# TestWithBasilisk True needs a compiled Basilisk code in the same folder called InitialCondition.c. If you do not have this code, set TestWithBasilisk to False.\n",
    "\n",
    "# Bond number is the input parameter. Use an array here to loop over multiple Bond numbers if needed. \n",
    "BondNumbers = array([1e-3, 1e-2, 1e-1, 1e0, 1e1, 1e2, 1e3])\n",
    "\n",
    "KappaTlist = zeros_like(BondNumbers)\n",
    "Bond = zeros_like(BondNumbers)\n",
    "Height = zeros_like(BondNumbers)\n",
    "Zcm = zeros_like(BondNumbers)\n",
    "Width = zeros_like(BondNumbers)\n",
    "Rfoot = zeros_like(BondNumbers)\n",
    "Perimeter = zeros_like(BondNumbers)\n",
    "SurfaceArea = zeros_like(BondNumbers)\n",
    "\n",
    "folder='TestingImages'\n",
    "if not os.path.exists(folder):\n",
    "    os.makedirs(folder)\n",
    "TableFile='NormalizeBond.csv'\n",
    "if os.path.exists(TableFile):\n",
    "   df = pd.read_csv(TableFile)\n",
    "   Table=True\n",
    "   # df.head()\n",
    "else:\n",
    "   KappaGuess = 2.0\n",
    "   Table=False\n",
    "\n",
    "for Bo in BondNumbers:\n",
    "  if Table:\n",
    "     # find the index of the closest value to the input value\n",
    "     idx = (abs(df['Bond'] - Bo)).argmin()\n",
    "     # print(idx)\n",
    "     KappaT = df['KappaTR0'][idx]\n",
    "  else:\n",
    "      KappaT = KappaGuess\n",
    "  \n",
    "  print(\"Initial guess for KappaT = \", KappaT)\n",
    "\n",
    "  R, Z, S, Phi, r, z, KappaT, Error = CorrectDrop(Bo, CountMax, lr, KappaT)\n",
    "\n",
    "  if PlotError:\n",
    "       plt.plot(abs(array(Error)), 'k.')\n",
    "       plt.xlabel('Iteration')\n",
    "       plt.ylabel('Error')\n",
    "       plt.yscale('log')\n",
    "       plt.show()\n",
    "  # Save some metrics\n",
    "  Rfoot[where(BondNumbers==Bo)] = R[-2]\n",
    "  # width and height of the drop\n",
    "  Height[where(BondNumbers==Bo)] = Z.max()\n",
    "  Width[where(BondNumbers==Bo)] = R.max()\n",
    "  # center of mass\n",
    "  Zcm[where(BondNumbers==Bo)] = centerOfMass(R, Z)\n",
    "  # Volume of the drop\n",
    "  Vol = volume(R, Z)\n",
    "  Vol /= (4.0/3.0)*pi        \n",
    "  # Perimeter of the drop\n",
    "  Perimeter[where(BondNumbers==Bo)] = S[-1]\n",
    "  # Surface area of the drop\n",
    "  SurfaceArea[where(BondNumbers==Bo)] = surface(R, Z, S)\n",
    "  KappaTlist[where(BondNumbers==Bo)] = KappaT\n",
    "\n",
    "  # Print some metrics!\n",
    "  print('------------------------------------')\n",
    "  print('(3V)(4pi)^{-1} = %5.4e' % Vol)\n",
    "  print('Perimeter = %5.4e' % Perimeter[where(BondNumbers==Bo)])\n",
    "  print('Surface Area = %5.4e' % SurfaceArea[where(BondNumbers==Bo)])\n",
    "\n",
    "  print('KappaT = %5.4e, Bo = %5.4e, H = %4.3f, Zcm = %4.3f, W = %4.3f, Rw = %4.3f' % (KappaT, Bo, float(Height[where(BondNumbers==Bo)]), float(Zcm[where(BondNumbers==Bo)]), float(Width[where(BondNumbers==Bo)]), float(Rfoot[where(BondNumbers==Bo)])))\n",
    "  print('<------------------------------------>')\n",
    "\n",
    "  if TestWithBasilisk:\n",
    "     print('Doing Basilisk now for Bo = %5.4e' % Bo)\n",
    "     Interface = pd.DataFrame({'x': Z, 'y': R})\n",
    "     InitConditionFile='%s/InitialCondition_Bo%4.3f.dat' % (folder, Bo)\n",
    "     Interface.to_csv(InitConditionFile, index=False, header=False, sep=' ')\n",
    "     # Run Basilisk\n",
    "     InterfaceBas = gettingFacets(L0, InitConditionFile)\n",
    "     print('Done with Basilisk for Bo = %5.4e' % Bo)\n",
    "  else:\n",
    "     InterfaceBas = None\n",
    "     \n",
    "  if Plot:\n",
    "    filename = '%s/Drops_Bond_%5.4f.pdf' % (folder, Bo)\n",
    "    Plotting(R, Z, S, Phi, r, z, filename, Bo, KappaT, Zcm[where(BondNumbers==Bo)], InterfaceBas, TestWithBasilisk)"
   ]
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